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Reconstruction of Individual Trees from Multi-Aspect TomoSAR Data

Schmitt, Michael and Shahzad, Muhammad and Zhu, Xiao Xiang (2015) Reconstruction of Individual Trees from Multi-Aspect TomoSAR Data. Remote Sensing of Environment, 165, pp. 175-185. Elsevier. DOI: 10.1016/j.rse.2015.05.012 ISSN 0034-4257

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Official URL: http://www.sciencedirect.com/science/article/pii/S0034425715300110


The localization and reconstruction of individual trees as well as the extraction of their geometrical parameters is an important field of research in both forestry and remote sensing. While the current state-of-the-art mostly focuses on the exploitation of optical imagery and airborne LiDAR data, modern SAR sensors have not yet met the interest of the research community in that regard. This paper presents a full prototypical processing chain for the reconstruction of individual deciduous trees: First, single-pass multibaseline InSAR data acquired from multiple aspect angles are used for the generation of a layover- and shadow-free 3D point cloud by tomographic SAR processing. The resulting point cloud is then segmented by supervised mean shift clustering, before ellipsoid models are fitted to the points of each cluster. From these 3D ellipsoids the relevant geometrical tree parameters are extracted. Evaluation with respect to helicopter-borne LiDAR data and a manually derived reference dataset prove that almost 86% of all trees are successfully localized, thus providing a promising perspective for further research towards individual tree recognition from SAR data.

Item URL in elib:https://elib.dlr.de/94511/
Document Type:Article
Title:Reconstruction of Individual Trees from Multi-Aspect TomoSAR Data
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Schmitt, Michaelm.schmitt (at) tum.deUNSPECIFIED
Shahzad, Muhammadmuhammad.shahzad (at) bv.tum.deUNSPECIFIED
Journal or Publication Title:Remote Sensing of Environment
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1016/j.rse.2015.05.012
Page Range:pp. 175-185
Keywords:Synthetic Aperture Radar (SAR), Tomography, Trees, Reconstruction
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Shahzad, Muhammad
Deposited On:12 Jan 2015 13:28
Last Modified:17 Dec 2015 16:22

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