ArcGIS Spatial Analyst

This course provides the foundation for understanding the operation of the ArcGIS Spatial Analyst extension, which provides a wide variety of important resources devoted to spatial analysis and modeling. You can create, query, draw maps, and analyze cell-based raster data; carry out an integrated raster / vector analysis; obtain new information from existing data; query information through several layers of data; and fully integrate raster data based on cells with traditional vector data sources.

Topics

  • Overview of ArcGIS Spatial Analyst
  • Work environment settings
  • Data preparation for analysis
  • Reclassification and data conversion
  • Surfaces Analysis
  • Generating data from surfaces
  • Interpolation of raster surfaces from vector data
  • Distance and Density tools execution
  • Working with map algebra
  • Use of the Raster Calculator
  • Supervised and unsupervised classification

Prerequisites

This course focuses on users with a Basic and Intermediate level in the use of Geographic Information Systems, specifically with ArcGIS for Desktop 10.x software, and must have completed the ArcGIS I or a similar course. You must also manage, at least generally, the basic concepts of spatial analysis and geospatial approach projects.

Furthermore, Windows environment skills for basic file management and browsing is required.

Those who complete the course will be able to:

  • Learn the interface and the distinct ways of accessing the geoprocesses of the extension
  • Understand the main concepts of Raster-Vector Analysis of spatial variables
  • Create maps of continuous surfaces
  • Build and analyze complex surfaces to identify patterns or characteristics within the data
  • Interpolate raster surfaces using different types of interpolation, in addition to understanding the advantages and disadvantages of each one of these
  • Execution of distance mapping and density, for calculating costs, routes and better understanding the spatial distribution of discrete variables on the ground
  • Use of Map Algebra to make weighted analysis between two or more raster layers, using the Raster Calculator
  • Run supervised and unsupervised classifications from remote sensing images

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