English | 28 Dec. 2015 | ISBN: 1783552425 | 394 Pages | PDF (True) | 12.27 MB
If you are a Python developer, researcher, or analyst who wants to perform Geospatial, modeling, and GIS analysis with Python, then this book is for you.
Familarity with digital mapping and analysis using Python or another scripting language for automation or crunching data manually is appreciated.
About This Book
Construct applications for GIS development by exploiting Python
This focuses on built-in Python modules and libraries compatible with the Python Packaging Index distribution system—no compiling of C libraries necessary
This practical, hands-on tutorial teaches you all about Geospatial analysis in Python
What You Will Learn
Automate Geospatial analysis workflows using Python
Code the simplest possible GIS in 60 lines of Python
Mold thematic maps with Python tools
Get hold of the various forms that geospatial data comes in
Produce elevation contours using Python tools
Create flood inundation models
Apply Geospatial analysis to find out about real-time data tracking and for storm chasing
Geospatial Analysis is used in almost every field you can think of from medicine, to defense, to farming. This book will guide you gently into this exciting and complex field. It walks you through the building blocks of geospatial analysis and how to apply them to influence decision making using the latest Python software.
Learning Geospatial Analysis with Python, 2nd Edition uses the expressive and powerful Python 3 programming language to guide you through geographic information systems, remote sensing, topography, and more, while providing a framework for you to approach geospatial analysis effectively, but on your own terms. We start by giving you a little background on the field, and a survey of the techniques and technology used. We then split the field into its component specialty areas: GIS, remote sensing, elevation data, advanced modeling, and real-time data.
This book will teach you everything you need to know about, Geospatial Analysis from using a particular software package or API to using generic algorithms that can be applied. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don’t become bogged down in just getting ready to do analysis. This book will round out your technical library through handy recipes that will give you a good understanding of a field that supplements many a modern day human endeavors.
Joel Lawhead is a project management institute-certified Project Management Professional (PMP), certified GIS Professional (GISP), and the Chief Information Officer (CIO) of NVision Solutions Inc., an award-winning firm that specializes in geospatial technology integration and sensor engineering.
Joel began using Python in 1997 and started combining it with geospatial software development in 2000. He is the author of the first edition of Learning Geospatial Analysis with Python and QGIS Python Programming Cookbook, both by Packt Publishing. His Python cookbook recipes were featured in two editions of Python Cookbook, O'Reilly Media. He is also the developer of the widely-used, open source Python Shapefile Library (PyShp). He maintains the geospatial technical blog http://geospatialpython.com/ and the Twitter feed, @SpatialPython, which discusses the use of the Python programming language in the geospatial industry.
In 2011, Joel reverse-engineered and published the undocumented shapefile spatial indexing format and assisted fellow geospatial Python developer, Marc Pfister, in reversing the algorithm used, allowing developers around the world to create better-integrated and more robust geospatial applications.
Joel serves as the lead architect, project manager, and co-developer for geospatial applications used by U.S. government agencies, including NASA, FEMA, NOAA, the U.S. Navy, and many other commercial and non-profit organizations. In 2002, he received the international Esri Special Achievement in GIS award for his work on the Real-Time Emergency Action Coordination Tool (REACT), for emergency management using geospatial analysis.