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Geospatial and Environmental Analysis

University of California, Davis via Coursera

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  • Provider Coursera
  • Subject GIS
  • $ Cost Free Online Course (Audit)
  • Session In progress
  • Language English
  • Certificate Paid Certificate Available
  • Start Date
  • Duration 4 weeks long

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Overview

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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.

Syllabus

Course Overview & Geospatial Analysis
In the first module of Geospatial and Environmental Analysis, we will be learning about a plethora of common tools used with vector data in ArcGIS for geospatial analysis projects. By the end of the module, you will be able to use: the clip tool, erase tool, identity tool, near tool, point distance tool, merge tool, dissolve tool, tabulate area tool, buffers, and conversion tools. In addition, you will also begin work on a geospatial analysis project that we will be using throughout this course.

Rasters and Surfaces
In this second module, we're going to cover raster data in depth and how to create 3-dimensional surfaces from our rasters. After completing this module you should be able to: describe different raster data formats and how they're used, use comparison and swipe tools, resample and retroject rasters, describe how fishnets and Thiessen polygons are used, create TINs, and convert your rasters to 3D data using ArcScene. In addition, you will continue your geospatial analysis project as you begin to plan your approach.

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.

Working Through a Project
In the final module of this course, we're going to devote some time to discussing symbology. We've talked about symbology use a little bit in some of the other courses of the specialization, but this module provides a much more in-depth look at symbology use in ArcGIS. After viewing the videos in this module, you'll be able to design color ramps for your data, bin or classify your data appropriately, stretch raster boundaries, and copy and reuse symbology on multiple layers. Finally, we'll wrap up the geospatial analysis project before you begin work on the final (peer-reviewed) assignment for this course.

Taught by

Nick Santos

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