Python Scripting for Spatial Data Processing (Pete Bunting, et al)

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Python Scripting for Spatial Data Processing (Pete Bunting, et al)

This book is a beginner's guide to Python that teaches spatial data processing. It is utilized in the GIS and remote sensing courses at Aberystwyth University in the UK.

Among the applications that handle spatial data is the group that includes geographic information systems. Certain spatial studies are carried out repeatedly in the same manner for various areas or districts. As a result, it is advantageous when batch data processing can be carried out automatically by a software extension. Using psycopg2, ogr2ogr, and other tools, we use Python to automatically translate data flow diagrams into program code.

Python is a powerful, interactive, interpreted, and object-oriented scripting language. Python's syntax is a key feature, making it easy to learn and develop applications rapidly. Python's syntax is also comparable enough to lower-level languages, such as C/C++, and Java, to give you a foundation from which to advance your knowledge.

The fact that Python is a so-called memory-managed language, which means that you, the developer, do not directly control the memory utilization within your application, simplifies development considerably. That's not to suggest that memory use shouldn't be taken into account, and as a developer, you have some control over how much memory your scripts use, but these specifics are outside the scope of this course.

With support for Windows, Linux, Mac OS X, and the majority of other UNIX platforms, Python is cross-platform. Additionally, Python has access to a large number of libraries (such as custom-built and external C++ libraries), and it has grown to be a very popular language for many applications, including those using the internet, remote sensing, and geographic information systems (GIS).

Almost every activity, from straightforward file operations and text manipulation to picture processing, may be completed with Python. It can also be used to boost the capabilities of other, more complicated programs.

Ebook Details

About the Authors
  • Dr. Pete Bunting began his Ph.D. at Aberystwyth University's Institute of Geography and Earth Sciences (IGES) in 2004. When he finished in the summer of 2007, he was given a lectureship in remote sensing and GIS.
  • Now working at Plymouth Marine Laboratory is Daniel Clewley (Devon, UK). He focused on recognizing decadal change using JERS-1 and PALSAR data as he examined uncertainty for time-series remote sensing classification in wetland environments.
Published Date / Year
(May 4, 2013)
CC BY-SA 3.0
eBook Format
PDF (194 pages, 695 KB)

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