Learning Geospatial Analysis with Python - Third Edition - Tapa blanda

Reseña del editor

Learn the core concepts of geospatial data analysis for building actionable and insightful GIS applications

Key Features

• Create GIS solutions using the new features introduced in Python 3.7
• Explore a range of GIS tools and libraries such as PostGIS, QGIS, and PROJ
• Learn to automate geospatial analysis workflows using Python and Jupyter

Book Description

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. With this systematic guide, you'll get started with geographic information system (GIS) and remote sensing analysis using the latest features in Python.

This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7. You'll learn everything you need to know about using software packages or APIs and generic algorithms that can be used for different situations. Furthermore, you'll learn how to apply simple Python GIS geospatial processes to a variety of problems, and work with remote sensing data.

By the end of the book, you'll be able to build a generic corporate system, which can be implemented in any organization to manage customer support requests and field support personnel.

What you will learn

• Automate geospatial analysis workflows using Python
• Code the simplest possible GIS in just 60 lines of Python
• Create thematic maps with Python tools such as PyShp, OGR, and the Python Imaging Library
• Understand the different formats that geospatial data comes in
• Produce elevation contours using Python tools
• Create flood inundation models
• Apply geospatial analysis to real-time data tracking and storm chasing

Who this book is for

This book is for Python developers, researchers, or analysts who want to perform geospatial modeling and GIS analysis with Python. Basic knowledge of digital mapping and analysis using Python or other scripting languages will be helpful.

Table of Contents

1. Learning about Geospatial Analysis with Python
2. Learning Geospatial Data
3. The Geospatial Technology Landscape
4. Geospatial Python Toolbox
5. Python and Geographic Information Systems
6. Python and Remote Sensing
7. Python and Elevation Data
8. Advanced Geospatial Python Modeling
9. Real-Time Data
10. Putting It All Together

Biografía del autor

Joel Lawhead is a PMI-certified Project Management Professional, a certified GIS Professional, and the Chief Information Officer of NVision Solutions Inc., an award-winning firm specializing in geospatial technology integration and sensor engineering for NASA, FEMA, NOAA, the US Navy, and many other commercial and non-profit organizations. Joel began using Python in 1997 and started combining it with geospatial software development in 2000. He has authored multiple editions of Learning Geospatial Analysis with Python and QGIS Python Programming Cookbook, both from Packt. He is also the developer of the open source Python Shapefile Library (PyShp) and maintains a geospatial technical blog, GeospatialPython, and Twitter feed, @SpatialPython.