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Proceedings Article

Using TanDEM data for forest height estimation and change detection

[+] Author Affiliations
Antje Thiele, Stefan Hinz

Karlsruhe Institute of Technology (Germany)

Clémence Dubois

Federal Institute for Geosciences and Natural Resources (Germany)

Markus Boldt

Fraunhofer IOSB (Germany)

Proc. SPIE 10005, Earth Resources and Environmental Remote Sensing/GIS Applications VII, 1000514 (October 18, 2016); doi:10.1117/12.2241795
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From Conference Volume 10005

  • Earth Resources and Environmental Remote Sensing/GIS Applications VII
  • Ulrich Michel; Karsten Schulz; Manfred Ehlers; Konstantinos G. Nikolakopoulos; Daniel Civco
  • Edinburgh, United Kingdom | September 26, 2016

abstract

Mapping of forest coverage and forest changes became an increasing issue due to deforestation and forest degradation. Moreover, the estimation of related indicators such as carbon reduction, biomass and wood capacity is of large interest for industry and politics. As forest height is an important contributing parameter for these indicators, the region-wide estimation of forest heights is an essential step. This article investigates the accuracy potential of forest height estimation that can be reached by the current configuration of the two SAR satellites TerraSAR-X and TanDEM-X. Depending on the chosen acquisition mode and flight geometry, products of different quality can be achieved. Eight InSAR data sets showing different characteristics in geometric resolution, length of baseline, and mapping time, are processed and analyzed. To enable a thorough evaluation of the estimated heights, first-pulse LIDAR point clouds and aerial ortho-images are used as reference data. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Antje Thiele ; Clémence Dubois ; Markus Boldt and Stefan Hinz
" Using TanDEM data for forest height estimation and change detection ", Proc. SPIE 10005, Earth Resources and Environmental Remote Sensing/GIS Applications VII, 1000514 (October 18, 2016); doi:10.1117/12.2241795; http://dx.doi.org/10.1117/12.2241795


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