- Platform
- Coursera
- Provider
- University of California, Davis
- Effort
- 2-5 hours a week
- Length
- 4 weeks
- Language
- English
- Credentials
- Paid Certificate Available
- Part of
- Course Link
Overview
Welcome to the last course of the specialization (unless your continuing on to the capstone project, of course!).
Using the knowledge you’ve learned about ArcGIS, complete technical tasks such raster calculations and suitability analysis. 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. We'll also explore a few topics that we don't really have time to discuss in detail, but might whet your appetite for future learning in other avenues: geocoding, time-enabled data, spatial statistics, and ArcGIS Pro.
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 including a very important one: the suitability analysis.
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: Region Group to make our own zones, Focal Statistics to smooth a hillshade, Reclassify to change values, and Point Density to create a density surface. Finally, we'll wrap up by talking about a few more things that you might want to explore more as you start working on learning about GIS topics on your own.
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, second, and third courses in this specialization, "Fundamentals of GIS," "GIS Data Formats, Design, and Quality", and "Geospatial and Environmental Analysis," respectively, before taking this course. By completing the fourth class you will gain the skills needed to succeed in the Specialization capstone.
WHAT YOU WILL LEARN
Taught by
Nick Santos
Welcome to the last course of the specialization (unless your continuing on to the capstone project, of course!).
Using the knowledge you’ve learned about ArcGIS, complete technical tasks such raster calculations and suitability analysis. 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. We'll also explore a few topics that we don't really have time to discuss in detail, but might whet your appetite for future learning in other avenues: geocoding, time-enabled data, spatial statistics, and ArcGIS Pro.
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 including a very important one: the suitability analysis.
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: Region Group to make our own zones, Focal Statistics to smooth a hillshade, Reclassify to change values, and Point Density to create a density surface. Finally, we'll wrap up by talking about a few more things that you might want to explore more as you start working on learning about GIS topics on your own.
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, second, and third courses in this specialization, "Fundamentals of GIS," "GIS Data Formats, Design, and Quality", and "Geospatial and Environmental Analysis," respectively, before taking this course. By completing the fourth class you will gain the skills needed to succeed in the Specialization capstone.
WHAT YOU WILL LEARN
- 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
Syllabus
Course Overview, Imagery, and Raster Calculator
In this module, we'll learn all about remote sensing and satellite imagery, starting out with an introduction to remotely sensed data and the electromagnetic spectrum before learning about satellite and aerial imagery capture and data products. You'll learn how to find and download satellite imagery online and how to use it in two different common types of analysis: NDVI and a trained classification. In the second lesson, you'll learn how to use some basic tools to support image analysis using Raster Calculator and Spatial Analyst.
ModelBuilder and Other Topics
In this module, we will learn about ModelBuilder, a drag and drop tool for automating, and reusing workflows in ArcGIS. We'll explore how models are constructed, build our own models, and undertake building a large processing workflow together in ModelBuilder that uses parameters, preconditions, variables, and a set of tools we haven't used before to work. In the second half of the module, we'll take a brief look at a few topics you should know about, but that we won't have time to explore in depth. You'll be introduced to geocoding, time enabled data, spatial statistics, and ArcGIS Pro. These are little teasers of potential capabilities you might want to explore more in the future on your own.
Digital Elevation Models and Common Algorithms
In this module, we'll be looking at DEMs and workflows. In the first half, we'll make and use a handful of products derived from digital elevation models, including contour lines, hillshades, viewsheds, and the cut fill tool. In the second half of the module, we'll go through a few common algorithms, starting with one of the most important ones to know: the suitability analysis. Then, we'll learn about the hydrologic processing you did in the tutorial assignment for the previous module and go through it step by step together.
Spatial Analyst and Where to Go from Here
In this module, we'll start by learning how to use a few different tools and concepts in Spatial Analyst that we haven't touched on before. We'll use Region Group to make our own zones, Focal Statistics to smooth a hillshade, Reclassify to change values, and Point Density to create a density surface. In the second half of the module, we'll give you some suggestions of directions for future learning by showing you all the things we *didn't* cover in this specialization, including web and mobile GIS applications, field data collection workflows, industry specific tools and workflows, spatial statistics, in-depth design and cartography, programming and GIS servers, and other GIS systems like QGIS and companion applications like Geospatial Modelling Environment. These can serve as seeds for your future GIS learning and careers!
Course Overview, Imagery, and Raster Calculator
In this module, we'll learn all about remote sensing and satellite imagery, starting out with an introduction to remotely sensed data and the electromagnetic spectrum before learning about satellite and aerial imagery capture and data products. You'll learn how to find and download satellite imagery online and how to use it in two different common types of analysis: NDVI and a trained classification. In the second lesson, you'll learn how to use some basic tools to support image analysis using Raster Calculator and Spatial Analyst.
ModelBuilder and Other Topics
In this module, we will learn about ModelBuilder, a drag and drop tool for automating, and reusing workflows in ArcGIS. We'll explore how models are constructed, build our own models, and undertake building a large processing workflow together in ModelBuilder that uses parameters, preconditions, variables, and a set of tools we haven't used before to work. In the second half of the module, we'll take a brief look at a few topics you should know about, but that we won't have time to explore in depth. You'll be introduced to geocoding, time enabled data, spatial statistics, and ArcGIS Pro. These are little teasers of potential capabilities you might want to explore more in the future on your own.
Digital Elevation Models and Common Algorithms
In this module, we'll be looking at DEMs and workflows. In the first half, we'll make and use a handful of products derived from digital elevation models, including contour lines, hillshades, viewsheds, and the cut fill tool. In the second half of the module, we'll go through a few common algorithms, starting with one of the most important ones to know: the suitability analysis. Then, we'll learn about the hydrologic processing you did in the tutorial assignment for the previous module and go through it step by step together.
Spatial Analyst and Where to Go from Here
In this module, we'll start by learning how to use a few different tools and concepts in Spatial Analyst that we haven't touched on before. We'll use Region Group to make our own zones, Focal Statistics to smooth a hillshade, Reclassify to change values, and Point Density to create a density surface. In the second half of the module, we'll give you some suggestions of directions for future learning by showing you all the things we *didn't* cover in this specialization, including web and mobile GIS applications, field data collection workflows, industry specific tools and workflows, spatial statistics, in-depth design and cartography, programming and GIS servers, and other GIS systems like QGIS and companion applications like Geospatial Modelling Environment. These can serve as seeds for your future GIS learning and careers!
Taught by
Nick Santos