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Geospatial Data Analytics on AWS

You're reading from   Geospatial Data Analytics on AWS Discover how to manage and analyze geospatial data in the cloud

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804613825
Length 276 pages
Edition 1st Edition
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Authors (3):
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Scott Bateman Scott Bateman
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Scott Bateman
Jeff DeMuth Jeff DeMuth
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Jeff DeMuth
Janahan Gnanachandran Janahan Gnanachandran
Author Profile Icon Janahan Gnanachandran
Janahan Gnanachandran
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Table of Contents (23) Chapters Close

Preface 1. Part 1: Introduction to the Geospatial Data Ecosystem
2. Chapter 1: Introduction to Geospatial Data in the Cloud FREE CHAPTER 3. Chapter 2: Quality and Temporal Geospatial Data Concepts 4. Part 2: Geospatial Data Lakes using Modern Data Architecture
5. Chapter 3: Geospatial Data Lake Architecture 6. Chapter 4: Using Geospatial Data with Amazon Redshift 7. Chapter 5: Using Geospatial Data with Amazon Aurora PostgreSQL 8. Chapter 6: Serverless Options for Geospatial 9. Chapter 7: Querying Geospatial Data with Amazon Athena 10. Part 3: Analyzing and Visualizing Geospatial Data in AWS
11. Chapter 8: Geospatial Containers on AWS 12. Chapter 9: Using Geospatial Data with Amazon EMR 13. Chapter 10: Geospatial Data Analysis Using R on AWS 14. Chapter 11: Geospatial Machine Learning with SageMaker 15. Chapter 12: Using Amazon QuickSight to Visualize Geospatial Data 16. Part 4: Accessing Open Source and Commercial Platforms and Services
17. Chapter 13: Open Data on AWS 18. Chapter 14: Leveraging OpenStreetMap on AWS 19. Chapter 15: Feature Servers and Map Servers on AWS 20. Chapter 16: Satellite and Aerial Imagery on AWS 21. Index 22. Other Books You May Enjoy

Quality and Temporal Geospatial Data Concepts

Geospatial data is everywhere, in every industry, and in nearly every file format. The good news is that this broad range of data can be stored, transformed, analyzed, and visualized on AWS. In this chapter, we will talk about some of the different scenarios, file formats, workflows, and data normalization challenges that are common in geospatial data. Whether you are in oil and gas, healthcare, retail, power and utility, agriculture, or mining, to name a few, you have probably already done some work with GIS data. GIS data is ubiquitous in everyday applications, so it’s highly likely you have worked with geospatial data and didn’t even know it. In this chapter, you will learn about the importance of quality and time dimensions in your geospatial data through the following topics:

  • Quality impact on geospatial data
  • Transmission methods
  • Streaming data
  • Understanding file formats
  • Normalizing data
  • Considering...
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