Performing Analysis with ArcGIS Desktop

This course teaches a proven process that can be applied to all types of spatial analysis projects. You will learn strategies for planning an analysis project and techniques for solving a variety of spatial problems, including site selection, line of sight (visibility) analysis, and hot spot analysis. You will also learn how to determine why a pattern exists using regression analysis. This course is taught with ArcGIS Spatial Analyst as some course exercises require that extension.

This course is designed for GIS analysts and others who need to perform different types of spatial analyses and generate reliable results that support decision making.

After completing this course you will be able to:

• Apply the steps of the recommended analysis process.
• Choose appropriate data, analysis methods, and GIS tools for a given project.
• Prepare vector and raster data for analysis.
• Create surfaces from sample data.
• Build and modify geoprocessing models.
• Create a weighted suitability model.
• Apply spatial statistics to analyze, interpret, and quantify geographic data.
• Build regression models to determine why a spatial pattern exists.
• Evaluate analysis results and present them to decision makers.

• Getting started with GIS analysis: GIS analysis and its benefits; Steps in the GIS analysis process; Applying steps of GIS analysis process to a given scenario; ArcGIS Server analysis demo; Translating a flowchart into a model; Using ModelBuilder to connect geoprocessing and analysis tools; Building a parcel notification model.
Translating a flowchart into a model; Using ModelBuilder to connect geoprocessing and analysis tools; Building a parcel notification model.
• Preparing data for analysis: Identifying what needs to be done to data prior to analysis; Exploring and preparing data for analysis; Modifying and converting spatial data; Datum transformation using a list variable in a model; Adding and calculating fields.
• Spatial modeling and GIS analysis: Spatial modeling and its benefits; Types of spatial models and examples of each; Describing and choosing analysis methods and tools; Building a site selection model.
• Creating more adaptive models: View a Python branching script in a model; Applying iterations in a model; Using iteration variables and variable substitution; Using model feedback; Setting a precondition on a tool in a model to tell it when to run.
• Analyzing raster data: Using raster data for analysis; Differences between raster and vector for analysis; Map algebra basics; Using Map Algebra for raster analysis.
• Creating surfaces: Sources of surface data; Applications of using surfaces; Creating surfaces; Interpolation methods; Interpolating surfaces; The importance of sample points; Testing your surface.
• Analyzing topographic surfaces: Analyzing topography, density, and distance; Solar radiation, slope, and aspect; Viewshed (line of sight or visibility analysis).
• Analyzing distance: Cell-based distance analysis; Determining straight-line distance; Determining direction and allocation; Determining cost distance and cost path.
• Planning and building a raster suitability model: Binary and weighted suitability modeling; Planning a scale of suitability, Determining proper layers and more important layers; Determining layer weights; Reclassifying raster data to a common scale; 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); Reasons for using spatial statistics; Pattern analysis; Creating scatterplot graphs; Summarizing spatial patterns using mean center, standard deviational ellipse, and Global Moran's I; Performing hot spot analyses.
• Regression analysis: Reasons to use regression analysis; Questions regression analysis can help answer; Ordinary Least Squares and Geographically Weighted regression; Building regression models; Creating a properly specified regression model.
• Exploring and refining analysis results: Evaluating analysis results; Changing model parameters to view differences in results; Use map animation to show a physical process; Create 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.

This course is designed to work with the following software:

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