Apply your GIS knowledge in this course on geospatial analysis, focusing on analysis tools, 3D data, working with rasters, projections, and environment variables. Through all four weeks of this course, we'll work through a project together - something unique to this course - from project conception, through data retrieval, initial data management and processing, and finally to our analysis products.
In this class you will learn the fundamentals of geospatial and environmental analysis during four week-long modules:
Week 1: Tour ArcToolbox and learn how to use common geospatial analysis tools built into ArcGIS
Week 2: Gain a working understanding of raster data models: symbolize, reproject, overlay, and assess rasters. Take a detour into 3D data models, and interpolation of observations into 3D surfaces and rasters
Week 3: Go in-depth on projections and coordinate systems, which are foundational to all GIS. Learn how to use environment variables to constrain your analyses and get better quality data products.
Week 4: Expand your knowledge of symbology. Learn how to visually display your data by classifying it in logical groupings and then symbolizing it on your map.
Take Geospatial and Environmental Analysis as a standalone course or as part of the Geographic Information Systems (GIS) Specialization. You should have equivalent experience to completing the first and second courses in this specialization, "Fundamentals of GIS" and "GIS Data Formats, Design, and Quality", before taking this course. By completing this third class in the Specialization you will gain the skills needed to succeed in the full program.

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Classifying and Viewing Data

In this third module, we're going to start off with talking all about projections. If you've taking the specialization with us, you may recall that we discussed this in the first course, but this will be an in-depth, more technical overview of projections and coordinate systems. In the second half of the module we'll learn about environment variables. By the end of this module, you will be able to describe coordinate systems, projected coordinate systems, compare the pros and cons of different projections, and define what environment variables are and what they are used for. You will also have the opportunity to actually begin to analyze your data in the course project.