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High-resolution forest mapping from TanDEM-X interferometric data exploiting nonlocal filtering

Martone, Michele and Sica, Francescopaolo and Gonzalez, Carolina and Bueso Bello, Jose Luis and Valdo, Paolo and Rizzoli, Paola (2018) High-resolution forest mapping from TanDEM-X interferometric data exploiting nonlocal filtering. Remote Sensing, pp. 1-17. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs10091477. ISSN 2072-4292.

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Abstract

In this paper, we discuss the potential and limitations of high-resolution single-pass interferometric synthetic aperture radar (InSAR) data for forest mapping. In particular, we present forest/non-forest classification mosaics of the State of Pennsylvania, USA, generated using TanDEM-X data at ground resolutions down to 6 m. The investigated data set was acquired between 2011 in bistatic stripmap single polarization (HH) mode. Among the different factors affecting the Quality of InSAR data, the so-called volume correlation factor quantifies the coherence loss due to volume scattering, which typically occurs in the presence of vegetation, and is a very sensitive indicator for the discrimination of forested from non-forested areas. For this reason, it has been chosen as input observable for performing the classification. In this framework, both standard boxcar and nonlocal filtering methods have been considered for the estimation of the volume correlation factor. The resulting forest/non-forest mosaics have been validated using an accurate vegetation map of the region derived from Lidar-Optic data as external independent reference. Thanks to their outstanding performance in terms of noise reduction, together with spatial features preservation, nonlocal filters show a level of agreement of about 80.5% and we observed a systematic improvement in terms of accuracy with respect to the boxcar filtering at the same resolution of about 4.5 percent points. This approach is therefore of primary importance to achieve a reliable classification at such fine resolution. Finally, the high-resolution forest/non-forest classification product of the State of Pennsylvania presented in this paper demonstrates once again the outstanding capabilities of the TanDEM-X system for a wide spectrum of commercial services and scientific applications in the field of the biosphere.

Item URL in elib:https://elib.dlr.de/122494/
Document Type:Article
Title:High-resolution forest mapping from TanDEM-X interferometric data exploiting nonlocal filtering
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Martone, MicheleUNSPECIFIEDhttps://orcid.org/0000-0002-4601-6599UNSPECIFIED
Sica, FrancescopaoloUNSPECIFIEDhttps://orcid.org/0000-0003-1593-1492UNSPECIFIED
Gonzalez, CarolinaUNSPECIFIEDhttps://orcid.org/0000-0002-9340-1887UNSPECIFIED
Bueso Bello, Jose LuisUNSPECIFIEDhttps://orcid.org/0000-0003-3464-2186UNSPECIFIED
Valdo, PaoloUNSPECIFIEDhttps://orcid.org/0000-0003-0641-5808UNSPECIFIED
Rizzoli, PaolaUNSPECIFIEDhttps://orcid.org/0000-0001-9118-2732UNSPECIFIED
Date:16 September 2018
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI:10.3390/rs10091477
Page Range:pp. 1-17
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:Published
Keywords:TanDEM-X mission, forest classification, SAR interferometry (InSAR), nonlocal filtering
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Projekt TanDEM-X (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > Spaceborne SAR Systems
Deposited By: Martone, Michele
Deposited On:25 Oct 2018 15:48
Last Modified:08 Nov 2023 14:15

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