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Geoprocessing with Python
85% of respondents would recommend this to a friend
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Take on professional geoprocessing tasks without investing in expensive proprietary packages.
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- SummaryGeoprocessing 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 TechnologyThis 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 BookGeoprocessing 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 InsideGeoprocessing from the ground upRead, write, process, and analyze raster dataVisualize data with matplotlibWrite custom geoprocessing toolsThree additional appendixes available onlineAbout the ReaderTo read this book all you need is a basic knowledge of Python or a similar programming language.About the AuthorChris Garrard works as a developer for Utah State University and teaches a graduate course on Python programming for GIS.Table of ContentsIntroductionPython basicsReading and writing vector dataWorking with different vector file formatsFiltering data with OGRManipulating geometries with OGRVector analysis with OGRUsing spatial reference systemsReading and writing raster dataWorking with raster dataMap algebra with NumPy and SciPyMap classificationVisualizing dataAppendixesA - InstallationB - ReferencesC - OGR - online onlyD - OSR - online onlyE - GDAL - online only
| Publisher | Manning |
| Publication date | May 23, 2016 |
| Edition | First Edition |
| Language | English |
| Print length | 360 pages |
| ISBN-10 | 1617292141 |
| ISBN-13 | 978-1617292149 |
| Item Weight | 1.34 pounds (610 grams) |
| Dimensions | 7.38 x 1 x 9.25 inches (18.7 x 2.5 x 23.5 cm) |
Who Should Buy?
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GIS Analysts
Ideal for GIS analysts looking to automate workflows and enhance geospatial data processing using Python scripting.
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Data Scientists
Data scientists interested in geospatial analysis can leverage Python's libraries to analyze and manipulate geographic information efficiently.
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Environmental Researchers
Perfect for environmental researchers who require detailed geoprocessing capabilities to analyze spatial data for their studies.
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Beginners in Programming
Not suitable for beginners unfamiliar with programming concepts, as it assumes foundational knowledge of Python and geospatial analysis.
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Software Development Editorial Review
** Geoprocessing with Python** "Geoprocessing with Python" has garnered an enthusiastic reception from readers, particularly those engaged in geospatial analysis and GIS (Geographic Information Systems). The author’s ability to simplify the complexities of geoprocessing through a clear and direct style resonates with users, making advanced concepts accessible to those at various levels of expertise. Consistently praised for its well-structured chapters, the book builds foundational knowledge effectively, allowing readers to gain a profound understanding of Python programming within a geospatial context. It provides detailed, step-by-step Python code examples that facilitate comprehension and practical application. The text includes a diverse range of examples from vector and raster data, enabling readers to familiarize themselves with different geospatial formats. Another highlight of the book is its thorough guidance on setting up the Python programming environment, which many readers found clearer and more straightforward compared to other resources. This approach not only enhances the overall learning experience but also equips practitioners with skills that can extend beyond the book’s content, applicable even with other programming languages and libraries. Readers appreciate the extensive information compiled in one place, which would often require extensive time and effort to source individually online. Many Consider this book an essential resource for anyone aiming to delve into geospatial problems, regardless of their prior experience with Python. In summary, "Geoprocessing with Python" stands out for its clarity, comprehensive content, and practical approach, making it an excellent recommendation for GIS professionals and Python developers alike. **
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Pros
- Clear and straightforward explanations
- Well-structured chapters building on previous concepts
- Detailed step-by-step Python code examples
- Comprehensive coverage of GDAL and other geospatial libraries
- Practical applications relevant to GIS professionals
- Clear guidance on setting up the Python programming environment
Cons
- Limited to GDAL as the primary focus, which may not align with those preferring newer libraries exclusively.
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Features & Benefits
- Learn to read, write, and process geospatial data using Python.
- Utilize free open source tools like GDAL, NumPy, and matplotlib.
- Master core practices with hands-on examples and custom geoprocessing tools.
- Handle multiple vector file formats and perform basic analyses on vector data.
- Manipulate and analyze raster data including aerial photographs and elevation models.
- Includes a free eBook with your print book purchase.
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