Performing Analysis with ArcGIS Desktop (10.0)

Description

In this course, you will acquire or improve skills to generate reliable results from different types of GIS analyses. The course teaches a proven process you can use to solve a variety of spatial problems including site selection, line of sight (visibility) analysis, and hot spot analysis. You will also learn regression analysis techniques for determining why a spatial pattern exists. This course is taught with an ArcInfo license of ArcGIS Desktop 10.0 software, and some course exercises use tools provided in the ArcGIS Spatial Analyst extension.

Who Should Attend

GIS analysts, specialists, and other experienced ArcGIS Desktop users who manage or conduct GIS analysis projects.

Learn How To

After completing this course you will be able to:

• Apply best practices to choose appropriate data, analysis methods, and GIS tools for a given project.
• Prepare vector and raster data for analysis.
• Build and modify a geoprocessing model to automate analysis tasks, examine what-if scenarios, and compare results.
• Create a weighted suitability model to select the best location for a new site.
• Apply spatial statistics to analyze, interpret, and quantify geographic data.
• Build a regression model to help determine why a spatial pattern exists.
• Evaluate analysis results and present them to decision makers.

Esri will provide the following software to use during class:

• ArcGIS 10.0 for Desktop (ArcInfo)
• ArcGIS 10.0 Spatial Analyst

Getting started with GIS analysis

• GIS analysis process
• Translating a flowchart into a model
• Using ModelBuilder to connect geoprocessing and analysis tools
• Building a parcel notification model

Preparing data for analysis

• Data quality issues
• Exploring and preparing data for analysis
• Modifying and converting spatial data
• Adding and calculating fields

Spatial modeling and GIS analysis

• Types of spatial models
• Choosing analysis methods and tools
• Building a site selection model

Creating more adaptive models

• Using Python branching scripts in a model
• Using iteration, feedback, and variables
• Analyzing model results

Analyzing raster data

• Planning for raster analysis
• Raster conversion
• Creating a Normalized Difference Vegetative Index (NDVI)

Creating surfaces

• Sources of surface data
• Creating surfaces
• Interpolation methods
• The importance of sample points
• Calculating density
• Evaluating results

Analyzing topographic surfaces

• Viewshed analysis
• Determining slope and aspect
• Determining line of sight

Analyzing distance

• Cell-based distance analysis
• Creating cost surfaces
• Using weights and masks
• Determining straight-line distance
• Determining direction and allocation

Planning and building a raster suitability model

• Binary and weighted suitability modeling concepts
• Planning a scale of suitability
• Reclassifying raster layers
• Layer weights
• Using the Weighted Overlay tool
• Building a weighted suitability model

Exploring data patterns and relationships using spatial statistics

• Spatial statistics concepts (standard deviation, confidence level, probability, z-score)
• Pattern and hot spot analysis
• Creating scatterplot graphs
• Summarizing spatial patterns using mean center, standard deviational ellipses, and Global Moran's I

Regression analysis

• Questions regression analysis can help answer
• Ordinary Least Squares and Geographically Weighted Regression
• Building regression models to analyze 911 call data

Exploring and refining analysis results

• Changing model parameters to view differences in results
• Using map animation to show a physical process
• Creating a video clip of animation

Completion of ArcGIS Desktop II: Tools and Functionality or Learning ArcGIS Desktop and ArcGIS Desktop III: GIS Workflows and Analysis or equivalent knowledge is required.