Volume 9 Issue 2
May  2020
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CHEN Hao, HILL David A., WHITE Joanne C., et al. Evaluating the impacts of using different digital surface models to estimate forest height with TanDEM-X interferometric coherence data[J]. Journal of Radars, 2020, 9(2): 386–398. DOI: 10.12000/JR20009
Citation: CHEN Hao, HILL David A., WHITE Joanne C., et al. Evaluating the impacts of using different digital surface models to estimate forest height with TanDEM-X interferometric coherence data[J]. Journal of Radars, 2020, 9(2): 386–398. DOI: 10.12000/JR20009

Evaluating the Impacts of Using Different Digital Surface Models to Estimate Forest Height with TanDEM-X Interferometric Coherence Data (in English)

doi: 10.12000/JR20009
Funds:  This work was supported by Natural Resources Canada and the Canadian Space Agency under Multisource Biomass GRIP and by the German Aerospace Centre for provision of TanDEM-X data
More Information
  • Author Bio:

    CHEN Hao received the B.Sc. degree in electrical engineering from the University of Beijing Iron and Steel Technology, Beijing, China, in 1983, and the M.Sc. degree in computer science from the University of Victoria, Victoria, BC, Canada, in 2004. He is a senior physical scientist with the Canadian Forest Service (CFS), Natural Resources Canada, working at the Pacific Forestry Centre, Victoria. Since joining the CFS in 2000, his work has focused on radar polarimetry and interferometry for forest applications and he has participated in many national and international radar remote sensing projects as a principal investigator or co-principal investigator. Mr. Chen has more than 20 publications and given presentations to national and international conferences and organizations

    HILL David A. received the B.Sc. degree in Physical Geography from the University of Victoria, Victoria, BC, Canada, in 1983 and a Diploma in Remote Sensing from the College of Geographic Sciences, Lawrencetown, NS, Canada, in 1988. In 1997, he joined the Canadian Forest Service as a Remote Sensing Analyst, where research focused on remote sensing for forest inventory applications using data from Canada’s Radarsat-1/2 satellites, CCRS Convair-580 airborne SAR/INSAR, Germany’s TerraSAR-X/Tandem-X, Japan’s ALOS-1/2, and Landsat 3-8. Mr. Hill currently works on assessment of current and future satellite, airborne, and terrestrial sensors for Canada’s National Forest Inventory Program

    WHITE Joanne C. received the B.Sc. and the M.Sc. degree in geography from the University of Victoria, Victoria, Canada, in 1994 and 1998 respectively, and the D.Sc. degree from the University of Helsinki, Helsinki, Finland, in 2019. She is a research scientist with the Canadian Forest Service, Natural Resources Canada, in Victoria. Her research focuses on the synergistic use of optical time series and 3D remotely sensed data (LiDAR and digital aerial photogrammetry) for large-area forest inventory and monitoring applications. Specializing in the development of novel approaches to characterize forest dynamics with remotely sensed data, she has co-authored more than 150 peer-reviewed scientific publications. For a complete list of publications and access to reprints, please visit the Canadian Forest Service publications site: http://cfs.nrcan.gc.ca/authors/read/19532

    CLOUDE Shane R. received the B.Sc. (Hons.) degree from the University of Dundee, U.K., in 1981, and the Ph.D. degree from the University of Birmingham, U.K., in 1987. He was then a Radar Scientist with the Royal Signals and Radar Establishment, Great Malvern, U.K. Following this, he held teaching and research posts at the University of Dundee, U.K., the University of York, U.K. and the University of Nantes, France, before taking on his present role in 2001. He is now Senior Scientist with AEL Consultants, undertaking research on a range of topics associated with radar and optics. His main research interests are in polarization effects in electromagnetic scattering and their applications in radar and optical remote sensing. He is the author of 2 books, 10 book chapters, 42 journal publications, and over 180 international conference and workshop papers. Dr. Cloude is a Fellow of the Alexander von Humboldt Foundation in Germany, and has held Honorary Professorships and Chairs at the Universities of Dundee and York, UK, the Macaulay Land Use Research Institute in Aberdeen, Scotland, and the University of Adelaide, Australia

  • Corresponding author: Hao Chen. E-mail: hao.chen@canada.ca
  • Received Date: 2020-02-07
  • Rev Recd Date: 2020-03-26
  • Available Online: 2020-04-23
  • Publish Date: 2020-04-01
  • In our previous studies, we demonstrated the usefulness of TanDEM-X interferometric bistatic mode with single polarization to obtain forest heights for the purposes of large area mapping. A key feature of our approach has been the use of a simplified Random Volume Over Ground (RVOG) model that locally estimates forest height. The model takes TanDEM-X interferometric coherence amplitude as an input and uses an external Digital Surface Model (DSM) to account for local slope variations due to terrain topography in order to achieve accurate forest height estimation. The selection of DSM for use as a local slope reference is essential, as an inaccurate DSM will result in less accurate terrain-correction and forest height estimation. In this paper, we assessed TanDEM-X height estimates associated with scale variations in different DSMs used in the model over a remote sensing supersite in Petawawa, Canada. The DSMs used for assessments and comparisons included ASTER GDEM, ALOS GDSM, airborne DRAPE DSM, Canadian DSM and TanDEM-X DSM. Airborne Laser Scanning (ALS) data were used as reference for terrain slope and forest height comparisons. The results showed that, with the exception of the ASTER GDEM, all DSMs were sufficiently accurate for the simplified RVOG model to provide a satisfactory estimate of stand-level forest height. When compared to the ALS 95th height percentile, the modeled forest heights had R2 values greater than 80% and Root-Mean-Square Errors (RMSE) less than 2 m. For a close similarity in slope estimation with the ALS reference, coverage across Canada and open data access, the 0.75 arc-second (20 m) resolution Canadian DSM was selected as a preferred choice for the simplified RVOG model to provide TanDEM-X height estimation in Canada.

     

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