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Learning Geospatial Analysis with Python-Second Edition

You're reading from   Learning Geospatial Analysis with Python-Second Edition An effective guide to geographic information systems and remote sensing analysis using Python 3

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Product type Paperback
Published in Dec 2015
Publisher Packt
ISBN-13 9781783552429
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Toc

Table of Contents (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python FREE CHAPTER 2. Geospatial Data 3. The Geospatial Technology Landscape 4. Geospatial Python Toolbox 5. Python and Geographic Information Systems 6. Python and Remote Sensing 7. Python and Elevation Data 8. Advanced Geospatial Python Modeling 9. Real-Time Data 10. Putting It All Together Index

Fiona


The Fiona library provides a simple Python API around the OGR library for data access and nothing more. This approach makes it easy to use and is less verbose than OGR while using Python. Fiona outputs GeoJSON by default. You can find a wheel file for Fiona at http://www.lfd.uci.edu/~gohlke/pythonlibs/#fiona.

As an example, we'll use the GIS_CensusTract_poly.shp file from the dbfpy example seen earlier in this chapter.

First we'll import fiona and Python's pprint module to format the output. Then, we'll open the shapefile and check its driver type:

>>> import fiona
>>> import pprint
>>> f = fiona.open("GIS_CensusTract_poly.shp")
>>> f.driver
ESRI Shapefile

Next, we'll check its coordinate reference system and get the data bounding box, as shown here:

>>> f.crs
{'init': 'epsg:4269'}
>>> f.bounds
(-89.8744162216216, 30.161122135135138, -89.1383837783784, 30.661213864864862)

Now, we'll view the data schema as geojson and format it using...

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