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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.

GIS Image Analysis in ArcGIS Pro

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Comienza el 22 oct
4 semanas estimadas
3–5 horas por semana
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Sobre este curso

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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 an ArcGIS Pro license in addition to unlimited course access and a verified certificate.

De un vistazo

  • Institución: AlaskaX
  • Tema: Análisis de datos
  • Nivel: Intermediate
  • Prerrequisitos:

    GIS1x: Geographic Information System (GIS) Foundations is highly recommended and precedes this course in the edX GIS Professional Certificate.

    Windows OS is required to run ArcGIS Pro software.

Lo que aprenderás

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  • 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

Plan de estudios

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Week 1: Introduction to Remote Sensing and Image Analysis

  • Remote sensing and the evolution of remote sensing
  • Electromagnetic radiation and atmospheric windows
  • Remote sensing processes and types
  • Images and image resolutions
  • Geographic and projected coordinate systems
  • Remote sensing: advantages and challenges

Week 2: Introduction to ArcGIS Pro, Spectral Indices and Image Interpretation

  • Introduction to ArcGIS Pro, Geoprocessing tools, and ArcGIS best practices
  • Fundamentals of image interpretation and feature visualization
  • Spectral indices and their applications:
  • NDVI (for vegetation health)
  • Band ratio (for cloud mask)
  • NBR (for mapping wildfire burn scars)
  • NDWI (for mapping surface water)

Week 3: Image Classification

  • Introduction to image classification
  • Image classifiers (supervised vs unsupervised)
  • Land cover mapping in ArcGIS Pro
  • Fieldwork for image classification accuracy assessment

Week 4: Image Analysis Applications

  • Search and download image data from the USGS EarthExplorer site
  • Lake change analysis using Landsat data
  • Arctic greening: effect of arctic warming on vegetation productivity

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