Course Summary
Spatial Analysis is a course that teaches you how to analyze and interpret spatial data using different techniques and tools. You will learn how to use GIS software, spatial statistics, and more to solve real-world problems.Key Learning Points
- Learn the basics of spatial analysis and how it can be used in different fields
- Understand how to use GIS software and tools to analyze spatial data
- Explore different techniques for spatial analysis, such as spatial statistics and network analysis
Related Topics for further study
Learning Outcomes
- Understand the basic principles of spatial analysis and how it can be applied to different fields
- Learn how to use GIS software and other tools to analyze spatial data
- Apply different techniques for spatial analysis, such as spatial statistics and network analysis, to real-world problems
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of statistics
- Familiarity with data analysis software (e.g. Excel, R, Python)
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Video-based
Similar Courses
- Geographic Information Systems (GIS) Specialization
- Data Science Essentials
- Applied Data Science with Python Specialization
Related Education Paths
Notable People in This Field
- Founder and President of Esri
- Emeritus Professor of Geography at UC Santa Barbara
Related Books
Description
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.
Knowledge
- Create 3-dimensional surfaces
- Create triangulated irregular networks (TIN) and modify rasters to 3D data
- Develop and analyze data for the geospatial analysis project
- Design color ramps for your data
Outline
- Course Overview & Geospatial Analysis
- Course Overview
- Course Mechanics
- Module 1 Overview
- Clip Tool
- Erase and Identity Tools
- Buffers and Multiple Ring Buffer
- Near and Generate Near Table Tools
- Merge Tool
- Dissolve Tool
- Behind the Scenes: Preparing the Dissolve Tool Lecture Data
- Tabulate Area
- Conversion Tools
- Making Charts and Graphs in ArcMap
- Geospatial Analysis Assignment Intro
- Data Acquisition for Our Project
- Getting the Crop Data
- Module 1 Summary
- Getting Started in this Course
- Tutorial Assignment 1: Generating Streamlines from Elevation Models
- Extra Practice: Use Geoprocessing Tools on New Data
- Lesson 1: Geospatial Analysis
- Rasters and Surfaces
- Module 2 Overview
- Raster Data Formats
- Raster Display Options
- Comparison/Swipe Tools
- Resampling and Cell Assignment
- Reprojecting Rasters
- Clipping Rasters and Extract by Mask
- Raster Mosaics
- Surfaces and Interpolation
- Rasters as 3D Data
- Thiessen Polygons and Fishnets
- TINs
- TINs in Action
- Z Values and 3D Data
- 3D Scenes
- Setting Up the Data, Part 1
- Setting Up the Data, Part 2
- Module 2 Summary
- Tutorial Assignment 2: Creating and Assessing DEMs from Points and Raster Data
- Extra Practice 2: Working with New Tools
- Lesson 3: Working with Rasters
- Lesson 4: Surfaces and the Third Dimension
- Classifying and Viewing Data
- Module 3 Overview
- Overview of Projections and Coordinate Systems
- Datums
- Geographic Coordinate Systems
- Preserving Properties of Data with Projections
- Common Projected Coordinate Systems
- Projections in Action
- What are Environment Variables?
- Output Coordinate System Environment Variable
- Extent Environment Variable
- Cell Size, Mask, and Snap Raster Environment Settings
- Project Data Analysis
- Module 3 Summary
- Tutorial Assignment 3: Spawning Redds and Timber Harvests - A Watershed-based Analysis
- Lesson 6: Projections and Coordinate Systems
- Lesson 7: Environment Variables
- Working Through a Project
- Module 4 Overview
- Color Ramps
- Binning/Classifying Data
- Stretching Rasters
- Copying Symbology
- Project Data Analysis and Wrapup
- Module 4 Summary
- Course Summary
- Extra Practice: Maplex Labeling
- Lesson 9: Symbology
Summary of User Reviews
The Spatial Analysis course on Coursera has received positive reviews from users. Many students found that the course was engaging and informative. Overall, the course has a high rating. One key aspect that many users thought was good is the clear and concise explanations provided by the instructor. Pros: - Engaging and informative - Clear and concise explanations - Well-structured course materials - Good balance of theory and practical applications - Useful for professionals in various fields. Cons: - Some users found the course challenging - Not all course materials were available for download - Some users wished the course went more in-depth into certain topics - Lengthy lectures may be difficult to follow for some users - Course may be too basic for advanced learners.Nick Santos
4.8 Raiting
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