The application’s user interface is highly customizable, allowing you to arrange tool windows like the Viewer, Properties, and Application Network to best suit your workflow. Windows can be “docked” to the edges of the main application or other window, grouped with other windows in tabs, or “floated” as independent windows on your desktop. This flexibility enables you to create a personalized layout that keeps the tools you need most frequently within easy reach.

Window Title Bar and Context Menu

Each tool window has a title bar containing several controls for managing its state. You can access these functions by right-clicking the title bar or by using buttons provided on the title bar directly.

Undocking and Floating Windows

A floating window is one that is detached from the main application window and can be moved freely around your screen, even to a second monitor. To make a window float:

• Drag the Title Bar: Click and hold the title bar of any docked window and drag it away from the edge. As you drag it towards the center of the screen, it will detach and become a floating window.
• Drag the Tab: For windows docked as tabs in same pane as other windows, drag the window by its tab.
• Use the Context Menu: Open the window’s context menu and select the Float option. The window will immediately detach from its docked position.

Docking Windows

To dock a floating window, simply drag it by its title bar. As you move it over the main application window or any floating window, a set of docking guide icons will appear. Dropping the window onto one of these icons will dock it to the corresponding location.

• Edge Docking: The four arrow icons at the edges of the screen will dock the window to the top, bottom, left, or right side of the main application, spanning its full width or height.
• Pane Docking: The five-icon control that appears in the center of an existing window pane allows for more precise placement. The four outer arrows will dock the window to the side of that specific pane, creating a split view. The center icon will dock the window as a new tab within that pane group.
• Document Area: One pane is designated as the central document area. It occupies the main, central space of the application window. The other docking guides for top, bottom, left, and right positions are usually arranged around this central area.
• Context Menu Docking: You can also use the context menu of a floating window. Dock will typically return it to its last docked position, while Dock as Document will place it as a tab in the central document area.

Note: The Application window is the central point of any EVS application and layout. It can only be either docked in the Document Area or made a floating window.

Auto-Hiding Windows (Pinning)

The Auto-Hide feature allows you to keep windows accessible without them permanently taking up screen space. You can control this using the pin icon in the window’s title bar or the Auto Hide option in the context menu.

• Pinned (Vertical Pin): When the pin icon is vertical, the window is pinned open. It will remain visible in its docked location.
• Unpinned / Auto-Hidden (Horizontal Pin): When the pin icon is horizontal, the window is set to auto-hide. It will collapse into a named tab on the edge of the window. To temporarily view it, simply hover your cursor over its tab. It will slide out for you to use and slide away again when you move your cursor off it. To keep it open, click the pin icon to return it to the pinned state.

Saving and Loading Layouts

When you created a layout you like, you can save it through the Options in the Menu. Layouts can be switched to previously saved ones through either the Menu or the Window Layouts button in the Main Toolbar.

Presentation Mode optimizes the user interface for interacting with a completed application. It simplifies the workspace by hiding development-focused UI elements, allowing you to focus on the application’s controls and outputs.

Accessing Presentation Mode

You can enable Presentation Mode using the Presentation Mode button in the Main Toolbar.

Presentation mode can be left using the Edit Mode button in the Main Toolbar. This button is only visible when Presentation Mode is active.

Purpose of Presentation Mode

Presentation Mode provides a cleaner, more streamlines experience ideal for presenting your work or for any scenario where you are primarily executing and interacting with the application rather than building or modifying it.

For this reason, the following elements are hidden or inactive:

• Application Window: The window containing the application workflow and for adding new modules is hidden.
• Module and Port Connections: The ability to create or modify connections between modules is disabled.
• Main Toolbar: Most buttons focused on creating applications are hidden.

Presentation Mode vs. EVS Presentation Files

While Presentation Mode is similar to the view when loading an EVS Presentation file, it is less restrictive. An EVS Presentation file (.evsp) is a self-contained, read-only version of an application that limits user editing and intended for delivery to end users. Its main purpose is for distribution to clients who need to run an application and change predetermined properties, but not modify it.

In contrast, Presentation Mode still allows for editing of module and application properties and options. It is merely a simplified user interface. This provides a flexible way to display interactive applications that are simplified for presentations but not entirely locked down.

Accessing Help

The help can be found through the Help Windows button in the Main Toolbar.

General Application Help

For general information, searching, and browsing all help topics, you can use the main Help window.

1. In the Main Toolbar, click the Help Windows button.
2. From the dropdown menu, select Contents.

This action opens the main Help window, where you can search for topics.

Module-Specific Help

When the Module Help window is opened, any module being edited (selected in the application window) will also show its help contents in the Module Help window. As you edit different modules, the Module Help will reflect the currently selected module.

To get help for a module which hasn’t been instanced, follow these steps:

1. Hover your mouse over the question mark in the desired module in the Module Library.
2. Wait for the module’s tooltip to appear:
   1. 
3. While the tooltip is visible, press the F1 key.

This will open the Module Help window containing specific information for that module.

The Tools menu provides a collection of utilities for file conversion, data processing, and creating animations. These tools are designed to help you prepare your data for use in EVS.

Accessing Tools

The Tools button can be found in the Main Toolbar. Clicking it will open a list of available tools.

Tool Buttons

EVS Input File Conversions

This section contains tools for processing and converting various data files into formats optimized for EVS.

Image and Animation Tools

This group of tools helps you create animations and prepare images for use in your projects.

Legacy File Processing

This section provides tools for working with older, outdated file formats.

• Images To Animation

  The Images To Animation tool allows you to compile a sequence of individual image files into a single video animation. This is ideal for creating time-lapse visualizations, showcasing model changes over time, or presenting a series of related images, for example written by EVS through sequences and Python Scripting, as a dynamic video.

• Georeference Image

  The Georeference Image tool is a useful utility for assigning real-world geographic coordinates to raster images. This process, known as georeferencing, allows you to accurately overlay images with other spatial data in your project. The tool enables you to create and edit world files (e.g., .jgw, .tfw) or ground control point files (.gcp), which store the image’s location, scale, and orientation information.

Opening Projects

The Open screen, accessible from the main application Menu, provides a comprehensive interface for loading existing projects. It is designed to give you quick access to your recent work, sample files, and any project on your system, complete with metadata and visual previews to help you find the right file quickly.

File Access Options

Info

While applications on network drives or shared drives may load, our customers often experienced file locking or similiar access issues when saving them. For the best experience, we recommend loading applications from a local filesystem if possible.

| | Recent Documents | The default view, offering the quickest way to resume work. It presents a scrollable and searchable list of your most recently accessed projects, ordered from newest to oldest. | | Custom Path | Acts as a configurable bookmark for frequently used folders. Once you set a directory in the application’s options, this button lists all application files in that location, saving you from navigating to it manually.

Note: The Custom Path option will not recurse subdirectories. Only application files directly in the favorited directories will be shown.
| | Sample Projects | Provides access to a curated collection of official C Tech sample applications that demonstrate best practices and diverse capabilities. These are the applications used in the EVS Training tutorials.

Note: If this list is empty, the C Tech Sample Applications have not been installed. You can obtain the installer from the C Tech website at www.ctech.com.
|

Filtering and Searching

When using the open file views, you can use the search and filter boxes to quickly locate a specific project. These tools are especially useful when dealing with a long list of files.

Project Information and Preview

When you select a file, the right-hand side of the screen populates with detailed information about that project.

The Operation and User Preferences window is the central hub for configuring application-wide settings in Earth Volumetric Studio. It allows you to customize the user interface, set default behaviors for new projects, manage system resources, and personalize user information. Tailoring these settings can significantly improve your workflow and efficiency.

To access this window, click the Options button on the main application menu located on the left side of the screen.

The window is divided into several logical sections, each handling a different aspect of the application’s configuration.

The options on the left side are all user preferences, and determine the look, feel, and operation of EVS for the current user. The options on the right side change the default values used for new modules and applications.

User

This section specifies the active user and their organization. This information is saved with .evs application files and other outputs, helping to track authorship and ownership of projects.

System

The System section controls settings that impact the core operation of EVS system-wide, including file handling, hardware utilization, and integration with external tools like Python.

Setting	Description
Open EVS Files With Existing Instance	When enabled, any .evs file you open from Windows File Explorer will launch within the currently running instance of Earth Volumetric Studio. If disabled, a completely new instance of the program will be launched for each file.
Processing settings	This section allows you to manage how EVS utilizes your computer’s hardware.

• **Logical Processors (CPU) to keep unused**: Reserves a specific number of your CPU's logical processors (cores/threads) for the operating system and other applications. This prevents EVS from consuming 100% of your CPU during intensive calculations, keeping your system responsive.
• **Use GPU for fast calculations**: When enabled, EVS leverages your graphics processing unit (GPU) to accelerate certain calculations. It is recommended to keep this enabled if you have a dedicated graphics card.
• **Force Emulated GPU**: An advanced troubleshooting setting. It forces EVS to use a software-based GPU emulator instead of your physical graphics card, which can help diagnose graphics-related issues but at a significant performance cost.

User Interface Options

This section controls the visual appearance and layout of the EVS user interface.

Setting	Description
Theme	Choose a visual theme for the application. For more details, see the Themes topic. Light: A bright theme with dark text. Dark: A dark theme with light text, which can reduce eye strain.
Window Layouts	Save, manage, and apply different arrangements of the application’s windows. For more about creating layouts, see Docking and Undocking Windows and Windows and Layout.

• **Layout List**: Displays all saved layouts.
• **+ / - Buttons**: Save the current window arrangement as a new layout or delete the selected layout.
• **Apply Selected Layout**: Applies the window positions from the selected layout.
• **Overwrite Current Layout**: Updates the selected layout with the current arrangement of windows.
• **Revert to Default**: Resets the selected layout to its original state.

• **Full Size**: The default style, featuring large icons with descriptive text.
• **Comfortable**: A more compact style with smaller icons and text.
• **Compact**: A minimal style with icons only.
• **Display in Title Bar**: Moves the toolbar into the application's title bar to maximize vertical space.

• **Hide Viewer Connections**: Hides connection lines to and from Viewer modules to reduce visual clutter.
• **Always Display Minor Ports**: When enabled, all module ports are visible. When disabled, less-used "minor" ports are hidden until you hover over the module.
• **Connection Checking**: Determines how strictly EVS validates module connections. "Strict Checking" ensures data types are perfectly compatible.
• **Connection Style**: Sets the visual style of connection lines (Curved or Straight).
• **Highlight Potential Connections**: Controls which available ports are highlighted as valid targets when dragging a connection (Major Ports Only, Include Minor Ports, or None).
• **Max Potential Connections**: Limits the number of potential connections highlighted at once to maintain performance.

• **Display Expert Properties**: Reveals advanced or less commonly used module parameters.
• **Always Show Critical Properties**: Ensures that important parameters are always visible, even if their category is collapsed.
• **Automatically Collapse Categories**: When enabled, all property categories collapse when you select a new module.

• **Include Deprecated Modules**: Shows older modules kept for backward compatibility.
• **Automatically Collapse Module Categories**: When enabled, all module categories in the Module Library will be collapsed by default.

New Module and Application Default Settings

This area defines the default settings that are applied to new applications, modules, and data processing tasks.

New Application Defaults

Setting	Description
Z Scale	Sets the default vertical exaggeration (Z-Scale) for new applications.
Explode	Sets the default explode factor for new applications, which pushes modules apart in the 3D viewer.
Application Colors	Sets the default colors for elements in the Viewer window for new applications.

• **Coloring Option**: Select from predefined color schemes (Light, Dark) or choose "Custom" to enable the color pickers below.
• **Background Color**: Sets the solid background color of the Viewer.
• **Gradient Color**: Creates a two-color vertical gradient with the Background Color.
• **Foreground Color**: Defines the default color for text, axes, and other primary annotations.
• **Secondary Color**: Defines the default color for less prominent visual elements.

Module Defaults

Setting	Description
Viewer Settings	Defines the default rendering and behavior for new Viewer modules.

• **Auto Fit Scene**: Controls when the viewer automatically rescales to fit all objects (On Significant Change, On Any Change, or Never).
• **Background Style**: Sets the default background rendering style (Two Color Gradient, Solid, or Vignette).
• **Smooth Lines**: When enabled, applies anti-aliasing to produce thicker, smoother lines.

• **Default Font**: Sets the default font family for text in new modules.
• **Force True Type Fonts**: When enabled, forces modules to use scalable TrueType fonts.
• **Include Language Specific Fonts**: Loads additional font sets for displaying characters from non-Latin languages (e.g., Chinese, Japanese, or Korean).

Model Generation Defaults

Provides fine-grained control over the default parameters used in modules for gridding, data processing, and statistical estimation.

Setting Area	Description
Gridding Defaults	Defines the default settings for new gridding modules like krige_3d.

• **Grid Resolution**: Sets the default number of nodes in the X, Y, and Z dimensions.
• **Boundary Offset**: Defines a default percentage to expand the grid boundary beyond the input data extents.
• **Use Convex Hull**: When enabled, automatically uses the convex hull of the input data as the gridding boundary.
• **Use Adaptive Gridding**: When enabled, uses adaptive gridding techniques by default.

• **Pre Clip Minimum**: Sets the default minimum clipping value applied to data **before** interpolation.
• **Post Clip Minimum**: Sets the default minimum clipping value applied to data **after** interpolation.

• **Horizontal Vertical Anisotropy**: Sets the default ratio of horizontal to vertical anisotropy.
• **Use all samples if # samples below**: When enabled, the module uses all data samples for estimation if the total count is below the specified limit.
• **Number of Points**: Specifies the number of nearby data points to use for estimation.
• **Statistical Confidence Tolerance**: Sets the default tolerance for statistical confidence when data processing is "Linear".
• **Statistical Confidence Factor**: Sets the default factor for statistical confidence when data processing is set to "Log Processing".
• **Confidence for Min and Max Plume**: Sets the default statistical confidence level for determining plume extents.

Reset All Options

The Reset All Options button at the bottom of the window reverts all settings to their original factory defaults. This action is irreversible and affects all sections, so it should be used with caution.

Earth Volumetric Studio features a flexible interface composed of several windows. You can customize their size, position, and docking state to create a layout that suits your workflow.

Customizing Your Workspace with Window Layouts

EVS provides a flexible windowing system that allows you to customize the layout of your workspace. You can control the position, size, grouping, and visibility of most windows to suit your workflow. These customized layouts can be saved and reloaded, which is useful for different tasks or screen resolutions.

For example, here is an application with a personalized window layout:

Window Visibility and Docking

You can manage window visibility and docking using the controls located on each window’s title bar. While most windows can be moved, resized, or closed, there are a couple of exceptions:

1. Application Window: The main area for adding and connecting modules is always part of the main EVS application window, except in EVS Presentations or when working in Presentation mode.
2. Viewer Window: The Viewer cannot be closed, but it can be undocked and moved to another monitor for a multi-screen setup.

Example: Optimizing for a Larger Viewer

You can create different layouts to optimize your workspace. For instance, the layout below is configured to maximize the Viewer’s screen space. Notice how windows are tabbed together to save space:

• The Application and Viewer windows are tabbed, with the Viewer active.
• The Information, Packaged Files, and Output Log windows are tabbed, with the Output Log active.

Saving a Custom Window Layout

Once you have arranged the windows to your liking, you can save the layout for future use.

1. Click the Options button in the Main Toolbar.
2. In the Options window, expand the Window Layouts section.
3. Here you have the option to create a new layout or overwrite the currently active layout.
   1. Create a new layout: Click the + (Add) button to save your current window arrangement as a new layout. It will appear in the list along with any previously saved layouts and the “Default” configuration.
   2. Overwrite the current layout: Click the Overwrite Current Layout button.

Loading or reverting a Custom Window Layout

There are two ways to switch to a different layout.

The Options window

You can load a previous or revert a layout in the same section as described above.

1. Click the Options button in the Main Toolbar.
2. In the Options window, expand the Window Layouts section.
3. Here you have the option to load a layout or revert to the “Default” layout.
   1. Load a layout: Select the desired layout and click the Apply Selected Layout button or alternatively revert to the “Default” layout using the Revert to Default button.
   2. Revert to default: Click the Revert to Default button to revert the current layout to the one saved as “Default”.

The Quick Access Button

You can easily switch between your saved layouts directly from the Main Toolbar.

1. Click the dropdown arrow next to the Window Layouts button in the Main Toolbar.
2. Select your desired layout from the list to apply it instantly.

The Application Properties provide a centralized location to access critical parameters needed to control your application. Any property that impacts the application itself and is not specific to an instanced module will show here.

Accessing Application Properties

The Application Properties are available via a button in the Application Window toolbar:

Alternatively, you can also access these when editing the Application Favorites. When the Application Favorites are displayed in the Properties window, click the Switch to Application Properties button at the top.

Finally, double clicking on the background of the network area will open the Application Favorites or Application Properties (whichever was most recently viewed).

Available Application Properties

Below is the default content of Application properties.

Following is a description of each category:

• Bookmarks

  Bookmarks provide an easy way to save and recall specific configurations of your application. They act as saved “snapshots” that can instantly change the camera view, which objects are visible, and the current state of any sequences. They also export to C Tech Web Scenes. This is essential for creating presentations, standardizing views for analysis, and optimizing the user experience in any exported C Tech Web Scenes.

• Application Colors

  The Application Colors feature provides a centralized way to manage a consistent color palette across your entire application. By setting a few base colors, you can ensure that various annotation modules - such as titles, legends, and axes - as well as the viewer background all share a coordinated and professional look. This feature is particularly powerful when used with linked properties, as it allows you to switch between entire color themes (e.g., from a light to a dark theme) with a single click.

The Application Favorites feature provides a powerful way to create a custom control panel for your EVS application. It allows you to gather the most important properties from various modules and global settings into a single, centralized location within the Properties window.

This is especially useful in large or complex applications, as it eliminates the need to navigate to each individual module to adjust key parameters. Instead, you can manage all critical settings from one convenient view.

Accessing Application Favorites

The Application Favorites are available via a button in the Application Window toolbar:

Alternatively, you can also access these when editing the Application Properties. When the Application Properties are displayed in the Properties window, click the Switch to Application Favorites button at the top.

Finally, double clicking on the background of the network area will open the Application Favorites or Application Properties (whichever was most recently viewed).

The Application Favorites View

Once you switch to the Application Favorites view, you will see a list of all the properties you have marked with a star. The properties are organized into groups based on their source module. For example, global settings like Z Scale and Explode are listed under “Application Properties,” while module-specific properties are grouped under the name of their respective module (e.g., “viewer”).

You can edit any of these properties directly from this view, just as you would in the standard properties editor.

How to Favorite a Property

You can favorite almost any property from any module.

1. Select a module in the Application Network to display its parameters in the Properties window.
2. To favorite a property, click in the empty space to the left of its name. A star icon will appear, indicating that the property has been added to your Application Favorites.

It is important to note that this action favorites the property for that specific instance of the module, not for all modules of that type. This allows you to select different key parameters from different modules. The same property from different modules can appear in the Application Favorites at the same time.

How to Remove a Property from Favorites

To remove a favorited property, simply click the star icon in either the module or the Application Favorites again.

Module Properties

When you select a module in the Application Network, its settings are displayed in the Properties window. This window allows you to configure the module’s parameters and control its execution behavior. At the top of the window, the name of the module you are editing is displayed.

Switch to Display Properties

This button provides a quick way to access the properties of the module’s primary Renderable Port (red) if they are being displayed in a viewer. The Red Port Properties will also feature a button to quickly switch back again.

Execution Control

The toolbar at the top of the Module Properties window provides powerful tools for managing when and how a module executes.

• Run Toggle: This switch controls the module’s automatic execution. By default, it is on, meaning the module will automatically run whenever one of its properties is changed or when an upstream module it depends on finishes running. Toggling this off prevents the module from running automatically. This is particularly useful when you want to make multiple changes to a module’s settings without triggering potentially time-consuming computations after each adjustment. This is also displayed and configurable on the modules in the Application Network. See Module Status Indicators.
• Run Once Button: When available, this button allows you to manually trigger the execution of the currently selected module. It forces the module to run a single time. This is most effective when the Run toggle is turned off, as it lets you apply your changes and see the result without having to re-enable automatic execution.

Module-Specific Properties

Below the execution controls, the Properties section contains all the configurable parameters for the selected module. The settings here are unique to each module’s function. These properties allow you to customize the module’s behavior to fit the specific needs of your analysis.

Property Description

At the bottom of the Properties window is a description panel. This panel is your first and most important resource for understanding what a specific property does. When you select a property from the list, this panel automatically updates to show a detailed explanation of that property and its function. For instance, selecting “Data Processing” will display text explaining that this property allows to declare whether the input data is to be treated as linear or log processed. This immediate, context-sensitive help makes it easy to learn and configure even complex modules without having to consult external documentation.

Here is an example for the Property Description of the “Glyph Size” property:

Understanding Linked Properties

In Earth Volumetric Studio, a Linked Property is a parameter whose value is automatically determined within the application, rather than being manually set by the user. This dynamic connection allows for a more intelligent and consistent workflow. You can identify a linked property by the link icon located next to it in the Properties window

• When the link icon is closed/connected, the property is linked, and its value will update automatically based on its source.
• When the link icon is broken, the property is unlinked, and its value is fixed to whatever you have manually set.

You can toggle a property’s linked state by simply clicking on the link icon.

Linked Property:	Unlinked Property:

Info

Not all properties can be linked. If a property does not have a link icon next to it, it is a manual property. Its value may be set directly by the user and will not change automatically.

The Purpose of Linked Properties

Linked properties are a core feature of the EVS expert system, designed to streamline the modeling process. By linking properties, EVS can ensure consistency across your entire application, provide smart defaults based on your data, and maintain visual coherence. For example, linking the Z Scale of multiple modules to the global Application Z Scale means you only have to change it in one place, but can still unlink and override it as needed. Linked properties may also provide good automatic starting values for further unlinked manual refinement.

While you can unlink any linked property to gain manual control, it is generally recommended to keep properties linked unless you have a specific reason and understand the effect of the change. This approach leads to a faster and better-looking result.

Info

Re-linking a previously unlinked property will cause its value to revert to the automatic, context-driven setting. This change may also trigger the module to re-execute immediately to reflect the new state, unless the module’s Run toggle is turned off.

Common Categories of Linked Properties

Z Scale

This is the most common linked property and the one you should change least often. Nearly every module that deals with 3D data has a Z Scale property that is, by default, linked to the global Z Scale found in the Application Properties. This ensures that all visual components in your scene use the same vertical exaggeration, which is critical for correct spatial representation.

Colors

Many modules that create visual elements, such as titles or legends, have color properties that are linked to the global Application Colors setting. When you switch the application theme between Dark, White, or Custom, these linked colors will automatically adjust to ensure they remain visible and aesthetically pleasing against the new background color. Unlinking a color property, such as Title Color, will fix it to a specific color, and it will no longer adapt to theme changes.

Coordinates

Many modules that process spatial data have coordinate properties (e.g., Min/Max extents) that are linked to the incoming data. When the module is run, it analyzes the input field and automatically populates these properties with the correct coordinate values. If the input data changes, re-running the module will cause these linked properties to update accordingly.

Expert System Parameters

EVS includes an expert system that analyzes your data to provide intelligent, scientifically appropriate default values for complex parameters. This is most common in geostatistical modules like kriging or lithologic modeling. Parameters for kriging and variogram settings are often linked to the expert system, which suggests optimal values based on the input data. Unlinking these properties allows for manual fine-tuning but overrides the data-driven recommendations.

Port Properties

When you double-click an output port on a any module in the Application Network, the Properties window displays detailed information and settings for that specific port. While the properties shown vary depending on the type of data the port provides, certain elements are common to all ports.

At the top of the window, a Switch to Module Properties button provides a convenient way to navigate back to the properties of the module that owns the port.

Common Port Properties

All output ports display a Port Information section with the following properties:

• Red Port Properties (Renderable Port)

  Renderable Object Port Properties In Earth Volumetric Studio, a red port is a Renderable Object port. It outputs a visual object—such as a surface, a set of points, or a volume—that can be displayed in a viewer. By editing the properties of this port, you can control every aspect of how the object is visualized in the 3D scene. See the Visualization Fundamentals section for additional details on rendering options.

• Blue Port Properties (Field Port)

  Field Port Properties In Earth Volumetric Studio, a blue port is a Field Port. It is the most common port type and is responsible for passing grid structures and their associated data between modules. A “field” contains the geometry (nodes and cells) as well as any data values defined on that grid, such as analytical results or material properties.

Introduction to Datamaps

In the fields of scientific and geometric visualization, a datamap is a fundamental concept that serves as the bridge between raw numerical data and its visual representation. At its core, a datamap is a function or a lookup table that translates data values into visual properties, most commonly color. Think of it as a sophisticated legend that instructs the rendering engine how to “paint” the data onto a geometric object, such as a surface, a volume, or a set of points.

Every value in your dataset, whether it represents temperature, contaminant concentration, pressure, or a geologic material type, is assigned a color based on the rules defined in the datamap. This transformation is what turns an abstract collection of numbers into an intuitive and immediately understandable visual model. Without datamaps, a 3D model of contaminant distribution would be a colorless, featureless shape, providing no insight into where the highest concentrations are or how they vary in space. The datamap is what brings the data to life, allowing us to see the patterns, trends, and anomalies that would otherwise be hidden in spreadsheets and data files.

The Purpose of Datamaps in EVS

In Earth Volumetric Studio, datamaps are the primary tool for communicating the meaning of your data within a visual context. Their purpose extends beyond simply making things colorful; they are a critical component of data analysis and presentation for several key reasons.

First, they make complex data interpretable. A bright red area in a plume model is instantly recognizable as a “hotspot” of high concentration, while a transition from green to blue can clearly show the gradient where values are decreasing.

Second, they provide a quantitative reference. A well-designed datamap, coupled with a legend, ensures that the visualization is not just a pretty picture but a scientifically accurate representation. Each color corresponds to a specific data value or range, allowing a viewer to probe any point on a model and understand its precise quantitative meaning.

Finally, they are essential for highlighting features of interest. Data in environmental and geological sciences often spans many orders of magnitude. A datamap can be carefully designed to focus the visual contrast on the most critical parts of the data range, making subtle but important variations stand out while de-emphasizing less relevant data.

Types of Data and Datamap Processing

Datamaps in EVS are highly flexible and can be configured to handle different types of data and distributions. The way a datamap translates values to color can be linear, non-linear, or categorical.

Linear Datamaps

A linear datamap applies a smooth, uniform color gradient across the entire range of the data. The relationship between a data value and its position in the color gradient is a straight line. For example, in a dataset ranging from 0 to 1000, a value of 500 would be mapped to the exact middle of the color ramp. This type of mapping is best suited for data that is evenly distributed and where the importance of changes is consistent across the entire range, such as a simple temperature scale.

Non-Linear Datamaps

A non-linear datamap is used when the data is not uniformly distributed or when certain ranges are more important than others. In this case, the relationship between data values and colors is not a straight line. This allows you to allocate more “color space” to the most critical parts of your data range.

A classic example is contaminant concentration data, which might range from 0.01 to 10,000. If a linear datamap were used, most of the color gradient would be dedicated to the high-end values, making it impossible to distinguish between low-level concentrations (e.g., 0.1 vs. 1.0), which might be the most critical range for regulatory purposes. A non-linear datamap can be configured to stretch the color gradient across the lower values, providing high visual contrast where it is needed most.

The colors of breaks on both sides don’t have to be continuous. If the Lock Adjacent Breaks toggle in the Datamap Editor is disabled, you can choose both colors separately.

A note on precision: Due to the nature of precision in floating-point calculations, a value that is identical to a break point can be categorized into either the adjacent upper or lower interval. If you need to ensure a specific value is colored correctly, we recommend slightly shifting the break point. For example, changing a break from 500.0 to 500.0001 ensures the value 500.0 falls into the lower interval.

Categorical Data

Datamaps are also used for categorical data, which is qualitative rather than quantitative. Examples include geologic material types (“Sand”, “Clay”, “Gravel”), land-use classifications, or sample location IDs. For this type of data, the datamap assigns a single, discrete color to each unique category. There is no gradient or blending between colors. In EVS, this is typically handled by assigning an integer ID to each category (e.g., Sand=1, Clay=2). The datamap is then configured with distinct colors for each integer value, effectively creating a color key for your categorical data.

Logarithmic Processing

Logarithmic processing is a specific type of non-linear mapping designed for data that spans several orders of magnitude. By taking the logarithm of the data values before mapping them to color, vast ranges are compressed into a more manageable scale. This makes logarithmic datamaps the standard and most effective way to visualize data like hydraulic conductivity or contaminant concentrations. EVS handles this transformation automatically when the log processing option is selected in many modules, so you do not need to manually convert your data. The datamap works with the log-transformed values, but associated legends will still display the original, human-readable values.

• Datamap Editor

  The Datamap Editor is the primary tool in Earth Volumetric Studio for creating and customizing the mapping between your data values and the colors used to represent them in a visualization. It provides a powerful, interactive interface to control color gradients, data ranges, and scaling, allowing you to effectively highlight the features of interest in your data.

The Module Library is a core component of the Application window, serving as the repository for all modules used to build data processing and visualization workflows. It is located on the left side of the Application window and a fixed part of it. Unlike most other windows, it cannot be undocked, but it can be hidden when not in use.

Modules are organized into collapsible categories, such as Estimation and Geology, allowing you to easily browse and find the tools you need. You can control whether these categories are expanded or collapsed by default in the Options menu of the Application window. To add a module to your workflow, simply drag it from the library and drop it onto the Application Network canvas. Alternatively, double clicking a module will also create a new instance on the Application Network.

At the top of the Module Library, you will find controls for searching and docking.

The Search bar allows you to quickly filter the list of modules. As you type, the library will display only those modules whose names match your search query. You can also use the keyboard shortcut Ctrl+M to focus on the search bar, even if the Module Library is unpinned and closed.

Next to the search bar is the Pin button. This button controls the auto-hide behavior of the Module Library. When the library is pinned, it remains permanently visible. If you unpin it, the library will automatically slide away when not in use and can be reopened by clicking the Show Module Library button in the Application window’s toolbar or via the keyboard shortcut Ctrl+M.

Annotations

At the bottom of the Module Library is a set of tools for adding visual annotations to your Application Network. These elements help document your workflow, clarify connections, and organize complex applications. Clicking on an annotation shows contextual menu items such as Delete, Copy, Paste and a coloring option.

The Application Network is the primary workspace in Earth Volumetric Studio for building and managing your data processing workflows. It is a visual, node-based environment where you construct “applications” by placing modules and connecting them to define a data flow from input to final visualization.

Modules

Modules are the fundamental building blocks of an application. Each module performs a specific task, such as reading data, performing a calculation, creating a geometric object, or rendering a scene. They are represented by rectangles on the Application Network, each stating a user-defined name and the module type under it. You add modules to your network by dragging them from the Module Library onto the Application Network canvas.

Each module has a set of icons that appear when you hover over it, providing quick access to key functions:

See Module Icons for more information.

Ports and Connections

Modules communicate with each other through ports. Each module has one or more input ports (on the top) and output ports (on the bottom). You create Connections between modules which define the top-down Data Flow of the application, directing the output of one module to become the input for the next. See the Connecting and Disconnecting Modules topic.

Ports are color-coded to indicate the type of data they handle, and you can only connect ports of a similar color. While there are many port types, the two most critical and frequently used are Field ports and Renderable Object ports.

See Port Colors, Red Port Properties (Renderable Port) and Blue Port Properties (Field Port) for more information about ports.

How to Remove connections

Connections can be removed by selecting the connection with the left mouse button in the Application Network and then either using the DEL key or by clicking the right mouse button and choosing the Disconnect option.

Module Right-Click Menu

Right-clicking on any module in the Application Network opens a context menu that provides quick access to several common actions and properties for that module.

Input Port Context Menu

Right-clicking on a module’s input port opens a context menu providing details and actions for the incoming connection.

Output Port Context Menu

Right-clicking on a module’s output port opens a context menu with information and actions related to that specific port.

• Module Icons

  Modules in the Application Network feature a set of icons directly on their surface that provide at-a-glance information and quick control over their execution and visibility. Modules that can be executed or produce a visible output have icons on their left and right sides. The right-side icon controls execution, while the left-side icon controls visibility in the viewer.

• Module Status Indicators

  Modules in the Application Network display several visual cues to indicate their current status. These indicators help you quickly understand which module is selected, which is being edited, whether a module has run successfully, and if it is set to execute automatically. This allows for efficient management of your application’s workflow. Selection and Editing Status The border of a module changes color to reflect its selection and editing state.

• Connecting and Disconnecting Modules

  Modules in the Application Network are linked together by connections, which represent the flow of data from an output port of one module to an input port of another. Creating and removing these connections is fundamental to building and modifying your application’s workflow. The system helps ensure that you only make valid connections between compatible port types.

• Port Colors

  The color of the ports on a module provides an immediate visual cue about the type of data they accept or output. Understanding these colors and types helps in quickly assessing a module’s function and ensuring you are making valid connections within the Application Network. Port Types Each port type is designed to handle a specific kind of data. The primary types are listed below.

Finding Modules in the Application Network

For large or complex application networks, the search functionality provides an efficient way to locate specific modules. The search tool is located in the toolbar at the top of the Application window.

Using the Search Tool

The appearance of the search tool depends on the available width of the Application window. In narrower views, it may appear as a magnifying glass icon. In wider views, it will be displayed as a full search box labeled “Search for Module in Application”.

To use the search, you can either begin typing the name of the module you wish to find or click on the search box (or icon). Clicking will reveal a dropdown list containing all modules currently in the Application Network. Selecting a module from this list will immediately locate it.

Search Results

When you select a module from the search results, two actions occur simultaneously in the user interface:

1. The Application Network view will automatically pan and zoom to center on the selected module, which will be highlighted with a green outline for easy identification.
2. The **Properties**window will update to display the parameters for the selected module. This allows for immediate access to view or edit the module’s settings without needing to manually select it in the network.

This integrated functionality streamlines the process of navigating and editing complex workflows, making it easy to manage even the most extensive application networks.

The Viewer is the primary 3D visualization window in Earth Volumetric Studio. It includes a dedicated user interface for navigating the 3D scene, managing the visibility of objects, and accessing various tools. Additional, more advanced properties are available in the Properties window when the viewer module is selected.

Viewer Window Interface

The Viewer window features a sidebar on the left that contains controls for orientation, scene management, and a table of contents

View Orientation Controls

At the top of the sidebar, the orientation controls allow for precise camera positioning.

Scene and View Controls Toolbar

A toolbar below the orientation controls provides quick access to common scene management functions.

Button	Icon	Description
Save Viewer Snapshot		Saves the current contents of the viewer to an image file. Clicking the main button saves with the last used settings, while the dropdown arrow reveals several options to control the output:

• **Use Transparent Background**: If enabled (and using PNG format), the viewer background will be transparent in the saved image.
• **Prefer Lossless**: When enabled, attempts to save in a lossless format like PNG.
• **Quality**: Sets the compression quality for lossy formats like JPEG (1-100).
• **View Scale**: A multiplier for the output resolution. A scale of 2.0 will produce an image twice the width and height of the current viewer size.
• **Scale Forward Facing Text**: Ensures that text elements scale correctly with the View Scale to maintain their relative size.

Table of Contents

The Contents section at the bottom of the sidebar acts as a layer manager for your scene. It displays a hierarchical tree view of every object connected to the viewer module in the Application Network.

• Visibility Control: Each item in the list has an eye icon next to it. Clicking this icon toggles the visibility of that object in the viewer. This allows you to quickly show or hide different components of your model without disconnecting modules. Objects hidden in the Table of Contents will also be hidden in exported C Tech Web Scenes (.ctws).
• Tree Structure: If you use modules like group_objects, the Table of Contents will reflect that structure. You can expand or collapse parent items to show or hide their children, and toggling the visibility of a parent will affect all the objects grouped under it.
• Double Click Interaction: Double left-click with your mouse on any item in the Table of Contents will select that module in the the-application-window.mdApplication, as well as show it’s properties in the Properties Window.

The Python Script Editor is the integrated environment within Earth Volumetric Studio for writing, editing, and running Python scripts. It provides a full-featured text editor with syntax highlighting, code formatting tools, and direct access to execution and debugging functions, making it the central hub for all your scripting activities.

Accessing the Python Script Editor

You can open the editor through the Python Scripting button located in the Main Toolbar.

The dropdown menu provides three main options:

Once a script is created or opened, the Python Script Editor window will appear.

Editor Toolbar Reference

The toolbar at the top of the editor provides a wide range of tools for managing and editing your code.

File and Edit Operations

Execution and Recording

Code Formatting and Navigation

Additional Menus

On the far right of the toolbar are two dropdown menus for additional functionality.

Information Menu

This menu provides access to related information and output windows.

Editor Options Menu

This menu (gear icon) controls the visual display of the text editor itself.

The Python Interactive window provides a real-time environment to execute Python statements and expressions. This tool allows you to test code snippets, perform quick calculations, and inspect data without needing to run a full script.

Window Components

The interface is divided into three primary sections:

To get started with the Python Interactive window, follow these steps:

1. Enter Code: Click into the input field at the bottom of the window.
2. Evaluate: Type a mathematical expression (e.g., 42 * 29.29) or a Python command.
3. Submit: Click the play icon on the right or press your execution hotkey.
4. Review: Check the Output Area for the result or any potential error messages.

While useful as a general tool (such as using as a calculator, as shown above), the window is typically used for interacting with the EVS API directly.

This is particularly useful when writing scripts, as you can interactively inspect the structure of the EVS API calls, and modify as needed.

For example, you can see the values in a dictionary returned by the API directly:

Clicking on the grey text in the Output Area will re-select it and enter it into the Input Box, which can then be edited. Using the above, this allows us to click on the previous code (evs.get_module_exte….), and then add the entry for SelectedOption to test and make sure we are fetching the results we would expect (the name of the analyte):

This shows us the results of the entered code, which could then be reused in a Python script (such as fetching the current analyte name above for use in a title).

You can programmatically read and set the properties of any module using Python Scripting. This is a powerful feature for automating workflows and creating complex interactions between modules. The scripting engine provides programmatic access to the same underlying properties that are exposed as controls in the Properties window. This allows scripts to read, evaluate, and update values, mirroring manual user interaction. The easiest way to script a property is to copy the required syntax directly from the Properties window.

Getting a Property’s Value

To get the current value of a property and assign it to a Python variable:

1. Open the Properties window for the module you want to control.
2. Right-click on the property you want to read.
3. Select Get Value or Get Extended Value from the context menu.

This action copies a line of Python code to your clipboard. You can then paste this code into the Python Script Editor.

Reading Value Example

Right-clicking on the Explode property of the explode and scale module and selecting Get Value will copy the following syntax:

explode = evs.get_module('explode and scale', 'Properties', 'Explode')

After executing this line, the explode variable in your script will hold the current value of the Explode property. Note that the Python API call has three arguments: the module name, the category name, then the property name.

Difference between Get Value and Get Extended Value

The context menu provides two options for getting a value. The Get Value option will use the evs.get_value API call, which fetches the value that is used when saving an application, and contains whatever is required to set the property. This is the value that should be used if using evs.set_value.

The extended option will use evs.get_extended_value, which typically results in a dictionary with the original value, as well as other metadata. For example, a drop down with a list of analytes will typically just return the selected item by index in get_value, but the extended option will include other information, such as the list of options, the selected value by name and index, and more.

Setting a Property’s Value

To set the value of a property:

1. In the Properties window, right-click on the property you want to modify.
2. Select Set Value from the context menu.

This copies the Python syntax for setting the property to your clipboard. Paste the code into the Python Script Editor or the Python Interactive Window and utilize the value as needed.

Updating Value Example

For example, using the same Explode property, the copied syntax would be:

evs.set_module('explode and scale', 'Properties', 'Explode', {'Linked': True, 'Value': 0.0})

You can change 0.0 to any valid value for that property, such as:

evs.set_module('explode and scale', 'Properties', 'Explode', {'Linked': False, 'Value': 1.0})

When dealing with a Linked Property, you must first disable the link to manually set its value. This is done by setting the corresponding Linked boolean property to false. If you attempt to set the value while it is still linked, your change will be overridden as the value is determined automatically.

Executing this command in the Python Script Editor or the Python Interactive Window will update the property in the module, and the change will be immediately visible in the Properties window.

Python Functions & Operators

Earth Volumetric Studio supports Python 3.12 and 3.13. It will use the highest supported system installed version by default, but can be configured in options.

A listing of Python Functions & Operators can be found at python.org. Below are links to relevant pages:

• Functions

• Math Operators

• String Operators

• Date and Time Operators

  • Date & time syntax

Please note: C Tech does not provide Python programming or syntax assistance as a part of Technical Support (included with valid subscriptions). Python scripting and functionality is provided as an advanced feature of Earth Volumetric Studio, but is not required to use the basic functionality.

Below are Earth Volumetric Studio specific functions which provide means to get and set parameters and to act upon the modules in the libraries and network.

evs.check_cancel():

Inserting this function at one or more locations in your Python script allows you to terminate (exit) the script when it is running once this function is reached. This should be inserted in loops which may run repeatedly so that canceling the script is possible.

Keyword Arguments: None

evs.get_application_info():

Gets basic information about the current application.

Keyword Arguments: None

evs.get_module(module, category, property):

Get a value from a module within the application.

Keyword Arguments:

module – the name of the module (required)

category – the category of the property (required)

property – the name of the property to read (required)

evs.get_modules():

Gets a list of all module names in the application.

Keyword Arguments: None

evs.get_module_type(module):

Gets the type of a module given its name.

Keyword Arguments:

module – the name of the module (required)

evs.rename_module(module, newName):

Renames a module, and returns the new name.

Keyword Arguments:

module – the name of the module (required)

newName – the suggested name of the module after renaming (required)

evs.get_module_extended(module, category, property):

Get an extended value from a module within the application.

Keyword Arguments:

module – the name of the module (required)

category – the category of the property (required)

property – the name of the property to read (required)

evs.set_module(module, category, property, value):

Set a property value in a module within the application.

Keyword Arguments:

module – the name of the module (required)

category – the category of the property (required)

property – the name of the property to set (required)

value – the new value for the property (required)

evs.get_port(module, port, category, property):

Get a value from a port in a module within the application.

Keyword Arguments:

module – the name of the module (required)

port – the name of the port (required)

category – the category of the property (required)

property – the name of the property to read (required)

evs.get_port_extended(module, port, category, property):

Get an extended value from a port in a module within the application.

Keyword Arguments:

module – the name of the module (required)

port – the name of the port (required)

category – the category of the property (required)

property – the name of the property to read (required)

evs.set_port(module, port, category, property, value):

Set a property value in a port in a module within the application.

Keyword Arguments:

module – the name of the module (required)

port – the name of the port (required)

category – the category of the property (required)

property – the name of the property to set (required)

value – the new value for the property (required)

evs.connect(starting_module, starting_port, ending_module, ending_port):

Connect two modules in the application.

Keyword Arguments:

starting_module – the starting module (required)

starting_port – the port on the starting module (required)

ending_module – the ending module (required)

ending_port – the port on the ending module (required)

evs.disconnect(starting_module, starting_port, ending_module, ending_port):

Disconnect two modules in the application.

Keyword Arguments:

starting_module – the starting module (required)

starting_port – the port on the starting module (required)

ending_module – the ending module (required)

ending_port – the port on the ending module (required)

evs.delete_module(module):

Delete a module from the application.

Keyword Arguments:

module – the module to delete (required)

evs.instance_module(module, suggested_name, x, y):

Instances a module in the application.

Keyword Arguments:

module – the module to instance (required)

suggested_name – the suggested name for the module to instance (required)

x – the x coordinate (required)

y – the y coordinate (required)

Result - The name of the instanced module

evs.get_module_position(module):

Gets the position of a module.

Keyword Arguments:

module – the module (required)

Result - A tuple containing the (x,y) coordinate

evs.suspend():

Suspends the execution of the application until a resume is called.

Keyword Arguments: None

evs.resume():

Resumes the execution of the application, causing any suspended operations to run.

Keyword Arguments: None

evs.refresh():

Refreshes the viewer and processes all mouse and keyboard actions in the application. Potentially unsafe operation.

Keyword Arguments: None

Refreshes the viewer and processes all mouse and keyboard actions in the application. At each occurrence of this function, your scripts will catch-up to behave more like manual actions. In most cases this is the only way that you can see the consequences of the commands reflected in your viewer upon this function’s execution.

This is a potentially unsafe operation under certain (hard to predict) circumstances.

If your script is malfunctioning with this command, try removing or commenting all occurrences.

We do not recommend using this command within Python scripts executed by the trigger_script module.

evs.sigfig(number, digits):

Rounds a number to a specific number of significant figures.

Keyword Arguments:

number – the number to round (required)

digits – the number of significant digits (required)

Result - The rounded value

evs.fn(number, digits = 6, include_thousands_separators = True, preserve_trailing_zeros = False):

Formats a number as string using a specific number of significant figures.

Keyword Arguments:

number – the number to round (required)

digits – the number of significant digits (optional, defaults to 6)

include_thousands_separators – whether to include separators for thousands (optional, defaults to True)

preserve_trailing_zeros – whether to preserve trailing zeros when computing significant digits (optional, defaults to False)

Result - The formatted number as a string

evs.is_module_executed():

Returns true if the script is being executed by a module.

Returns false when user executes (ie: hitting play in script window).

Keyword Arguments: None

evs_util.evsdate_to_datetime(d):

Convert a scripting “date” value to a datetime.datetime

Keyword Arguments:

d: the date to convert (required)

Result - The converted date

evs_util.datetime_to_evsdate(d):

Convert a datetime.datetime to a scripting “date” value

Keyword Arguments:

d: the date to convert (required)

Result - The converted date

evs_util.datetime_to_excel(d):

Convert a datetime.datetime into an excel compatible date number

Keyword Arguments:

d: the date to convert (required)

Result - The converted date

evs_util.evsdate_to_excel(d):

Convert a scripting “date” into an excel compatible date number

Keyword Arguments:

d: the date to convert (required)

Result - The converted date

evs_util.excel_to_datetime(d):

Convert form an excel compatible date number into a datetime.datetime

Keyword Arguments:

d: the date to convert (required)

Result - The converted date

evs_util.excel_to_evsdate(d):

Convert form an excel compatible date number into a scripting date value

Keyword Arguments:

d: the date to convert (required)

Result - The converted date

Let’s load an application to get an idea of how EVS works.

Browse to

Find and double click the file “painting-facility-interactive-labels.intermediate.evs”.

The application will run and in less than one minute you will see:

For more on opening applications see the topic Open Files.

Transformations with the Mouse

Now that we have an application loaded, let’s investigate the many ways we can interact with it.

Rotate the model

• Hold down the left mouse button and move the mouse pointer in various directions. The model rotates.
• Vertical motions rotate the model about a horizontal axis.
• Horizontal motions rotate the model about a vertical axis.
• Roll is suppressed so that mouse rotations always keep vertical objects (e.g. telephone poles) vertical.

Scale (zoom) the model

• The wheel on wheel mice also zooms in and out.
• Alternate method:
  • Hold down both the Shift key and the left mouse button (or the middle button alone).
  • Keeping the Shift key and mouse button held down, move the mouse pointer downward or to the left. As we do, the model scales down. Moving the mouse pointer upward or to the right scales up.

Move (Translate or Pan) the model

• Hold down the right mouse button and drag the object up, down, and around, then center the model.

or

Hold down the Shift key and drag the object with the left mouse button (Shift-LMB)

or

Use the middle mouse button or wheel as a button without Shift |

Transformations with the Azimuth and Inclination Controls

Azimuth and Inclination controls are available in two places and gives us more precise ways to transform (scale, pan and rotate) an object:

1. The viewer’s Properties window.
2. The viewer’s slide-out properties in the Viewer window.

Double click on the viewer module to open the Properties window with view controls including sliders and an array of buttons. These controls allows you to instantly select a view from any azimuth and inclination. For a given (positive) inclination, selecting different azimuth buttons is equivalent to flying to different compass points on a circle at a constant elevation. The azimuth buttons are the direction from which you view your objects. (i.e. 180 degrees views the objects from the south). An inclination of 90 degrees corresponds to a view from directly overhead, 0 degrees is a view from the horizontal plane (side view) and -90 degrees is a view from the bottom.

c. Use the Azimuth and Inclination Panel to obtain a specific view by setting the scale slider and inclination slider to desired settings and click once on the desired azimuth button. If you choose a scale of 1.0, an Inclination of 30 degrees and an azimuth of 200 degrees

The viewer will show:

The Advanced options provide the ability to allow rotations about a user defined center, as opposed to the default center of the objects, which is chosen by EVS. Additionally you can apply a ROLL to the view which will make vertical objects (such as the Z axis) not appear vertical. If you do not see the options, click on the Advanced category in the Properties window to expand them.

Below the Advanced options, there are three buttons

1. Set to Top View: Returns the model view to Azimuth 180, Inclination 90 and Scale of 1.0
2. Zoom To Fit: Returns the Scale to 1.0
3. Center On Picked: This button is normally inactive, but is activated by probing with CTRL-Left mouse on any object in the view. The default center of an object shown in our viewer is midway between the min-max of the x, y and z dimensions. This button then causes the view to recenter on the selected point. When you pick a point on an object, the following information is displayed in the Information window.

The Perspective Mode toggle switches to Perspective (vs. Orthographic) viewing. In perspective mode, parallel lines no longer appear parallel but instead would point to a vanishing point.

The Field of View determines the amount of perspective. Larger values result in more perspective distortion.

The Render selection allows you to choose between OpenGL and Software renderers. On some computers with minimal graphics cards Software renderer may perform better or be more stable.

Auto Fit Scene: The choices here include:

• On Significant Change: This is the default behavior which causes the view to recenter and rescale if the extents of the view would change significantly. Otherwise the view is unaffected.
• On Any Change: This causes the view to recenter and rescale if the extents of the view changes at all
• Never: The view will not change if objects change.

The Window Sizing options

• Fit to Window: The view size is determined by the size of the viewer window
• Size Manually: The view size is set in the Viewer Width and Height type-ins below to a specific size. The viewer then has scroll bars if the view size exceeds the window size.

At any time after modules have run, you can quickly obtain basic statistical and model extents data merely by double left mouse clicking on any FIELD (blue) output port.

Let’s demonstrate this by using the second output port of the cut module

When we double-click here, the following information appears in the Properties window.

This quickly tells us that this port has a model with the following data and coordinate extents

• 211,200
• 181,779 cells
• We can select any of the three nodal data (TOTHC is shown)
• The X, Y & Z Minimum, Maximum and Extents are provided

For more comprehensive statistical analysis of the nodal data, click on the “Open Statistics Window” button, and the following appears.

Before we end this first workbook, let’s interact with this application in another way.

In the Application window, double click on the intersection_shell module, and you will see a green border around it. This green border designates the selected module whose properties are available for editing.

This will open its Properties in the Properties window in the upper right. In this application, intersection_shell is performing two tasks. It is cutting the model using information provided by the cut module and it is also subsetting what remains by Total Hydrocarbon (TOTHC) level. It might seem strange at first that the cut module isn’t actually cutting the model. But if it did, it would only provide one side or the other. By giving us data that is the “signed” distance from the specified cutting plane, we are able to use cut’s data to create the cut for the front side giving us the plume and the back side giving us the geologic layers. We can also offset any distance from the theoretical cutting plane without actually moving the cutting plane, but only changing the “cut” Subsetting level. In fact, in this application we’re cutting 100 feet from the specified cutting plane.

Change the TOTHC Subsetting Level to be 2.0 and your view should look like this:

You can continue to experiment and see that you can view any subsetting level in less than a second.

Let’s exit EVS.

Open the Menu using the Show Menu button in the upper right corner. Select Exit at the bottom. Alternatively, exit EVS using the regular close icon at the upper right on the main window.

EVS exits after displaying a confirmation message.

If you close the main window using the X in the upper left, it will prompt you similarly.

You have now completed Workbook 1.

Create a “project” folder with all of your data in one or more subfolders under that folder (any number of levels deep). As long as you don’t put your applications more than 2 levels deep inside of the project folder, everything will be relative, and moving the project folder (as a whole) will always “just work”.

An example would be:

• drive\some\path
  • project
    • applications
    • data
      • data sub 1
      • data sub 2

Alternatively, the most portable EVS Application is one where all of the data is packaged.

2D Estimation: Instance Modules

Now let’s see just how fast we can instance the modules to create a useful application. In the Modules section of the Application network window, type 2

This will show all modules beginning with the number 2. From this filtered list we can instance any of these modules by double-clicking on them. However, we can get the first one, 2d estimation by hitting Enter. Do that.

When you hit enter, it also clears the filter (search) field.

Now type p. Double-click on plume, ~5th in the list.

Since we didn’t hit enter, we need to clear the p and now type e. Double-click on external edges, 7th in the list.

Finally, backspace or clear the e and type l for legend, finding it as the 5th module and double click on it too.

You may need to pan in the application to see our application should be:

We’ll now connect these modules. Connections determine how data flows or is shared among modules, and affects the modules’ order of execution. Use the left mouse button to drag from one port to another to connect them.

We could leave these modules in their current positions, but let’s move them around so they better match how we want the data to flow. Adjust the positions to approximately match:

Then connect a few of them as shown below.

The method of connecting modules is detailed in the topic Connecting and Disconnecting Modules.

We are not connecting all of the modules at this time since we want to examine the simplest 2D kriging applications first and then make it more complex.

Let’s execute the analysis module, 2d estimation, in order to produce a model based on the data file we will select. You will need to have installed the Studio Projects specific to the version of Studio you have installed.

• First, double-left-click on 2d estimation to open its properties so you can see the window below
• Click on the Open button to the right of Filename and browse to Studio Projects/Analytic and Stratigraphic Modeling and choose railyard.apdv
• Then click “Execute”.

2d estimation reads the analyte (e.g. chemistry) data and begins the kriging process. In a very short time, it calculates the estimated concentrations for the grid we selected.

While it runs, 2d estimation prints messages to the Information Window such as percentage completion.

When it is done, the Output Log will show two lines, which when expanded will display:

The viewer will promptly display a top view of the surface we have estimated. Your viewer should look like this:

In the Application window, please change the Z Scale to 10. This will create an artificial topography to our surface where elevations correlate to concentration.

With a simple rotation of our model we now have

With the kriging interpolation results from 2d estimation, the next step is to refine the visualization. This can be accomplished by subsetting the output to display only the regions that fall within a specific value range.

To begin, connect the 2d estimation module to a plume module, and then connect the plume module to the viewer. This directs the data flow through the plume module, which will perform the subsetting operation before rendering the final output.

Initially, the viewer’s output may appear unchanged. This is because the 2d estimation and plume modules are rendering overlapping geometry. To isolate the output from plume, you can toggle the visibility of the 2d estimation module. Click the eye icon on the 2d estimation module in the Application Network to hide its output. This feature is essential for debugging complex applications, allowing you to focus on the output of specific modules.

After hiding the upstream module, the viewer updates to show only the geometry from the plume module. The visualization is now more informative, displaying only the areas of interest where the TOTHC value is above 3.06. This default level was automatically determined from the data entering the plume module as a starting point for you to estimate a suitable value in the data range.

You can easily customize this filtering behavior. To demonstrate, select the plume module by double-clicking it. In the Properties window, set the Subsetting Level to 100.

The viewer immediately reflects these changes. As a result, it now renders only the regions with a TOTHC value above 100, effectively further reducing the areas of high concentration. This feature allows you to interactively explore your data and isolate different phenomena within the dataset.

Begin by selecting the “Generate EVS Input” button in the Main Toolbar, and select AIDV File.

Let’s browse to the folder shown and select the file fuel-storage-gw.xlsx

You’ll need to select the appropriate table in the file. Some may have several, this one has only one named FuelStorage. Once you do, the program will attempt to automatically choose settings for you, but as you can see below, it isn’t perfect.

Since Xylene starts with the letter “X”, it was chosen as the X Coordinate. This is clearly wrong, however, everything else along the left side is correct. By default, the Data Components list will select whatever is left over. Sometimes this is handy, but often, and in this case it is excessive. This excel table includes water table and bottom of model elevations that we will want for a .GEO file, but not for the AIDV file. So we’ll need to make quite a few changes.

It also can’t know the correct units for your analytes nor your coordinate units. It is your responsibility to make sure these are correct or change them.

The last thing you MUST do is determine and choose a Max Gap parameter. This parameter takes some understanding to properly determine. I’ve looked at this excel file in detail and the screen intervals vary from 0.26 to 35.1 meters in length. The Max Gap parameter is the longest length we will allow to be converted into a single point when we convert intervals to points for kriging. I would recommend setting it to 5 for this data file. That means that any interval less than 5 meters will be represented by a single point at the center of the interval. Intervals longer than 5 meters will be represented by two or more points. Choosing a value too small will create oversampling along the Z direction and too large can result in plumes which become disconnected in Z. Fortunately there tends to be a large range of reasonable values. For this dataset, I expect that good results can be obtained with values ranging from 1 to 12.

With all of our settings correct as shown above, all we need to do is click the Generate AIDV File button, and let’s call the file btx.aidv.

Our last two tasks will be to take a look at the file in a text editor and confirm that it works in Earth Volumetric Studio.

Although Windows comes with Notepad, it is really a very poor text editor since it lacks line numbers, column numbers, and the ability to handle large files. There are many freeware text editors, but the one we like is Notepad++.

Begin by selecting the “Generate EVS Input” button in the Main Toolbar, and select APDV File.

Note: this topic builds upon Creating AIDV Files and assumes that you have completed that topic.

Let’s browse to the folder shown and select the file Railyard-soil.xlsx

This file has three sheets and for this example, we’ll choose the second one. This particular sheet has Z coordinates represented as both true Elevation and Depth below ground surface. Both are commonly used and it is not uncommon to see both in a database as a convenience for people working with the data. Our exporter can use either one and there is no technical advantage of one over the other. However, the data file created will retain the Z coordinate option selected.

Since we used True Elevations for AIDV files, let’s work with Depths this time. The correct settings are:

Please note that Top, which is our Ground Surface must be in true elevation since it is the reference surface used to define depths. Depths are always positive numbers with greater depth corresponding to lower elevations.

With all of our settings correct as shown above, all we need to do is click the Generate APDV File button, and let’s call the file railyard-tothc.apdv.

In notepad++ our file looks like:

and if we look at this file in Studio with Z-Scale of 5 it is:

Begin by selecting the “Generate EVS Input” button in the Main Toolbar, and select GEO File.

Let’s browse to the folder shown and select the file fuel-storage-gw.xlsx since we mentioned that this file had three surface which we can use for stratigraphic geology. In this case the three surfaces define just two layer which correspond to the vadose and saturated regions, however, that is an important minimal geology file for working with groundwater data.

If we select the only table, choose the correct settings and scroll to the far right we can see the fields that represent our bottom two surfaces:

Based on the values for both surfaces, it is clear they are Elevations and not Depths. For the Surfaces selectors, we don’t choose Ground because it is already selected as the Top Surface. This file will have three surfaces defining two layers.

With all of our settings correct as shown above, all we need to do is click the Generate AIDV File button, and let’s call the file btx.geo.

Since geo files are rather boring in post_samples, let’s do something a bit more interesting with this data.

Below is our application and its output. We cheated a bit and I want to explain where and why.

We’ve kriged groundwater data into both layers of our model. However it doesn’t make sense to ever display or do any volumetric analysis of groundwater data in the vadose zone. We could have used the subset horizons module to get only the single bottom layer corresponding to the saturated zone (aquifer) but if we did that, we wouldn’t have both stratigraphic layers which we are displaying with the external_edges module and could display with a variety of other techniques. In that case we would need to create a parallel path in our application where we would use horizons to 3d to create either the top layer only or both layers in order to display the geology separate from the groundwater chemistry.

So we cheated and kriged into both layers, but we used the select cell sets module to turn off the upper layer before we display the plume with plume_shell. If we wanted to do volumetrics, we would be sure to only do so for the bottom layer. Other than a few seconds used to krige into the vadose layer we’ve managed to get by with a simpler application.

Begin by selecting the “Generate EVS Input” button in the Main Toolbar, and select PGF File.

We’ll choose lithology-data.xlsx and its only table, DEMO.

When you look at the table, it is clear that we have a Start and End (Top and Bottom), which means that we need to select the “Rows Are Intervals” toggle in the upper left. This toggle allows us to select separate X-Y-Z coordinates for the Start and End to handle non-vertical borings, but if the borings are vertical, both X and Y columns can be the same.

This is another table where we could work in Depths or Elevations. However for a PGF file, the file itself is always in Elevation, so if you choose depth, it just does the conversion before creating the file. We’ll just use the elevation fields directly. However, always make sure you’ve selected the right ones and be consistent.

With all of our settings correct as shown above, all we need to do is click the Generate PGF File button, and let’s call the file litho.pgf.

Below is the file in Notepad++

We can now load this file in post samples, where we can see that this dataset spans a very large set with borings in three distinct groupings. We need a Z-Scale of 50 to be able to see the borings well.

The collection and formatting of data for volumetric modeling is often the most challenging task for novice EVS users. This tutorial covers the instructions for preparing and reviewing all types of data commonly used in Earth Science modeling projects.

The next topics will demonstrate how to visualize these file formats, helping to ensure the quality and consistency of your data.

The following guidelines will simplify your data preparation:

• Use a single consistent coordinate projection (e.g. UTM, State Plane, etc.) for all data files used on a project, ensuring that X, Y and Z coordinate units are the same (e.g. meters or feet).
• For each file, you must know whether your Z coordinates represent Elevation or Depth below ground surface (most EVS data formats will accommodate both)
• Understand the data formats and what they represent. Below is a list of C Tech’s primary ASCII input file formats:
  • Geologic Data
    • PGF: A PGF file can be considered a group of file sections where each section represents the lithology for individual borings (wells). Typical borings logs can be easily converted to PGF format, and many boring log software programs export C Tech’s PGF format directly.
    • GEO: This file format represents a series of stratigraphic horizons which define geologic layers. GEO files are limited to data collected from vertical borings and require interpretation to handle pinched layers and dipping strata. The create stratigraphic hierarchy module may be used to create GEO files from PGF files, though they can be created in other ways.
    • GMF: This file format represents a series of stratigraphic horizons which define geologic layers. GMF files are not limited to vertical borings as GEO files are. Each horizon can have any number of X-Y-Z coordinates, however interpretation is still required to handle pinched layers and dipping strata. The create stratigraphic hierarchy module may be used to create GMF files from PGF files.
  • Analytical Data
    • Analytical Data files can be used for many types of data and industries including:
      • Chemical or assay measurements
      • Geophysical data (density, porosity, conductivity, gravity, temperature, seismic, resistance, etc.)
      • Oceanographic & Atmospheric data (conductivity, temperature, salinity, plankton density, etc.)
      • Time domain data representing any of the above analytes
    • APDV: The Analytical Point Data Values (.apdv) format should be used for all analytical data which is (effectively) measured at a point. Even data which is measured over small consistent (less than 1-2% of vertical model extent) intervals should normally be represented as being measured at a single point (X-Y-Z coordinate) at the midpoint of the interval. Time domain data for a single analyte should use this format.
    • AIDV: The Analytical Interval Data Values (.aidv) format should be used for all analytical data which is measured over a range of elevations (depths). Data which is measured over variable intervals, usually exceeding 2% of vertical model extent should use this format. Time domain data for a single analyte should use this format.
• The C Tech Data Exporter will export the above formats for data in Excel files and Microsoft Access databases. In all cases, the data source must contain sufficient information to create the desired output.

It is important to view your data prior to using it to build a model. There are many common file errors that can be quickly detected by viewing your raw data files, including:

• Transposing X & Y (Easting and Northing) coordinates
• Using Depth or Elevations incorrectly
• Consistency of geologic and analytical data

Let’s begin by creating a very simple application. In the Modules pane in the Application window, type p in the Search for Module section.

Notice that as soon as you type p, only those modules which start with this letter are displayed. The one we want in the first one listed, “post samples”.

We now want to copy the post_samples module into our Application window. We do this using the mouse. Left-click on “post samples” in the Modules window and hold the mouse down. Drag post samples to the Application Network window and place it above the viewer as shown below.

Note that post samples has a red border along the bottom. This tells us that the module has not yet run. This visual indication is very useful, especially with complex applications.

The next step is to connect post samples and the viewer. You can see that the only port color they have in common is red. Left-click in the red output port of post samples:

Then, while holding down the left-mouse, drag a short distance from the port, but near the thin-red connection, until the connection becomes bolder.

At this point, release the left mouse button and the connection is made. The reason for the thin and bolder lines is that there are often multiple modules that can be connected. All will be shown thin, but only the connection which is closest to the cursor will be bold.

Deleting a connection

If we make an incorrect connection, we can delete the connection. To delete the connection, merely click on it to highlight it and then press the Delete key on your keyboard.

With the simple application from the previous topic, let’s read a PGF file and see that data represented in the viewer.

Double-left-click on post samples in the Application Network window to make its settings editable in the Properties window.

post samples will automatically adjust many of its settings based on the type of file read. Click on the Open button and browse to the Lithologic Geologic Modeling folder in Studio Projects and select dipping_strata_lens.pgf.

post samples will automatically run and your viewer should show a top view of:

By default, we are seeing a top view of the borings represented in the PGF file. Using the left mouse button, rotate the view so you can see the 3D borings which are colored by lithology (geologic material).

The image above demonstrates the default display of PGF (pregeology) files. The lithology intervals are colored by material and spheres are located at the beginning and end of each interval.

The colors represent material and range from purple (low) to orange-brown (high). Since this is geology, let’s add a legend to make it clear what materials correspond to our colors.

Type “l” in the Modules pane in the Application window and it will display

Copy legend to the Application (left-click and drag) and make the new connections as shown below

You can move the modules around so that your application and the associated connections between modules is as clear as possible. However, the arrangement (placement) of the modules does not affect how the application behaves. With legend our view becomes:

In the next topic, Viewing GEO Files, we’ll adjust colors

To view a GEO file, the process is nearly identical as with PGF.

Replace post_samples with a fresh instance of the module because when we read different file types, there are many settings in post samples which can change:

Click on the Open button and browse to the Lithologic Geologic Modeling folder in Studio Projects and select railyard_pgf.geo.

Your viewer (after rotating) should show:

Your first question might be, why are the borings so short?

Welcome to the real world. In the last topic we were dealing with a site where the z-extent was comparable to the x & y extents. But for this site, the z extent is 5-10% of the x-y extent. In order to better see the Stratigraphy represented by our .GEO file, we need to apply some vertical exaggeration, which we also refer to as Z-Scale.

We find the Z-Scale parameter in one of 2 places. Either at the top of the Application window:

or in the Application Properties. To get to the Application Properties, double click on any blank space (not on a module or connection) in the Application.

Notice if we change it here, to be 5, it changes on the Home tab and in every module which has a Z-Scale. Our viewer now shows:

Please note: We could have changed the Z-Scale in post samples, but by doing so, we would have broken its link to the Global Z-Scale on the Home tab and Application Properties. In general you want all modules to share the Global Z-Scale, but there are times when you want control on a module-by-module basis. That is why we allow both.

GMF files are different than most other C Tech file formats in that the data is specifically NOT associated with borings. GMF files can be viewed using post samples, but file statistics can often be more useful, especially when dealing with large datasets.

Let’s build a new application:

file statistics (and post samples) will only display a single surface of a GMF file at one time. The advantage of file statistics is that it will provide the extents and basic statistics information. The Data Component parameter determines which surface is displayed. 0 (zero) is the first surface.

file statistics outputs points which are colored by elevation (for GMF files).

Double click on file statistics and select the file Reference\bottom.gmf. In the Application window at the top or the Application Properties, make sure the Z-Scale is set to 5.0.

The viewer should show:

In the view above, each point is displayed as a single pixel point. You can increase the size to be a square of 2x2 pixels or larger using the Point Width parameter.

When file statistics runs, it provides the following information to the Information window.

Note that Number of Bins was set to 10, and Detailed Statistics was turned on.

APDV files represent analyte data which is measured at points. The data can be collected at scattered locations or along borings. When boring IDs are included in the file, post samples will draw the borings as well as the samples.

Create the following application. It is nearly identical to the application used for PGF files, but we do not need to connect the yellow port which contains geology or lithology names, as those are not applicable to APDV (or AIDV) files. However, if you do connect it, it won’t hurt anything.

Double click on post samples to open its Properties window. Select Analytic and Stratigraphic Modeling\railyard.apdv and change the Z Scale to 5 on the Application window or Application Properties.

to show the following in the viewer.

post samples has many options for displaying this type of data (also applicable to PGF, GEO, AIDV). These include (but are not limited to):

• displaying the data as colored tubes (with or without spheres/glyphs)
• using different glyphs to represent each sample (a sphere is the default glyph)
• changing the diameter of glyphs or tubes based on the data magnitudes
• labeling the samples and/or borings

Let’s see the four options above:

It is easy to display colored tubes. You can scroll down to the Color Tubesoption in the “Properties” cagtegory.

Check the Color Tubes option:

To change glyphs is incredibly simple. We just go to the Glyph Settings, and we’ll change the Generated Glyph to be Cube instead of the default Sphere, and we’ll also set the Maximum Scale Factor to be 200%

Since we’ve still left colored tubes on, our viewer shows:

Before we make any other changes let’s uncheck the Color Tubes option again which will change our view to be:

Finally, we’ll add labels at each sample and the top of the borings:

When working with dense datasets, sample labels can become cluttered and difficult to read. The post samples module includes label subsetting features to resolve this by intelligently blanking labels to improve clarity. This functionality is controlled by the Label Subsetting option in the Label Settings category.

For example, if you set the Z Scale in the Application Properties to 1.0 and zoom in on a boring with dense data, such as CBS-6, you will see the problem of overlapping and unreadable labels:

To resolve this, locate the Label Subsetting option and set it to Blank Labels.

By default, Label Subsetting is set to None. Changing it to Blank Labels enables collision detection, which hides lower-priority labels that overlap with higher-priority ones. Label priority is determined by the sample’s value, with higher values taking precedence. Well labels, if enabled, are always given the highest priority. The result is a much cleaner and more informative visualization.

Before: No Blanking	After: Blanking Enabled

You can further refine the display using the following settings:

• Blanking Factor: This setting controls the size of the buffer around each label used for collision detection. Increasing this value creates more space around labels, potentially blanking more of them.
• Boring Min/Max: This mode displays only one sample label per boring, either the one with the highest or lowest value. The Favor Min Value toggle determines which is shown.

AIDV files represent analyte data which is measured over an interval. The data is inherently collected along borings. Boring IDs are required in the file, and post samples will draw the borings as well as the sample intervals.

Create the following application. It is identical to the application used for APDV files.

Let’s read the file in Studio Projects: Analytical (Contaminant) Modeling\fuel-storage-deep-benz.aidv

By default, post samples will display AIDV files as intervals of colored tubes representing the top and bottom of each sample screen.

This dataset spans 779 feet in Z. One of our default settings is “Color Separation which colors the borings light-and-dark grey alternating every 10 units (feet) in depth. We want to change that parameter to be 100 feet for this data.

Packaging a single file is very simple, but is seldom necessary since you will generally use the option to package all of the files in your application.

In every module with a file browser, you merely click on the drop-down button shown next to any filename property, and a Package button will appear.

To view your Packaged Files, click on Packaged Files button in the Main Toolbar:

Which will open the Packaged Files window, if not open already.

When a module is reading a packaged file, the file appears in the browser as light-blue text with no apparent path. However, if you hover over the file, you will see the path as:

package://fuel-storage-deep-benz.aidv

Once one or all files are packaged in a .EVS application, when you save the application, the data files will be saved “in” the .EVS file.

See more in the Packaged Files topic.

To Package all files in an Application, open the Packaged Files window and merely press the Package All Files in an Application button.

For the application railyard-looped-cut.intermediate.evs, the list of packaged files are:

Once one or all files are packaged in a .EVS application, when you save the application, the data files will be saved “in” the .EVS file.

Note: The EVS modules requiring special treatment will be properly and automatically handled when using the Package All Files in an Application button.

Using a file that has been added to an application’s packaged data is easy, but is a bit different. The process involves selecting the file in the Packaged Files window with the left mouse and dragging and dropping it onto the file browser of the module where you wish to use it.

Below, we drop the railyard.apdv file from the Packaged Files onto the file browser of post samples #1

When we drop (release) the file it appears in the browser as light-blue text

Several EVS modules require special treatment in order to package their data. We summarize the main reasons why this is required for each module, but we will explain some of the reasons and advantages of the post-treatment application.

The affected modules are:

1. import vector_gis
2. overlay_aerial
3. import wavefront obj

In general, these modules read file formats which are often not single file formats. The conversion during packaging converts the usable data to a single, packaged file in a format usable by EVS. In addition, steps are often taken to pick a format which will allow for smaller file sizes.

• import vector gis

  The packaging process converts these files to binary EVS Field Files (.efb files) and requires replacing the original modules with a new read evs fiel

• overlay aerial

  The special treatment for overlay aerial is quite different. Packaging is problematic when a module reads a file, but that process results in reading

Inherent in the kriging process is the determination of the expected error or Standard Deviation at each estimated point. As we approach the location of our samples, the standard deviation will approach zero (0.0) since there should be no error or deviation at the measured locations.

The units of standard deviation are the same as the units of your estimated analyte.

The figure below shows why one standard deviation corresponds to 68% of the occurences, whereas three sigma (standard deviations) covers 99.7%

At a particular node in our grid, if we predict a concentration of 50 mg/kg and have a standard deviation of 7 mg/kg , then we can say that we have a ~68% confidence that the actual value will fall between 43 and 57 mg/kg.

The computation of the expected Minimum and Maximum estimates for a given Confidence level is what our Min/Max Estimate provides.

The Confidence values are the answer to a question, and the wording of the question depends on whether you are Log Processing your data or not.

• For the “Log Processing” case the question is: What is the “Confidence” that the predicted value will fall within a factor of “Statistical Confidence Factor” of the actual value?
• For the “Linear Processing” case, the question is: What is the “Confidence” that the predicted value will fall within a +/- tolerance “Statistical Confidence Tolerance” of the actual value?

So if your “Statistical Confidence Factor” is 2.0 as shown for a Log Processing case above, the question is:

What is the “Confidence” that the predicted value will fall within a factor of 2.0 of the actual value?

The confidence is affected by your variogram and the quality of fit, but also by the range of data values and the local trends in the data where the Confidence estimate is being determined.

If your data spans several orders of magnitude, the confidences will be lower and if your data range is small the confidences will be higher depending also on the settings you use.

If the “Statistical Confidence Factor” were set to 10.0, because we are working on a log10 scale, EVS would take the log10 of the Statistical Confidence Factor (the value was 10, so the log is 1.0). It then compares the log concentration values and a corresponding standard deviation that was calculated for every node in our domain. For log concentrations, one unit is a factor of ten, therefore we are asking what is the probability that we will be within one unit. Above, where the Statistical Confidence Factor is 2.0, the questions would have been: What is the confidence that the predicted concentration will be within a factor of 2 of the actual concentration?

The actual calculation to determine confidence requires the standard deviation of the estimate at a node, and the Statistical Confidence Factor. The figure below shows the confidence (as the shaded area under the “bell” curve) for a Statistical Confidence Factor of 10 at a node where the predicted concentration was 10 ppm (1.0 as a log10 value) and the standard deviation for this point was 1.1 (in log10 units). For this example, the confidence would be ~64%, which means that 64% of the time, the value would lie in the shaded region.

For example, consider the case where we are estimating soil porosity, and the input data values are ranging from 0.12 to 0.29. We would want to use “Linear Processing”, and since our values fall within a tight range of numbers we might want to use a “Statistical Confidence Tolerance” that was 0.01. The confidence values we would compute would then be based upon the following question:

What is the “Confidence” that the predicted porosity value will be within 0.01 of the actual value?

If we were careless and used a “Statistical Confidence Tolerance” of 1.0 all of our confidences would be 100% since it would be impossible to predict any value that would be off by 1.0.

However, if we used a “Statistical Confidence Tolerance” of 0.0001, it is likely that our confidence values would drop off very quickly as we move away from the locations where measurements were taken.

At first glance, confidence seems to be a reasonable measure of site assessment quality. If the confidence is high (and we are asking the right question), we can be assured of the reasonableness of the predicted values. You might be tempted to collect samples everywhere that the confidence was low, and if you did, your site would be well characterized.

But, there is a better, more cost-effective way. Instead of focusing on every place where confidence was low, we could focus on only those locations where there was low confidence and where the predicted concentration was reasonably high. We make that easy by providing the Uncertainty.

In EVS, uncertainty is high where concentrations are predicted to be relatively high (above the Clip Min), but the confidence in that prediction is low. If the goal is to find the contamination, using uncertainty allows for more rapid, cost effective site assessment. Uncertainty is the core of our DrillGuideTM technology which performs successive analyses using the location of Maximum Uncertainty to select new locations for sampling on each analysis iteration.

NOTICE: Uncertainty values should be considered unitless and their magnitudes cannot directly be used to assess the quality of a site assessment. Please observe the following precautions:

• Use Uncertainty as it was intended, as a guide to locations needing additional characterization.
• Do not use Uncertainty values directly to assess the quality of a site assessment
• A 50% reduction in Uncertainty magnitude cannot be construed as a 50% improvement in site assessment.

Our training videos cover the use of DrillGuide and how to properly use and interpret Uncertainty.

Both krig_2d and 3d estimation include the ability to compute the Minimum and Maximum Estimate, which is computed using the nominal estimates and standard deviations at every grid node based upon the user input Min-Max Plume Confidence.

The issue with our MIN or MAX plumes is that they represent the statistical Min or Max at every point in the grid. It is quite unrealistic to believe that you could possibly have a case where you’d find the actual concentration would trend towards either the Min or Max at all locations.

C Tech’s Fast Geostatistical Realizations^^®^ (FGR^^®^) creates more plausible cases (realizations) which allow the Nominal concentrations to deviate from the peak of the bell curve (equal probability of being an under-prediction as an over-prediction) by the same user defined Confidence. However, FGR^^®^ allows the deviations to be both positive (max) and negative (min), and to fluctuate in a more realistic randomized manner.

For the case of Max Plume and 80% confidence, at each node, a maximum value is determined such that 80% of the time, the actual values will fall below the maximum value (for that nominal concentration and standard deviation). This process is shown below pictorially for the case of a nominal value of 10 ppm with a standard deviation of 1.1 (log units). For this case, the maximum value at that node would be ~84 ppm. This process is repeated for every node (tens or hundreds of thousands) in the model.

Note that for this plot, the entire left portion of the bell curve is shaded. If we were assessing the minimum value, it would be the right side. Statistically, we are asking a different type of question than when we calculate confidence for our nominal concentrations.

If this Confidence value were set to ~81% then we would be adding one standard deviation to the nominal estimate to create the Max and subtracting one standard deviation to create the Min. The higher you set the Min-Max Plume Confidence the greater the multiplier for standard deviations which are added/subtracted to create the Max/Min.

Even though Min & Max Estimates may not be realistic “realizations” of a likely site state, they still provide the best technique to determine when your site is adequately characterized. Some sites may have very complex contaminant distributions and high gradients while others may be very simple. Applying a single standard for sampling based on fixed spacing will never be optimal.

It is up to the regulators and property owners to determine the ultimate criteria, but generally having the ability to assess the variation in the expected plume volume and the corresponding variation in analyte mass within, provides the best metric for assessing when a site has been sufficiently characterized.

As defined above, our discussion of environmental data will be limited to data that includes spatial information. When spatial data is collected with a GPS (Global Positioning Satellite) system, the spatial information is often represented in latitude and longitude (Lat-Lon). Generally, before this data is visualized or combined with other data, it is converted to a Cartesian coordinate system. The process of converting from Lat-Lon to other coordinate systems is called projection. Many different projections and coordinate systems can be used. The single most important thing is maintaining consistency. Projecting this data is especially necessary for three-dimensional visualization because we want to maintain consistent units for x, y, and z coordinates. Latitude and longitude angle units (degrees, minutes and seconds) do not represent equal lengths and there is no equivalent unit for depth. Projections convert the angles into consistent units of feet or meters.

analyte (e.g. chemistry)

analyte (e.g. chemistry) data files must contain the spatial information (x, y, and optional z coordinates) as well as the measured analytical data. The file should specify the name of the analyte and should include information about the detection limits of the measured parameter. The detection limit is necessary because samples where the analyte was not detected are often reported as zero or “nd”. It is generally not adequate (especially when logarithmically processing this data) to merely use a value of 0.0.

If we want to be able to create a graphical representation of the borings or wells from which the samples were taken, the analyte (e.g. chemistry) data file should also include the boring or well name associated with each sample and the ground surface elevation at the location of that boring.

The chapter on analyte (e.g. chemistry) Data Files includes an in-depth look at the format used by C Tech Development Corporation’s Environmental Visualization System (EVS).

Geology

Geologic information is considerably more difficult to represent in a single, unified data format because of its nature and complexity. Geologic data files can be grouped into one of two classes, those representing interpreted geology and those representing boring logs. By some definitions, boring logs are interpreted since a geologist was required to assign materials based on core samples or some other quantitative measurements. However, for this discussion interpreted geology data will be defined as data organized into a geologic hierarchy.

C Tech’s software utilizes one of two different ASCII file formats for interpreted geologic information. These two file formats both describe points on each geologic surface (ground surface and bottom of each geologic layer), based on the assumption of a geologic hierarchy. Simply stated, geologic hierarchy requires that all geologic layers throughout the domain be ordered from top to bottom and that a consistent hierarchy be used for all borings. At first, it may not seem possible for a uniform layer hierarchy to be applicable for all borings. Layers often pinch out or exist only as localized lenses. Also layers may be continuous in one portion of the domain, but are split by another layer in other portions of the domain. However, all of these scenarios and many others can be usually be modeled using a hierarchical approach.

The easiest way to describe geologic hierarchy is with an example. Consider the example above of a clay lens in sand with gravel below.

Imagine borings on the left and right sides of the domain and one in the center. Those outside the center would not detect the clay lens. On the sides, it appears that there are only two layers in the hierarchy, but in the middle there are three materials and four layers.

EVS’s & MVS’s hierarchical geologic modeling approach accommodates the clay lens by treating every layer as a sedimentary layer. Because we can accommodate “pinching out” layers (making the thickness of layers ZERO) we are able to produce most geologic structures with this approach. Geologic layer hierarchy requires that we treat this domain as 4 geologic layers. These layers would be Upper Sand (0), Clay (1), Lower Sand (2) and Gravel (3).

If desired, both Upper and Lower Sand can have identical colors or hatching patterns in the final output.

Figure 0.1 Geologic Hierarchy of Clay Lens in Sand

When this geologic model is visualized in 3D, both Upper and Lower Sand can have identical colors or hatching patterns. Since the layers will fit together seamlessly, dividing a layer will not change the overall appearance (except when layers are exploded).

For sites that can be described using the above method, it is generally the best approach for building a 3D geologic model. Each layer has smooth boundaries and the layers (by nature of hierarchy) can be exploded apart to reveal the individual layer surface features. An example of a much more complex site is shown below in Figure 1.3. Sedimentary layers and lenses are modeled within the confines of a geologic hierarchy.

Figure 0.2 Complex Geologic Hierarchy

The hierarchical borehole based geology file format used for Figure 1.3 is described in the chapter on Borehole Geology Files.

With C Tech’s EVS software, there are two other geology file formats. One of them is a more generic format for interpreted (hierarchical) geologic information. With that format; x, y, and z coordinates are given for each surface in the model. There is no requirement for the points on each surface to have coincident x-y coordinates or for each surface to be defined with the same number of points. The borehole geology file format described above could always be represented with this more generic file format.

The last file format is used to represent the materials observed in each boring. Borings are not required to be vertical, nor is there any requirement on the operator to determine a geologic hierarchy. C Tech refers to this file format as Pregeology referring to the fact that it is used to represent raw 3D boring logs. This format is also considered to be “uninterpreted”. This is not meant to imply that no form of geologic evaluation or interpretation has occurred. On the contrary, it is required that someone categorizes the materials on the site and in each boring.

In C Tech’s EVS software, the raw boring data can be used to create complex geologic models directly using a process called Geologic Indicator Kriging (GIK). The GIK process begins by creating a high-resolution grid constrained by ground surface and a constant elevation floor or some other meaningful geologic surface such as rockhead. For each cell in the grid, the most probable geologic material is chosen using the surrounding nearby borings. Cells of common material are grouped together to provide visibility and rendering control over each material.

The pregeology file format is discussed in this chapter.

Many methods of environmental data visualization require mapping (interpolation and/or extrapolation) of sparse measured data onto some type of grid. Whenever this is done, the visualization includes assumptions and uncertainties introduced by both the gridding and interpolation processes. For these reasons, it is crucial to incorporate direct visualization of the data as a part of the entire process. It becomes the operator’s responsibility to ensure that the gridding and interpolation methods accurately represent the underlying data.

A common means for directly visualizing environmental data is to use glyphs. A “glyph” refers to a graphical object that is used as a symbol to represent an object or some measured data. For the purposes of this paper, glyphs will be positioned properly in space and may be colored and/or sized according to some data value. For a graphics display, the simplest of all glyphs would be a single pixel. A pixel is a dot that is drawn on the computer screen or rendered to a raster image. The issue of pixel size often creates confusion. Pixels (by definition) do not have a specific size. Their apparent size depends on the display (or printer) characteristics. On a computer screen, the displayed size of a pixel can be determined by dividing the screen width in inches or millimeters by the screen resolution in pixels. For example, a 19" computer monitor has a screen width of about 14.5 inches. If the “Desktop Area” is set to 1280 by 1024, the width of a pixel would be approximately 0.011 inches (~0.29 mm). If the “Desktop Area” were reduced, the apparent size of a pixel would increase.

There are virtually no limits to the type of glyph objects that may be used. Glyphs can be simple geometric objects (e.g. triangles, spheres, and cubes) or they can be representations of real-world objects like people, trees or animals.

Glyphs in 3D

It is once we move to the three-dimensional world that glyphs become much more interesting. In Figure 1.5, cubes (hexahedron elements) are positioned, sized and colored to represent chemical measurements made in soil at a railroad yard in Sacramento, California. Axes were added to provide coordinate references and this picture was rendered with perspective effects turned on. This results in a visualization where parallel lines do not remain parallel and objects in the foreground appear larger than those in the background.

Figure 0.4 Three-Dimensional Cubic Glyphs

When representations of the borings are added, the figure becomes much more useful. Figure 1.6 shows the sample represented by colored spheres and tubes represent the borings. The tubes are colored alternating dark and light gray where the color changes on ten-foot intervals. This provides a reference to allow the viewer to quickly determine the approximate depth of the samples. The borings are also labeled with their designation. These last two figures both represent the same data, however it is clear which one provides the most useful information.

Figure 0.5 Three-Dimensional Glyphs with Boring Tubes

Glyphs can also be used to represent vector data. The most commonly encountered vector data represents ground water flow velocity. In this case, the glyph is not only colored and sized according to the magnitude of the velocity vector, but the glyph can also be oriented to point in the vector’s direction. For this type of application, an assymetric glyph (as opposed to a sphere or cube) is used. Figure 1.7 uses a glyph that is referred to as “jet”. It is an elongated tetrahedron that points in the direction of the vector. The data represented in this figure is predicted velocities output.

Figure 0.6 Three-Dimensional Glyphs Representing Vector Data

Although there is great value in directly visualizing measured data; it does have many limitations. Without mapping sparse measured data to a grid, computation of contaminant areas or volumes is not possible. Further, the techniques available for visualizing the data are very limited. For these reasons and more, significant attention should be paid to the process of creating a grid into which the data will be interpolated and extrapolated.

For this paper, a grid is defined as a collection of nodes and cells. Nodes are points in two or three-dimensions with coordinates and usually one or more data values. The word “cell” and “element” are both used as a generic term to refer to geometric objects. The cell type and the nodes that comprise their vertices define these objects. Commonly used cell types are described in Table 1.1 and Figure 1.2.

Table 1.1 Common Cell Types

Dimensionality refers to the space occupied by the cell. Points have do not have length, width, or height, therefore their dimensionality is zero (0). Lines are dimensionality “1” because they have length. Dimensionality 2 objects such as quadrilaterals (quad) and triangles have area and dimensionality 3 objects ranging from tetrahedrons (tet) to hexahedrons (hex) are volumetric. When creating a two-dimensional grid, areal cells are used and for three-dimensional grids, volumetric cells are used.

Figure 1.2 Common Cell Types

Rectilinear (a.k.a. uniform) grids are among the simplest type of grid. The grid axes are parallel to the coordinate axes and the cells are always rectangular in cross-section. The positions of all the nodes can be computed knowing only the coordinate extents of the grid (minimum and maximum x, y and optionally z). Two-dimensional rectilinear grids are comprised of quadrilateral cells. For a 2D grid with i nodes in the x direction and j nodes in the y direction, there will be a total of (i - 1)*(j - 1) cells.

The connectivity of the cells (the nodes that define each cell) can be implicitly determined because the nodes and cells are numbered in an orderly fashion. The advantages of rectilinear grids include the ease of creating them and the uniformity of cell area in 2D and cell volume in 3D. The disadvantages are that grid nodes are generally not coincident with the sample data locations and large areas of the grid may fall outside of the bounds of the data. A simple two-dimensional rectilinear grid is shown in Figure 1.9.

Figure 0.8 Two-Dimensional Rectilinear Grid

Three-dimensional rectilinear grids offer the simplest method for gridding a volume. They are constrained to rectangular parallel piped volumes and have hexahedral cells of constant size. (See Figure 1.10) For some processes and visualization techniques such as volume rendering, this is advantageous and may even be required. For a grid having i by j by k nodes there will be (i-1) * (j-1) * (k-1) hexahedron cells whose connectivity can be implicitly derived.

Figure 0.9 Three-Dimensional Rectilinear Grid

Finite Difference

The following type of grid derives its name from the numerical methods that it employs. Simulation software such as the USGS’s MODFLOW utilizes a finite difference numerical method to solve equilibrium and transient ground water flow problems. This solution method requires a grid that contains only rectangular cells. However the cells need not be uniform in size. For two-dimensional grids, this results in rectangular cells, however it is possible that no two cells are precisely the same size. Some simulation software requires that finite difference grids be aligned with the coordinate axes. EVS does not impose this restriction, but it does provide a means to export the grid transformed so that the grid axes are aligned. Figure 1.11 shows a rotated 2D finite difference grid. Smaller cells are concentrated in areas of the model where there are significant gradients in the data. For groundwater simulations this is usually where wells are located. For environmental contamination it should be the location of spills or areas where DNAPL (dense non-aqueous phase liquids) contaminant plumes were detected. The smaller cells provide greater accuracy in estimating the parameter(s) of interest.

Figure 0.10 Two-Dimensional Rotated Finite Difference Grid

Three-dimensional finite difference grids have the same restrictions as 2D grids with respect to their x and y coordinates (cell width and length). However, the z coordinates of the grid (which define the cell thicknesses) are allowed to vary arbitrarily. This allows for creation of a grid that follows the contours of geologic surfaces. For a grid having i by j by k nodes there will be (i-1) * (j-1) * (k-1) hexahedron cells whose connectivity can be implicitly derived. However the coordinates of the nodes for this grid must be explicitly specified. Figure 1.12 shows the grid created to model the migration of a contaminant plume in a tidal basin.

Figure 0.11 Three-Dimensional Finite Difference Grid

The convex hull of a set of points in two-dimensional space is the smallest convex area containing the set. In the x-y plane, the convex hull can be visualized as the shape assumed by a rubber band that has been stretched around the set and released to conform as closely as possible to it. The area defined by the convex hull offers significant advantages. Within the convex hull all parameter estimates are interpolations. The convex hull best fits the spatial extent of the data. Remember that the convex hull defines an area. That area can be gridded in many ways. EVS grids convex hull regions with quadrilaterals. Smoothing techniques are used to create a grid that has reasonably equal area cells. A two-dimensional example of a convex hull grid is shown in Figure 1.13. In this example, the domain of the model was offset by a constant amount from the theoretical convex hull. This results in rounded corners and a model region that is larger than the convex hull.

Figure 0.12 Convex Hull Grid with Offset

Adaptive Gridding

Adaptive gridding is the localized refinement of a grid to provide higher resolution in the areas or volumes surrounding measured sample data. Adaptive gridding or grid refinement can be accomplished in many different ways. In EVS, rectilinear, finite difference and convex hull grids can all be refined using a similar method. In two-dimensions a new node is placed precisely at the measured sample data location. Three additional nodes are placed to create a small quadrilateral cell within the cell to be refined. The corners of the small cell are connected to the corresponding corners of the cell being refined creating a total of five cells where the one previously was. The resulting nodal locations and grid connectivity must be explicitly defined.

Adaptively gridding offers many advantages. It assures that there will always be nodes at the precise coordinates of the sample data. This insures that the data minimum and maximum in the gridded model will match the sample data. It also provides greater fidelity in defining data trends in regions with high gradients. Figure 1.14 shows a two-dimensional adaptively gridded convex hull model. This model’s area was also offset from the convex hull. Since each sample data point results in a refined region, and the sample points define the convex hull, the regions in each corner of the model contain adaptively gridded cells.

Figure 0.13 Adaptively Gridded Convex Hull Grid

Figure 1.15 is a close-up view of some refined cells near the lower right in Figure 1.14. It shows one of the special cases. If the point to be refined falls very near an existing cell edge, that edge is refined and the cells on either side of the edge are symmetrically refined. Since the edge must be broken into three segments, the cells on both sides must be affected.

Figure 0.14 Close-up of Figure 1.14

The refinement process can also be applied to all types of 3D grids. When a sample falls in a hexahedron (hex) cell, a new much smaller hex cell is created with one of its’ corners located precisely at the coordinates of the sample point. The eight corners of the small cell are connected to the corresponding corners of the parent cell. This creates 7 hex cells that fully occupy the volume of the original cell. Since the 3D-refinement process occurs internal to the volume of the model, it is more difficult to visualize the process. In order to see the refined cells, removing all cells in the grid with any nodes that were below a thresholded concentration level created Figure 1.16. By choosing the threshold properly, several of the refined cells become visible.

Figure 0.15 3D Adaptively Gridded Model

This figure (Figure 1.17) is an enlarged view of the right hand corner. It reveals the structure, relative sizes and connectivity resulting from 3D adaptive gridding.

Figure 0.16 Close-up of Figure 1.16

Triangular networks are defined as grids of triangle or tetrahedron cells where all of the nodes in the grid are exclusively those in the sample data. For these types of grids, the cell connectivity must be explicitly defined. In two dimensions, these grids are referred to as Triangulated Irregular Networks or TINs. The 3D equivalent grids are Tetrahedral Irregular Networks.

Triangulated Irregular Networks – 2D

Delaunay triangulation is one of the most commonly used methods for creating TINs. By definition, 3 points form a Delaunay triangle if and only if the circle defined by them contains no other point. Focusing on creating Delaunay triangles produces triangles with fat (large) angles that have preferred rendering characteristics. The boundary edges on the Delaunay network form the convex hull, which is the smallest area convex polygon to contain all of the vertices.

Figure 0.17 Flat-Shaded Delaunay TIN of Geologic Surface

The TIN surface above (Figure 1.18) has significant variation in the size of the triangles. This is a natural consequence of the grid’s being created using only nodes from the input data file. When such a surface is rendered with data, having very large triangles can result in very objectionable visualization anomalies. These anomalies result from rendering large triangles that have a range of data values that span a significant fraction of the total data range. There are many methods that could be used to assign color to each triangle. These methods are referred to as surface rendering modes.

Two of the most commonly used rendering modes are flat shading and Gouraud shading. Flat shading assigns a single color to the entire triangle. The color is computed based on the average elevation (data value) for that triangle, lighting parameters and orientation to the viewer camera. In the upper left corner we have a large single triangle that spans a significant range of elevations. When it is assigned a color that corresponds to the mean elevation for that triangle, that color will be wrong. More precisely, the color does not fall within the color scale. Note the color of the triangle in the upper right corner of Figure 1.18 and the one below it. The color of these triangles is outside the range of our color scale.

The problem of large triangles is no better when using Gouraud shading. Gouraud shading assigns colors to each node of the triangle based on the data values. This assures that the colors at the nodes (vertices of the triangles) will be correct. Colors are then interpolated over the area of the triangle based on lighting parameters and orientation to the viewer camera. Consider the triangle in the upper right hand corner of Figure 1.19. The upper right node is assigned the color blue (corresponding to a low value) and the upper left node is assigned the color red (corresponding to a high value). The color scale for this problem ranges from blue to cyan to green to yellow to red. However, for this anomalous situation the color that will be interpolated between blue and red along the uppermost edge will be magenta. Magenta is not a color in our range of colors.

Figure 0.18 Gouraud-Shaded Delaunay TIN of Geologic Surface

To overcome the problems caused by large triangles, the triangles can be refined (subdivided) to create a grid that still contains points that honor the original input nodes, but has more uniform cell sizes. In Figure 1.20 (which has a spatial extent of 500 feet in x and 380 feet in y) it was specified that no triangle’s edge may exceed 45 feet in length. We must interpolate the elevation values (or our data values) to these new nodes created as a result of the triangle subdivision. The simplest means of doing this is bilinear interpolation. The refined TIN grid with bilinear interpolation and flat shaded triangles is shown in Figure 1.21. Note that the all of the triangles have appropriate colors. To avoid the large cell coloring problem (this is a problem with all cell types except points), no single cell should have data values at its nodes that span more than about 20 percent of the total data range.

Figure 0.19 Flat-Shaded Subdivided TIN of Geologic Surface

If Gouraud shading is employed instead of flat shading, the resultant surface has a smoother appearance, however the fundamental linear interpolation along cell edges is still evident in the colors. If the maximum triangle size were made much smaller, the flat shaded model would approach the appearance of the Gouraud shaded model. However, without using a different interpolation approach the Gouraud-shaded model would not change dramatically.

Figure 0.20 Gouraud-Shaded Subdivided TIN of Geologic Surface

EVS includes another technique for coloring surfaces. This method, called solid contours, assigns uniform color bands based on the data values. Figure 1.22 demonstrates this method that subdivides cells using bilinear interpolation. Because this method inherently includes triangle subdivision using bilinear interpolation, the figure would be identical whether the input grid was the large triangles from the original TIN surface or the refined smaller triangles. The boundaries of the colored bands are effectively isopachs (isolines) of constant elevation.

Figure 0.21 Solid Contour TIN of Geologic Surface

To complete this discussion and comparison of gridding and interpolation methods, the same data file was used to create a convex hull grid and the elevation data was estimated using EVS’s two-dimensional kriging software. Kriging will be discussed in more detail in section 1.3.3. This technique honors all of the original data points, but creates much smoother distributions between the values. The result shown in Figure 1.23 is a more realistic and aesthetically superior surface. Labeled isolines on 10 foot intervals were added to this figure. Note that these isolines are similar, but much smoother than those in Figure 1.22.

Figure 0.22 Kriged 2D Convex Hull Grid

Tetrahedral Irregular Networks – 3D

Tetrahedral Irregular Networks provide a method to create a volumetric representation of a three-dimensional set of points. As with a TIN, the nodes in the resulting grid are exclusively those in the original measured sample data. Tetrahedral Irregular Networks use tetrahedron cells to fill the three-dimensional convex hull of the data as shown in Figure 1.24. The result often contains cells of widely varying volumes having potentially large data variation across individual cells. For this and other reasons, this approach is not often used.

Figure 0.23 Tetrahedral Irregular Network

Spatial interpolation methods are used to estimate measured data to the nodes in grids that do not coincide with measured points. The spatial interpolation methods differ in their assumptions, methodologies, complexity, and deterministic or stochastic nature.

Inverse Distance Weighted