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

Field Work Course 2019

Field Work Course 2019

Within the EAGLE program many Earth Observation applications and techniques are introduced and practically executed with quite some computer work. However, remote sensing research also requires a sound understanding of the study area. Field work is therefore a crucial...

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EAGLE visit DLR-EOC

EAGLE visit DLR-EOC

Our EAGLEs in 2018 visited the German Aerospace Center, namely the Earth Observation Center, close to Munich. Various topics were presented by DLR scientist and the EAGLEs hat the chance to discuss various topics in small groups with individual scientists.

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EAGLE Internships

EAGLE Internships

On Monday, 24th of September, at 1pm the following internship reports will be presented: Bharath: "Installation and Characterization of an imaging Spectrometer for the UAV-based remote sensing" Johannes: "Crop classification based on S1/S2 in...

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