The document provides an overview of using Python in geoinformatics, highlighting its capabilities, common pitfalls, and various frameworks like ArcGIS and QGIS. It explains how Python's scripting can extend geospatial data management and visualization through tools such as KML and pyproj. Additionally, it mentions the importance of community support and available resources for learning Python in this field.

1. Marianna Zichar
University of Debrecen

2. Agenda
 Motivation
 The language (with the main pitfalls)
 ArcGIS
 KML
 QGIS
 Projections
 Visualization
 Analysis and management of geospatial data
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3. The language
 General-purpose interpreted, interactive, high-level
programming language
 Multiple programming paradigms
 Object-oriented
 Imperative
 Functional programming
 Procedural
 Dynamic language: Scripting  Non scripting
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4. The language
 Python code can be packaged into standalone
executable programs
 Popular
 open source
 lots of tutorials and online resources
 very active community
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5. Main pitfalls of Python
 Indentation identifies blocks of code
 Case sensitivity
 = is used to assign values
 == is used to test conditions
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6. Python in geoinformatics?
YES!
Thousands of different modules and packages are
available to extend the functionality of Python
containing several ones related to geoinformatics.
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7. ArcGIS
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8. ArcGIS
Arcgisscripting (ArGIS 9.x)
Arcpy (ArcGIS 10.x)
 automate geoprocessing tasks
 manage map documents and layers
 find and fix broken data links
 edit data in feature classes and tables
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9. Creating KML files
XML based language to describe features with geospatial
information
Simple text file
Modul: xml.dom.minidom
Assuming that you are already familiar with reading shape
files or geodatabases you can now write your own function to
export data.
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10. QGIS
 Python Console
The integrated Python console is ideal for scripting. When
the console is started the modules qgis.core and qgis.utils
will be imported automatically.
 Python Plugins
It is possible to create and use Python plugins to enhance
the functionality of QGIS. The plugin installer allows users
to easily fetch, upgrade and remove Python plugins.
 Python Applications
Custom applications can be developed based on QGIS API.
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13. Projections
 Pyproj
 ”wrapper’” around library called PROJ.4
 Class: Proj
longitude, latitude  native map (x,y) coordinates
 Class: Geod
performs various Great Circle distance and angle
calculations
npts() method: calculates
the coordinates of a number
of points spaced equidistantly
along a geodesic line
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14. Projections
Translating UTM location into latitude and longitude
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15. Visualizing geospatial data
 Mapnik toolkit: to build mapping applications

 Heavily used by OpenStreetMap, because it produces
images which are ideal to include in webpages.
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Geospatial data from
PostGIS database,
shapefile, any other
format supported by
GDAL
Clearly rendered
images

16. Analyzing and manipulating geospatial
data
Shapely
package for manipulation and analysis of two-dimensional
geospatial geometries.
Based on the GEOS library.
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17. Conclusion
Do you maybe know additional packages?
There are several packages which support
geoinformatics, and from which I overviewed some,
pointing out how useful is to get to know Python
language.
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