Complete Remote Sensing Image Analysis with ENVI Software

Open Landsat 8 imagery in ENVI by selecting file, open as, and geo tiff with metadata, then load the text document describing the unpacked zip to display the images.

Explore how to manage Landsat 8 data with the data manager, display spectral bands in color, and use red, green, and blue band displays to reveal features.

Save ENVI files by selecting file save as and choosing formats like ENVI, JPEG, ERDAS Imagine, or TIFF, with options for spectral and spatial subsets and georeferenced with GPS coordinates.

Edit ENVI header to adjust image metadata, set band loading and display, add data ignore value to remove no data areas, and apply a default stretch for clearer Landsat imagery.

Explore the ENVI spectral library to compare mineral and vegetation signatures, import your own spectral signature, create custom folders, and export results as images or PDX for material identification.

Convert digital numbers to top of atmosphere radiance via radiometric calibration, ignore zeros to exclude no data, then apply atmosphere correction in ENVI to obtain bottom of atmosphere reflectance.

Perform flash atmospheric correction on Landsat 8 radiance to obtain surface reflectance from top-of-atmosphere values; apply band math to divide by 10000.

Draw a region of interest (roi) in ENVI by a rectangle to isolate fields. Use subset data to save a focused field image.

Learn to isolate water in an image by spectral thresholding in ENVI, using near infrared reflectance, histograms, and color-coded region of interest that saves for later.

Master ENVI basics through Lab 1, practicing core ENVI tools with downloadable data, zip handling, and guided exercises, plus example questions and solutions for practice.

Create a water mask in ENVI from an atmospherically corrected Landsat 8 image, saving only water pixels with a near-infrared threshold for lake studies like chlorophyll or algae blooms.

Isolate clouds with a threshold in the coastal aerosol band of Landsat 8, preview selection, save as a cloud mask, and apply an inverse mask to reveal land and water.

Apply band ratios in ENVI to create a simple vegetation index (near infrared over red), visualize with raster color slices, and customize color schemes to compare vegetation levels.

Use ENVI's MDVIP to compute NDVI on a Landsat 8 subset, save the VI fields, set red band 4 and near-infrared 5, and display vegetation health with red-to-green colors.

Explore unsupervised classification in ENVI by clustering pixels with iso data or k-means, then compare to supervised classification that uses training data to label water and fields.

Train data guides a supervised classification of a Landsat 8 image in ENVI, defining water and fields classes with multiple training samples.

Convert Landsat 8 thermal data to kelvin surface temperature using radiometric calibration and brightness temperature in ENVI, compare lake and land temperatures, and explore band math to Fahrenheit or Celsius.

Learn to compare before and after tsunami images using the image change workflow, analyze vegetation index differences, apply auto thresholding, and export results as ENVI and shapefile outputs.

Explore thematic change detection in ENVI by comparing the same scene's pre-Katrina and post-Katrina classification images to identify changes and export results as a shape file.

Construct a Landsat time series from 1975 to 2014 to monitor urban expansion and vegetation changes, using calibrated, atmospherically corrected images and an optimized soil adjusted vegetation index.

Explore reprojection, registration, and mosaicking of remote sensing images using ENVI software, with exercises and version-specific instructions for accurate analysis.

Create an attribute image for supervised classification by combining spectral, height, and vegetation attributes into a layer stack in ENVI, then use an enhanced vegetation index to distinguish surface features.

Explore hyperspectral analysis and visualization in ENVI, selecting red, green, and blue bands, compare spectral signatures with a library to identify minerals using continuum removed for clearer discrimination.

Learn to preprocess Avars data and convert it to surface reflectance using flash atmosphere correction, handle scale factors, edit bad bands, and prepare for hyperspectral analysis.

Analyze hyperspectral imagery with ENVI to identify vegetation stress from insect damage, using spectral indices like the moisture stress index and the forest health tool to map stressed areas.

Install MapTiler to load satellite imagery as a scalable base map. Download, install via the desktop wizard, accept the terms, then load satellite images for web applications.

Pan sharpen Landsat 8 to a 15-meter color image using red, green, blue bands from a 30-meter base, then save as a native ENVI file for a high-resolution base map.

Convert the native file to MBTiles format for use with map tiler. Apply a 2 percent linear stretch and set 0–255 scales for a zoomable, tiled output.