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ArcGIS 3: Performing Analysis

Overview

Description
Advance your foundational ArcGIS skills by learning how to obtain reliable results from different types of GIS analysis. You will apply a standard workflow to efficiently solve spatial problems using a variety of ArcGIS tools and vector, raster, and temporal data. Techniques to effectively share your analysis workflows and results are covered. This course is taught using ArcGIS for Desktop Advanced and some course exercises use tools provided in the ArcGIS Spatial Analyst extension.

Who Should Attend
GIS analysts, specialists, and others who manage or conduct GIS analysis projects.

Goals
After completion of this course you will be able to:
• Choose appropriate data, methods, and tools to plan, execute, and document a given analysis project.
• Automate analysis tasks using geoprocessing models.
• Create a weighted suitability model to select the optimal location for a new site.
• Apply spatial statistics to examine distribution patterns and identify hot spots.
• Model temporal data to analyze and visualize change over time.
• Share analysis results so they are accessible and repeatable.

Prerequisites
Completion of ArcGIS II: Essential Workflows or equivalent knowledge is required.

Course Outline

GIS analysis workflow
• Types of spatial analysis
• Steps in the workflow
• Options for sharing results

Preparing data for analysis
• Evaluating data quality
• Correcting spatial reference issues
• Sharing results as a map service

Proximity analysis
• Categories of proximity analysis
• Choosing the right tool based on the required output
• Measuring proximity: Geodesic or Euclidean?
• Performing proximity analysis to plan emergency response activities

Overlay analysis
• Techniques and tools
• Apportioning attributes
• Performing overlay analysis to estimate tornado damage
• Using model iterators and variables
• Creating geoprocessing packages to share results

Using raster data for suitability analysis
• Binary and weighted suitability models
• Suitability scales and levels of measurement
• Reclassifying data
• Determining the optimal location for a vineyard

Analyzing spatial patterns
• Quantifying patterns using spatial statistics
• Spatial statistics tools
• Hot spot analysis
• Building a model to analyze the distribution of public safety incidents
• Sharing the model as a geoprocessing service

Modeling temporal data
• What is time-aware data?
• Analyzing patterns in temporal data
• Working with animations and the time slider
• Sharing results as an animated map service