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Chris Garrard - Geoprocessing with Python [2016, PDF, ENG]

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Post 10-Oct-2016 01:00

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Geoprocessing with Python
Год издания: 2016
Автор: Chris Garrard
Жанр или тематика: Программирование
Издательство: Manning Publications
ISBN: 978-1617292149
Язык: Английский
Формат: PDF
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 360
Описание: Geoprocessing with Python teaches you how to use the Python programming language, along with free and open source tools, to read, write, and process geospatial data.
About the Technology
This book is about the science of reading, analyzing, and presenting geospatial data programmatically, using Python. Thanks to dozens of open source Python libraries and tools, you can take on professional geoprocessing tasks without investing in expensive proprietary packages like ArcGIS and MapInfo. The book shows you how.
About the Book
Geoprocessing with Python teaches you how to access available datasets to make maps or perform your own analyses using free tools like the GDAL, NumPy, and matplotlib Python modules. Through lots of hands-on examples, you’ll master core practices like handling multiple vector file formats, editing geometries, applying spatial and attribute filters, working with projections, and performing basic analyses on vector data. The book also covers how to manipulate, resample, and analyze raster data, such as aerial photographs and digital elevation models.
What's Inside
- Geoprocessing from the ground up
- Read, write, process, and analyze raster data
- Visualize data with matplotlib
- Write custom geoprocessing tools
- Three additional appendixes available online

Примеры страниц

Оглавление

brief contents
1 Introduction 1
2 Python basics 15
3 Reading and writing vector data 35
4 Working with different vector file formats 67
5 Filtering data with OGR 88
6 Manipulating geometries with OGR 105
7 Vector analysis with OGR 129
8 Using spatial reference systems 153
9 Reading and writing raster data 173
10 Working with raster data 208
11 Map algebra with NumPy and SciPy 237
12 Map classification 276
13 Visualizing data 287
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