Imagery, Automation, and Applications
4.0 /5- Offered byCoursera
Imagery, Automation, and Applications at Coursera Overview
Duration | 20 hours |
Mode of learning | Online |
Difficulty level | Intermediate |
Credential | Certificate |
Imagery, Automation, and Applications at Coursera Highlights
- Offered By University of California
- Earn a certificate from University of California
- 15% got a pay increase or promotion
- 38% got a tangible career benefit
Imagery, Automation, and Applications at Coursera Course details
- Use the imagery in two different common types of analysis: NDVI and trained classification
- Practice with tools to support image analysis using Raster Calculation and Spatial Analyst
- Develop a large processing workflow in ModelBuilder
- Use products derived from digital elevation models
- In this class you will become comfortable with spatial analysis and applications within GIS during four week-long modules:
- Week 1: You'll learn all about remotely sensed and satellite imagery, and be introduced to the electromagnetic spectrum. At the end of this week, you'll be able to find and download satellite imagery online and use it for two common types of analysis: NDVI and trained classification.
- Week 2: You'll learn how to use ModelBuilder to create large processing workflows that use parameters, preconditions, variables, and a new set of tools.
- Week 3: In week three, we'll make and use digital elevation models using some new, specific tools such as the cut fill tool, hillshades, viewsheds and more. We'll also go through a few common algorithms
- Week 4: We'll begin the final week by talking about a few spatial analyst tools we haven't yet touched on in the specialization
Imagery, Automation, and Applications at Coursera Curriculum
Week-1-Course Overview, Imagery, and Raster Calculator
Course Overview
Course Mechanics
Remote Sensing Basics
Characteristics of Remotely Sensed Data
Modes of Acquisition
Acquisition Platforms
Acquiring Imagery and Terrain Data
Working with Imagery in ArcMap
Normalized Difference Vegetation Index (NDVI)
Classifying Imagery and Derived Products
Map Algebra/Raster Calculator/Overlaying Rasters
Con/SetNull
Create Constant/Random Raster
Geospatial Modelling Environment
Week-2-ModelBuilder and Other Topics
Module 2 Overview
What is ModelBuilder?
Creating Toolboxes and Tools with ModelBuilder
Setting Up a Larger Mode
Using Interface Tools as Geoprocessing Tools in ModelBuilder
Feature Layers and Selections in Models
Branching, Preconditions, and Viewing Progress Interactively
Polishing Models for Reuse
Advanced Models and Exporting Models to Python
Geocoding and Reverse Geocoding
Time Enabled Data
Spatial Statistics Introduction
ArcGIS Pro Introduction
3 readings
Tutorial Assignment 2: ModelBuilder for Hydrology
Extra Practice: ModelBuilder
Extra Practice: Geocoding
Week-3-Digital Elevation Models and Common Algorithms
Module 3 Overview
Contours
Hillshade
Viewshed
Cut Fill
Vector-Based Suitability Analysis
Fuzzy Suitability Analysis
Watershed Processing
Processing DEMs into Streamlines
Week-4-Spatial Analyst and Where to Go from Here
Module 4 Oveview
Region Group
Focal Statistics and the Swiss Hillshade
Reclassify
Point Density
Online and Connected Applications
Collecting and Managing Data for Your Workflows
Additional Desktop GIS Topics
Programming GIS Software, Server-Side GIS, and Cartography
Other GIS Tools & Plugins, and Joining Communities
Course Summary
Continue Learning GIS
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Imagery, Automation, and Applications at Coursera Students Ratings & Reviews
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