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 Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python Unleash the power of Python 3 with practical techniques for learning GIS and remote sensing

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837639175
Length 432 pages
Edition 4th Edition
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Table of Contents (18) Chapters Close

Preface 1. Part 1:The History and the Present of the Industry
2. Chapter 1: Learning about Geospatial Analysis with Python FREE CHAPTER 3. Chapter 2: Learning about Geospatial Data 4. Chapter 3: The Geospatial Technology Landscape 5. Part 2:Geospatial Analysis Concepts
6. Chapter 4: Geospatial Python Toolbox 7. Chapter 5: Python and Geospatial Algorithms 8. Chapter 6: Creating and Editing GIS Data 9. Chapter 7: Python and Remote Sensing 10. Chapter 8: Python and Elevation Data 11. Part 3:Practical Geospatial Processing Techniques
12. Chapter 9: Advanced Geospatial Modeling 13. Chapter 10: Working with Real-Time Data 14. Chapter 11: Putting It All Together 15. Assessments 16. Index 17. Other Books You May Enjoy

Computer-aided drafting

Computer-aided drafting (CAD) is worth mentioning, though it does not directly relate to geospatial analysis. The history of CAD system development parallels and intertwines with the history of geospatial analysis. CAD is an engineering tool that’s used to model two- and three-dimensional objects, usually for engineering and manufacturing purposes. The primary difference between a geospatial model and a CAD model is that a geospatial model is referenced to the Earth, whereas a CAD model can exist in abstract space.

For example, a three-dimensional blueprint of a building in a CAD system would not have latitude or longitude, but in a GIS, the same building model would have a location on Earth. However, over the years, CAD systems have taken on many features of GIS systems and are commonly used for smaller GIS projects. Likewise, many GIS programs can import CAD data that has been georeferenced. Traditionally, CAD tools were designed primarily to engineer data that was not geospatial.

However, engineers who became involved with geospatial engineering projects, such as designing a city’s utility electric system, would use the CAD tools that they were familiar with to create maps. Over time, the GIS software evolved to import the geospatial-oriented CAD data produced by engineers, and CAD tools evolved to support geospatial data creation and better compatibility with GIS software. AutoCAD by Autodesk and ArcGIS by Esri were the leading commercial packages to develop this capability, and the Geospatial Data Abstraction Library (GDAL) OGR library developers added CAD support as well.

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Learning Geospatial Analysis with Python - Fourth Edition
Published in: Nov 2023
Publisher: Packt
ISBN-13: 9781837639175
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