Geospatial Development By Example With Python
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Geospatial Development By Example with Python
Author: Pablo Carreira
language: en
Publisher: Packt Publishing Ltd
Release Date: 2016-01-30
Build your first interactive map and build location-aware applications using cutting-edge examples in Python About This Book Learn the full geo-processing workflow using Python with open source packages Create press-quality styled maps and data visualization with high-level and reusable code Process massive datasets efficiently using parallel processing Who This Book Is For Geospatial Development By Example with Python is intended for beginners or advanced developers in Python who want to work with geographic data. The book is suitable for professional developers who are new to geospatial development, for hobbyists, or for data scientists who want to move into some simple development. What You Will Learn Prepare a development environment with all the tools needed for geo-processing with Python Import point data and structure an application using Python's resources Combine point data from multiple sources, creating intuitive and functional representations of geographic objects Filter data by coordinates or attributes easily using pure Python Make press-quality and replicable maps from any data Download, transform, and use remote sensing data in your maps Make calculations to extract information from raster data and show the results on beautiful maps Handle massive amounts of data with advanced processing techniques Process huge satellite images in an efficient way Optimize geo-processing times with parallel processing In Detail From Python programming good practices to the advanced use of analysis packages, this book teaches you how to write applications that will perform complex geoprocessing tasks that can be replicated and reused. Much more than simple scripts, you will write functions to import data, create Python classes that represent your features, and learn how to combine and filter them. With pluggable mechanisms, you will learn how to visualize data and the results of analysis in beautiful maps that can be batch-generated and embedded into documents or web pages. Finally, you will learn how to consume and process an enormous amount of data very efficiently by using advanced tools and modern computers' parallel processing capabilities. Style and approach This easy-to-follow book is filled with hands-on examples that illustrate the construction of three sample applications of how to write reusable and interconnected Python code for geo-processing.
Learning Geospatial Analysis with Python
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.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.
Ethics, Machine Learning, and Python in Geospatial Analysis
In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management. Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and machine learning. The book’s meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques.