Mastering Geospatial Analysis with Python Explore GIS processing and learn to work with GeoDjango,
CARTOframes and MapboxGL-Jupyter
By 作者: Silas Toms - Eric Van Rees - Paul Crickard
ISBN-10 书号: 1788293339
ISBN-13 书号: 9781788293334
Release Finelybook 出版日期: 2018-04-27
Pages 页数: 440
The Book Description
Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis.
You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.
1: PACKAGE INSTALLATION AND MANAGEMENT
2: INTRODUCTION TO GEOSPATIAL CODE LIBRARIES
3: INTRODUCTION TO GEOSPATIAL DATABASES
4: DATA TYPES, STORAGE, AND CONVERSION
5: VECTOR DATA ANALYSIS
6: RASTER DATA PROCESSING
7: GEOPROCESSING WITH GEODATABASES
8: AUTOMATING QGIS ANALYSIS
9: ARCGIS API FOR PYTHON AND ARCGIS ONLINE
10: GEOPROCESSING WITH A GPU DATABASE
11: FLASK AND GEOALCHEMY2
13: GEOSPATIAL REST API
14: CLOUD GEODATABASE ANALYSIS AND VISUALIZATION
15: AUTOMATING CLOUD CARTOGRAPHY
16: PYTHON GEOPROCESSING WITH HADOOP
What You Will Learn
Manage code libraries and abstract geospatial analysis techniques using Python 3.
Explore popular code libraries that perform specific tasks for geospatial analysis.
Utilize code libraries for data conversion, data management, web maps, and REST API creation.
Learn techniques related to processing geospatial data in the cloud.
Leverage features of Python 3 with geospatial databases such as PostGIS, SQL Server, and Spatialite.
Eric van Rees
Eric van Rees was first introduced to Geographical Information Systems (GIS) when studying Human Geography in the Netherlands. For 9 years, he was the editor-in-chief of GeoInformatics, an international GIS, surveying, and mapping publication and a contributing editor of GIS Magazine. During that tenure, he visited many geospatial user conferences, trade fairs, and industry meetings. He focuses on producing technical content, such as software tutorials, tech blogs, and innovative new use cases in the mapping industry.