EdX

GIS Image Analysis in ArcGIS Pro (edX)

Offered by University of Alaska Fairbanks, AlaskaX,
GIS Image Analysis in ArcGIS Pro (edX)

Learn fundamentals of remote sensing, image analysis, image processing and its application on real-world problems such as vegetation health, wildfire severity, and flooding. Image analysis is extraction of meaningful information from an image to accomplish a simple task like understanding the landscape or to solve a complex problem like face recognition.

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This course is focused on image analysis and applications in the area of natural resource management, geography, geology, and environmental studies. Participants will use a variety of remotely sensed data including Digital Elevation Model, Landsat and Sentinel satellite data to solve specific problems.
Participants in this course will learn fundamentals of remote sensing, image processing and image analysis. Participants will learn image analysis in ESRI ArcGIS Pro through hands-on exercises including image display, image georeferencing, change detection methods, supervised and unsupervised classification, and accuracy assessment methods.
The course is designed for self-study with lessons covering GIS image analysis applications on real-world problems.
This course is part of the Geographic Information Systems (GIS) Essentials Professional Certificate.

What you'll learn

  • Access open source satellite image and data products for any part of the world
  • Perform image analysis using raster functions in ArcGIS Pro software efficiently
  • Co-register and use historic remotely sensed imagery for change detection applications
  • Use spectral indices to assess vegetation health, burn severity, and flooding
  • Use unsupervised and supervised classification algorithms to create land cover maps
  • Create elegant map figures for communicating image analysis results

Syllabus

Week 1: Introduction to GIS Image analysis

  • What is an image? How do you get an image?
  • Image display and image properties
  • Spectral region
  • Basic image operations and enhancements

Week 2: Spectral Indices

  • Spectral indices introduction
  • NDVI and delta_NDVI (for vegetation health)
  • NBR and delta_NBR (for wildfire severity)
  • NDWI and delta_NDWI (for flooding)

Week 3: Image Classification

  • Image classifiers (supervised vs unsupervised)
  • Land cover mapping in ArcGIS Pro
  • Image classification accuracy assessment

Week 4: Landsat/Sentinel sensor applications

  • Landsat sensor
  • Mapping Arctic greening
  • Mapping Aspen Defoliation
  • Mapping lake area change
Go to Class
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