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