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Research article - Peer-reviewed, 2014

Forest Variable Estimation Using Radargrammetric Processing of TerraSAR-X Images in Boreal Forests

Persson, Henrik; Fransson, Johan

Abstract

The last decade has seen launches of radar satellite missions operating in X-band with the sensors acquiring images with spatial resolutions on the order of 1 m. This study uses digital surface models (DSMs) extracted from stereo synthetic aperture radar images and a reference airborne laser scanning digital terrain model to calculate the above-ground biomass and tree height. The resulting values are compared to in situ data. Analyses were undertaken at the Swedish test sites Krycklan (64 degrees N) and Remningstorp (58 degrees N), which have different site conditions. The results showed that, for 459 forest stands in Remningstorp, biomass estimation at the stand level could be performed with 22.9% relative root mean square error, while the height estimation showed 9.4%. Many factors influenced the results and it was found that the topography has a significant effect on the generated DSMs and should therefore be taken into consideration when the stand level mean slope is above four degrees. Different tree species did not have a major effect on the models during leaf-on conditions. Moreover, correct estimation within young forest stands was problematic. The intersection angles resulting in the best results were in the range 8-16 degrees. Based on the results in this study, radargrammetry appears to be a promising potential remote sensing technique for future forest applications.

Keywords

SAR; X-band; TerraSAR-X; forestry; stereogrammetric methods; radargrammetry

Published in

Remote Sensing
2014, volume: 6, number: 3, pages: 2084-2107
Publisher: MDPI AG

Authors' information

Swedish University of Agricultural Sciences, Department of Forest Resource Management
Fransson, Johan
Swedish University of Agricultural Sciences, Department of Forest Resource Management

Associated SLU-program

Remningstorp

UKÄ Subject classification

Other Engineering and Technologies not elsewhere specified
Forest Science
Signal Processing

Publication Identifiers

DOI: https://doi.org/10.3390/rs6032084

URI (permanent link to this page)

https://res.slu.se/id/publ/65124