By Chris Garrard
Geoprocessing with Python teaches you the way to exploit the Python programming language, besides loose and open resource instruments, to learn, write, and method geospatial data.
Purchase of the print booklet contains a loose publication in PDF, Kindle, and ePub codecs from Manning Publications.
About the Technology
This ebook is ready the technological know-how of analyzing, studying, and offering geospatial facts programmatically, utilizing Python. due to dozens of open resource Python libraries and instruments, you could tackle expert geoprocessing initiatives with out making an investment in dear proprietary applications like ArcGIS and MapInfo. The ebook indicates you how.
About the Book
Geoprocessing with Python teaches you ways to entry on hand datasets to make maps or practice your personal analyses utilizing loose instruments just like the GDAL, NumPy, and matplotlib Python modules. via plenty of hands-on examples, you’ll grasp middle practices like dealing with a number of vector dossier codecs, modifying geometries, employing spatial and characteristic filters, operating with projections, and acting simple analyses on vector facts. The booklet additionally covers the best way to manage, resample, and study raster information, comparable to aerial photos and electronic elevation models.
- Geoprocessing from the floor up
- Read, write, strategy, and learn raster data
- Visualize info with matplotlib
- Write customized geoprocessing tools
- Three extra appendixes to be had online
About the Reader
To learn this e-book all you would like is a simple wisdom of Python or the same programming language.
About the Author
Chris Garrard works as a developer for Utah nation college and teaches a graduate path on Python programming for GIS.
Table of Contents
- Python basics
- Reading and writing vector data
- Working with varied vector dossier formats
- Filtering facts with OGR
- Manipulating geometries with OGR
- Vector research with OGR
- Using spatial reference systems
- Reading and writing raster data
- Working with raster data
- Map algebra with NumPy and SciPy
- Map classification
- Visualizing data
- A - Installation
- B - References
- C - OGR - on-line only
- D - OSR - on-line only
- E - GDAL - on-line only
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Extra resources for Geoprocessing with Python
This is where the edit window comes in. You can use the File menu in IDLE to open a new window, which will contain an empty file. py extension first. The output from the script will be sent to the interactive window. Speaking of output, in many of the interactive examples in this book I type a variable name to see what the variable contains, but this won’t work if you’re running the code from a script. Instead, you need to use print to explicitly tell it to send information to the output window.
This example iterates through a list of names and prints a message for each one: >>> names = ['Chris', 'Janet', 'Tami'] >>> for name in names: ... format(name)) ... Hello Chris! Hello Janet! Hello Tami! The first time through the loop, the name variable is equal to ‘Chris’, the second time it holds ‘Janet’, and the last time it is equal to ‘Tami’. I called this variable name, but it can be called anything you want. 30 CHAPTER 2 Python basics THE RANGE FUNCTION The range function makes it easy to iterate over a sequence of numbers.
5 CHAPTER 1 Introduction Summary ■ ■ ■ ■ Python is a powerful multiplatform programming language that’s relatively easy to learn. Free and open source software is not only free with regard to price (free beer), but also allows for many freedoms with how it’s used (free speech). Many excellent open source Python modules exist for processing both vector and raster geospatial data. You don’t give up quality by using open source tools. In fact several of these packages are also used by proprietary software.