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ENVI® Fundamentals

Geospatial eLearning Program


ENVI Fundamentals provides an introduction to ENVI software. It is designed for those who are new to ENVI or who need a refresher on ENVI’s capabilities. You will learn about the ENVI interface, analytical tools, and task automation.


Sections in This Course



Introduction to ENVI

3 Hours

  • Learning the ENVI interface
  • Exploring ENVI Help
  • Learning about different analytical tools
  • Opening and displaying a multispectral image
  • Using the Layer Manager and Data Manager to manage multiple images and views
  • Using the Cursor Value tool and Status bar to get image and map coordinates
  • Using Pan, Rotate, and Zoom tools
  • Applying contrast stretches and color tables

Exploring Data

2 Hours

  • Viewing and interpreting data values
  • Measuring distances in a georeferenced image
  • Viewing metadata fields and values
  • Calculating basic image statistics and histograms
  • Creating a 2D scatter plot of pixel values
  • Displaying different types of profiles

Preprocessing

2 Hours

  • Creating a quick mosaic from georeferenced images
  • Defining a spatial subset
  • Using the Quick Atmospheric Correction (QUAC) tool

Vegetation Indices

2 Hours

  • Creating broadband greenness indices from a 4-band image
  • Creating specialized, narrowband indices from a 10-band image
  • Creating a Forest Health image using the Vegetation Analysis Workflow

Change Detection

3 Hours

  • Creating Two-Color Multi-View (2CMV) composites showing urban development over a seven-year period
  • Exploring different methods for quantifying changes in urban development
  • Interactively defining change thresholds
  • Using a guided workflow to create a change detection classification image

Time-Series Analysis

2 Hours

  • Understanding how time-series analysis is different than change detection
  • Learning how temporal resolution and satellite revisit times are related
  • Building a time series of co-registered reflectance images
  • Animating a time series of images
  • Plotting a time-series profile of reflectance data
  • Building and plotting a temporal cube of vegetation indices for multiple dates and crop types

Image Classification

3 Hours

  • Using ISODATA and K-Means unsupervised classifiers
  • Using image-derived Regions of Interest (ROIs) to collect training data for supervised classification
  • Previewing and evaluating initial classification results from multiple classifiers
  • Creating a Maximum Likelihood classification image
  • Evaluating classification accuracy using a confusion matrix

Automating ENVI Tasks

3 Hours

  • Learning what constitutes an ENVI Task
  • Learning the basic components of the ENVI Modeler
  • Creating a simple model that combines multiple tasks
  • Revising a model to allow end users to specify their own input and output files
  • Creating a model that iteratively creates ISODATA classification images with different output classes
  • Creating a model that iteratively creates ISODATA classification images from multiple input images
  • Creating a custom classification model that consists of multiple tasks, including Normalized Euclidean Distance (NED) classification
  • Creating a metatask from the custom classification model
  • Publishing the custom classification model to a Toolbox extension so that you can invoke it from the ENVI Toolbox

This Course Includes:

  • Course Length: 20 Hours
  • ENVI Software: 60-day temp license and required modules
  • Learning Checks: Quiz at end of each lesson
  • Certificate: Certificate of Completion at course end

System Requirements

  • Operating System: Windows 10 or 11
  • Disk Space: Approx. 4GB for installation
  • Memory: Minimum 8GB


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