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Complete Remote Sensing Image Analysis with ENVI Software

Name: Complete Remote Sensing Image Analysis with ENVI Software
Rating: 4.5 (351 reviews)

Learn basic to advanced remote sensing image processing, spatial analysis, and GIS techniques using ENVI software

Highest Rated

Created byMatt .

Last updated 11/2020

English

English [Auto],

What you'll learn

Use ENVI software for a variety of image processing techniques
Understand basic tools in ENVI
Radiometric Calibration
Multiple Atmospheric Correction Techniques
Classification of Images
Downloading Satellite Data
Import and export images
Vegetation Indices
How to apply band ratios and algorithms to your image
Image Registration
Hyperspectral Data Analysis
GDAL and Basemaps
Mosaic images
Anomaly Detection
Pansharpen Satellite Images

Course content

9 sections • 59 lectures • 6h 55m total length

Downloading Satellite Imagery2:27
Downloading satellite imagery from https://earthexplorer.usgs.gov
Unpacking Satellite Imagery Files2:07
How to unzip satellite imagery files. June 19 2016, June 12 2016, and August 4 2015 data have been uploaded below. This way you can use the same data sets that I will be using throughout the course.

Opening Satellite Imagery in ENVI1:32
Data Manager3:39
Saving ENVI Files3:17
Spatial and Spectral Subset2:25
Layer Manager2:43
Opening Saved ENVI Files2:33
Exporting ENVI Satellite Images to Google Earth2:23
Basic Tools 14:30
Cursor Value, Crosshairs, Select, Pan, Fly, Rotate View, Zoom, Fixed Zoom In, Fixed Zoom Out, Zoom to Full Extent, North Up,
Basic Tools 24:32
Arbitrary Profile, Spectral Profile, Scatter Plot Tool, Region of Interest (ROI) Tool, Feature Counting, "Go To" Box, Brightness, Contrast
Basic Tools 36:56
Stretching, Reset Stretch Type, Sharpen, Transparency, Mensuration, Portal, View Blend, View Flicker, View Swipe, Different Views
Toolbox3:59
Edit ENVI Header3:34
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.
Spectral Library2:10
Statistics6:16
ENVI Help0:49

Radiometric Calibration5:19
Atmospheric Correction 1 (Fast Line-of-Sight Atmospheric Analysis of Hypercubes)16:51
Perform flash atmospheric correction on Landsat 8 radiance to obtain surface reflectance from top-of-atmosphere values; apply band math to divide by 10000.
Atmospheric Correction 2 (Dark Object Subtraction)14:51
Spectral Profile1:38
Crosshair data values, Spectral Profile
Try radiometric calibration and atmospheric correction on your own
Preform Radiometric Calibration and Atmospheric Correction on June 12 2016 Image

Resize Data3:11
Subset Data From ROI (Region of Interest)3:41
Subset Data Based on Spectral Properties: Isolating Water4:05
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.
Lab1: Mastering ENVI Basics2:07
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.
Creating a Mask: An example with water7:07
Creating a Mask: Masking out Clouds Quickly5:31
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.
Band Ratios5:25
Band Math4:50
NDVI4:41
Lab2: Image Display Concepts1:40
Change Detection Difference Map10:37
We will be doing a change detection difference map between a subset of June 19 2016 image and the August 2015 Image. In a previous assignment you should have already preformed radiometric calibration and FLAASH atmospheric corrections on the August 4 2015 Image. Otherwise FLAASH atmospherically corrected August 4 2015 Image is provided below in a zip file.
Change Detection NDVI Map
Seamless Mosaic7:49
We will be preforming a seamless mosaic between the June 19 2016 Landsat 8 Image and the June 12 2016 Landsat 8 Image to create once large image. In a previous assignment you should have radiometrically and atmospherically corrected the June 12 2016 Image. Otherwise the atmospherically corrected June 12 2016 image is attached below in a zip file for downloading.
Unsupervised Classification3:57
Unsupervised Classification: Using Classification Workflow4:31
A second way to preform unsupervised classification of your image
Supervised Classification7:26
Train data guides a supervised classification of a Landsat 8 image in ENVI, defining water and fields classes with multiple training samples.
Pansharpening9:41
Lab3: Classification2:01

Converting Pixel Values to Surface Temperature3:17
Image Change Detection6:31
Image Registration10:31
Anomaly Detection6:55
Thematic Change Detection8:33
Landsat Time Series9:02
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.
Burn Indicies22:53
Mosaic (Advanced Workflow)11:19
Lab 4: Reprojection, Registration, Mosaicking1:16
Explore reprojection, registration, and mosaicking of remote sensing images using ENVI software, with exercises and version-specific instructions for accurate analysis.

Hyperspectral Analysis9:22
Preprocessing AVRIS Data11:47
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.
Hyperspectral Vegetation Indicies21:58
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.
Hyperspectral Analysis: SAM and SFF13:36
Spectral Angle Mapper (SAM) and Spectral Feature Fitting (SFF)

Install MapTiler3:18
Install GDAL (Anaconda)2:32
Create an RGB Pansharpened Satellite Image9:57
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 NITF File to MBTILES Format in GDAL10:59
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.

Requirements

Have a basic knowledge and understanding of remote sensing principles
Have access to ENVI software

Description

Are you currently enrolled in my Fundamentals of Remote Sensing and Geospatial Analysis course and want to take your remote sensing knowledge to the next level?

Are you already familiar with the field of remote sensing and want to learn how to process images?

The next step for you is to gain proficiency in remote sensing data analysis using ENVI software!

Go from zero to hero in remote sensing satellite image processing!

My course provides a complete foundation to carry out practical and real life remote sensing image analysis processes using ENVI software. ENVI is the most widely used remote sensing and image analysis program within Industry and Research. In this course you will be using actual images and data from Landsat 8 and other popular satellites to give you hands on experience in image processing techniques. First we will go over the basic tools in ENVI and learn how to navigate the software. Then we will dive into and learn step by step the fundamental techniques in satellite remote sensing image processing such as:

image mosaicing
radiometric calibration
multiple atmospheric correction techniques (Fast Line of Sight Atmospheric Analysis of Hypercubes and Dark Object Subtraction)
supervised and unsupervised classification
vegetation indies
band ratios
and many more!

Additional satellite images and data will be provided so that you can practice these techniques on your own. I will also provide you with additional resources that you can download and use in your future remote sensing career! We will also go over on how to locate and download FREE remote sensing satellite images!

Once you have learned the basics of ENVI we will go into intermediate and advanced ENVI remote sensing processes such as:

hyperspectral data analysis
image registration
anomaly detection
creating a burn index map
mineral mapping from hyperspectral images
spectral angle mapper
time series analysis
pansharpening and much more!

I hope that you ENROLL NOW and learn the remote sensing software that industry and research positions require! Start your remote sensing career here and learn the basics of remote sensing image analysis using ENVI software!

Who this course is for:

Anyone interested in learning how to process remote sensing satellite imagery in ENVI
Anyone wanting to learn how to use ENVI software

Complete Remote Sensing Image Analysis with ENVI Software

What you'll learn

Explore related topics

Course content

Introduction and Sample Data2 lectures • 5min

Basic ENVI Tools15 lectures • 51min

Atmospheric Corrections4 lectures • 39min

Fundamental ENVI Remote Sensing Processes17 lectures • 1hr 28min

Example Project1 lecture • 20min

Intermediate and Advanced ENVI Processes9 lectures • 1hr 20min

Classification (Intermediate/Advanced)3 lectures • 48min

Hyperspectral Analysis4 lectures • 57min

Making a Satellite Image Basemap for MapTiler4 lectures • 27min

Requirements

Description

Who this course is for: