Spatial Python for Remote Sensing

Lecturer

Stephen Hill

ECTS

5 ECTS

 

Aim

In this course we will elaborate large and complex workflows dealing with the analysis and handling of big data using Python. Moreover, we will try to develop a fully automated processing chain in Python for landcover mapping starting with the download of Landsat data, preprocessing, classification and building up a spatial database that enables GIS functionality over large datasets for further analysis.

 

Content

We will start with the basics of Python programming language and quickly evolve towards image processing techniques with packages such as scipy, numpy, scikit-learn, scikit-image and gdal. We will also focus on arcpy for ESRI software products which allows for a convenient and powerful automatization of spatial analysis functions.

 

General Course News and Updates

Spatial Python block course

Last week Steven Hill and Thorsten Dahms gave a course that introduced EAGLE students to Python-based spatial data analysis. The advantages and challenges of different python libraries, data sets and methods were covered in hands-on exercises and also discussed...

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Remote Sensing in Ecology

The EAGLE course "Remote Sensing in Biodiversity and Conservation Science" took place in the last week of the summer term at the field research station in Fabrik Schleichach, Steigerwald. 20 biology and EAGLE students worked and lived together for one week and...

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