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**Harvard**

Soja, M., Persson, H. och Ulander, L. (2015) *Detection of Forest Change and Robust Estimation of Forest Height from Two-Level Model Inversion of Multi-Temporal Single-Pass InSAR Data*.

** BibTeX **

@conference{

Soja2015,

author={Soja, Maciej J. and Persson, Henrik and Ulander, Lars M. H.},

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

booktitle={IEEE International Geoscience and Remote Sensing Symposium},

isbn={978-1-4799-7929-5},

pages={3886-3889},

abstract={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.},

year={2015},

keywords={canopy density; forest height; clear-cut; two-level model (TLM); TanDEM-X},

}

** RefWorks **

RT Conference Proceedings

SR Electronic

ID 226249

A1 Soja, Maciej J.

A1 Persson, Henrik

A1 Ulander, Lars M. H.

T1 Detection of Forest Change and Robust Estimation of Forest Height from Two-Level Model Inversion of Multi-Temporal Single-Pass InSAR Data

YR 2015

T2 IEEE International Geoscience and Remote Sensing Symposium

SN 978-1-4799-7929-5

SP 3886

OP 3889

AB 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.

LA eng

DO 10.1109/IGARSS.2015.7326673

LK http://dx.doi.org/10.1109/IGARSS.2015.7326673

LK http://publications.lib.chalmers.se/records/fulltext/226249/local_226249.pdf

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