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Detection of Forest Change and Robust Estimation of Forest Height from Two-Level Model Inversion of Multi-Temporal Single-Pass InSAR Data

Maciej J. Soja (Institutionen för rymd- och geovetenskap, Radarfjärranalys) ; Henrik Persson ; Lars M. H. Ulander (Institutionen för rymd- och geovetenskap, Radarfjärranalys)
IEEE International Geoscience and Remote Sensing Symposium (2153-6996). p. 3886-3889. (2015)
[Konferensbidrag, refereegranskat]

In this paper, forest change detection and forest height estimation are studied using two-level model (TLM) inversion of multi-temporal TanDEM-X (TDM) data. Parameter Delta h, describing the distance between ground and vegetation levels, is kept constant for all acquisitions, whereas parameter mu, the area-weighted backscatter ratio, changes with acquisition. Two multi-temporal sets of TDM data, acquired over the hemi-boreal test site Remningstorp, situated in southern Sweden, are studied: one consisting of 12 acquisitions made in the summers of 2011, 2012, 2013, and 2014 with heights-of-ambiguity (HOAs) between 32 m and 63 m, and one consisting of 33 acquisitions made between August 2013 and August 2014 with HOAs between 38 m and 195 m. The first dataset is used to show that commercial thinnings and clear-cuts can be detected by studying the canopy density estimate eta(0) = 1 = (1 + mu). The second dataset is used to show that seasonal change can be observed in eta(0) for deciduous plots, but not for coniferous plots. Moreover, it is shown that 1.3 Delta h is a good estimate of the basal area-weighted (Lorey's) height, with a correlation coefficient equal to 0.98 and a root-mean-square error of 0.9 m.

Nyckelord: canopy density; forest height; clear-cut; two-level model (TLM); TanDEM-X

Denna post skapades 2015-11-24. Senast ändrad 2016-05-24.
CPL Pubid: 226249


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Institutioner (Chalmers)

Institutionen för rymd- och geovetenskap, Radarfjärranalys


Hållbar utveckling

Chalmers infrastruktur