Next Article in Journal
Previous Article in Journal
Remote Sens. 2014, 6(3), 2084-2107; doi:10.3390/rs6032084
Article

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

*  and
Received: 23 December 2013; in revised form: 17 February 2014 / Accepted: 24 February 2014 / Published: 7 March 2014
View Full-Text   |   Download PDF [1812 KB, updated 19 June 2014; original version uploaded 19 June 2014]
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°N) and Remningstorp (58°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°. Based on the results in this study, radargrammetry appears to be a promising potential remote sensing technique for future forest applications.
Keywords: radargrammetry; forestry; X-band; stereogrammetric methods; SAR; TerraSAR-X radargrammetry; forestry; X-band; stereogrammetric methods; SAR; TerraSAR-X
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Persson, H.; Fransson, J.E. Forest Variable Estimation Using Radargrammetric Processing of TerraSAR-X Images in Boreal Forests. Remote Sens. 2014, 6, 2084-2107.

AMA Style

Persson H, Fransson JE. Forest Variable Estimation Using Radargrammetric Processing of TerraSAR-X Images in Boreal Forests. Remote Sensing. 2014; 6(3):2084-2107.

Chicago/Turabian Style

Persson, Henrik; Fransson, Johan E. 2014. "Forest Variable Estimation Using Radargrammetric Processing of TerraSAR-X Images in Boreal Forests." Remote Sens. 6, no. 3: 2084-2107.


Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert