This tutorial focuses on regression-based unmixing of urban land cover from simulated EnMAP imagery. The slide collection provides the theoretical foundation for the tutorial, including general introductions into urban land cover mapping and regression-based unmixing using synthetically mixed training data. The practical provides hands-on training for working with the EnMAP-Box, including a basic introduction into its functionalities and spectral library handling, as well as the regression-based unmixing processing chain.
Urban areas are of significant importance to mankind and our environment. This introduction lesson gives an insight on the characteristics of urban areas and their mapping with remote sensing technologies.
In this lesson the importance of urban footprint mapping is explained, while various SAR features relevant for mapping these urban footprints are given. Moreover, you will learn about the “Global Urban Footprint” project of DLR.
Advanced knowledge about the importance of urban area mapping and the relevant characteristics of urban areas in SAR data are given in this lesson. Moreover, the sensor requirements for accurate urban LC mapping and methodologies for land cover change classification utilizing SAR data are explored.
This module will show the importance of extracting certain urban objects, such as buildings, trees or roads. Moreover, the potential of SAR data for urban object extraction is given.
In this lesson the importance of urban DSM mapping is going to be explained. Therefore, relevant SAR features for the generation of these urban DSMs are given. Moreover, different approaches established in urban DSM mapping from SAR data are introduced.
Synergy between different sensor systems bares the potential for a more holistic analysis for (urban) environments. Advantages and drawbacks of optical remote sensing data and SAR data for urban area mapping are shown. Moreover, synergy effects using multispectral satellite data and SAR information for urban area mapping are explained.
In this tutorial you learn how to monitor the behavior of the Earth’s surface due to underground hard coal mining activities with SAR data. The presentation gives insights in the usage of the software packages ‘NEST’ for data processing and analysis as well as ‘Snaphu’ for the phase unwrapping. The tutorial guides you from the import and preprocessing of the data over the generation and analysis of interferograms to the export of the results to Google Earth.
Anthropogenic activities have manifold influences on the shape and dynamic of the Earth’s surface. In this lesson you learn methods and concepts used to monitor the behavior and extent of deformation phenomena from various sources. Furthermore, SAR interferometry is compared to traditional deformation measurement techniques.
This tutorial will show you the basics of SAR data processing within the program environment of “SNAP”. These basics of SAR data processing include: generation of multi-looked imagery, generation of interferometric coherence, creating an RGB composite and exporting this RGB to Google Earth. Moreover, urban footprint mapping and a change detection analysis based on two urban footprints utilizing Sentinel-1 SAR data is given.
Please make sure to download the sample data as explained in the attached tutorial.