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AlaskaX: GIS Image Analysis in ArcGIS Pro
Learn fundamentals of remote sensing, image analysis, image processing and its application to real-world problems such as changing water bodies, vegetation health, and wildfire severity.
This Course Includes
edx
4.4 (8 reviews )
4 weeks at 3-5 hours per week
english
Online - Self Paced
course
AlaskaX
About AlaskaX: GIS Image Analysis in ArcGIS Pro
Image analysis is the 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.
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 high resolution aerial photo, Landsat and Terra MODIS satellite data to solve specific problems.
Learners in this course will learn fundamentals of remote sensing, image processing and image analysis. Learn image analysis in Esri ArcGIS Pro through hands-on exercises including image display, image interpretation, change detection using spectral indices, supervised and unsupervised image classification for land cover mapping, and effect of arctic warming on vegetation productivity.
The course features lessons covering GIS image analysis applications on real-world problems.
Verified track learners will receive one-year ArcGIS Pro Desktop (Windows) license with support only for tools used in the course in addition to unlimited course access and a verified certificate.
Sign up for this online course or full GIS Essentials certificate today to expand your skillset in geographic information systems.
What You Will Learn?
- Access open source satellite image and data products for any part of the world.
- Perform image analysis using raster functions and raster geoprocessing tools in ArcGIS Pro software efficiently.
- Use appropriate image bands for feature visualization and image interpretation.
- Use spectral indices to assess vegetation health, wildfire burnscars, and lake change.
- Use unsupervised and supervised classification algorithms to create land cover maps.
- Create publication quality charts using data from an attribute table for communicating image analysis results.