If you know Python and would like to use it for Geospatial Analysis this book is exactly what you've been looking for. With an organized, user-friendly approach it covers all the bases to give you the necessary skills and know-how.
Overview
In Detail
Geospatial analysis is used in almost every field you can think of from medicine, to defense, to farming. It is an approach to use statistical analysis and other informational engineering to data which has a geographical or geospatial aspect. And this typically involves applications capable of geospatial display and processing to get a compiled and useful data.
"Learning Geospatial Analysis with Python" uses the expressive and powerful Python programming language to guide you through geographic information systems, remote sensing, topography, and more. It explains how to use a framework in order to approach Geospatial analysis effectively, but on your own terms.
"Learning Geospatial Analysis with Python" starts with a background of the field, a survey of the techniques and technology used, and then splits the field into its component speciality areas: GIS, remote sensing, elevation data, advanced modelling, and real-time data.
This book will teach you everything there is to know, from using a particular software package or API to using generic algorithms that can be applied to Geospatial analysis. 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.
"Learning Geospatial Analysis with Python" will round out your technical library with handy recipes and a good understanding of a field that supplements many a modern day human endeavors.
What you will learn from this book
Approach
This is a tutorial-style book that helps you to perform Geospatial and GIS analysis with Python and its tools/libraries. This book will first introduce various Python-related tools/packages in the initial chapters before moving towards practical usage, examples, and implementation in specialized kinds of Geospatial data analysis.
Who this book is written for
This book is for anyone who wants to understand digital mapping and analysis and who uses Python or another scripting language for automation or crunching data manually.This book primarily targets Python developers, researchers, and analysts who want to perform Geospatial, modeling, and GIS analysis with Python.
Joel Lawhead
Joel Lawhead is a PMI-certified Project Management Professional (PMP) and the Chief Information Officer (CIO) for NVisionSolutions.com, an award-winning firm specializing in geospatial technology integration and sensor engineering.
He began using Python in 1997 and began combining it with geospatial software development in 2000. He has been published in two editions of the Python Cookbook by O'Reilly. He is also the developer of the widely used open source Python Shapefile Library (PyShp) and maintains the geospatial technical blog GeospatialPython.com and Twitter feed @SpatialPython discussing the use of the Python programming language within the geospatial industry.
In 2011, he 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 involving shapefiles.
He has served as the lead architect, project manager, and co-developer for geospatial applications used by US government agencies including NASA, FEMA, NOAA, the US Navy, as well as many commercial and non-profit organizations. In 2002, he received the international "Esri Special Achievment in GIS" award for work on the Real-time Emergency Action Coordination Tool (REACT) for emergency management using geospatial analysis.
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