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Use of Segmentation for Combining Radar Backscatter, InSAR, and Lidar Measurements to Determine Vegetation 3D Structure and Biomass from Space
Paul
Robert
Siqueira, University of Massachusetts, siqueira@ecs.umass.edu
(Presenter)
Caitlin
Dickinson, University of Massachusetts, dickinson@ecs.umass.edu
Razi
Ahmed, University of Massachusetts, rahmed@ecs.umass.edu
Scott
Hensley, JPL, scott.hensley@jpl.nasa.gov
Kathleen
Bergen, University of Michigan, kbergen@umich.edu
Richard
Maxwell
Lucus, University of Aberystwyth, rml@aber.ac.uk
Yang
Lei, University of Massachusetts, ylei@ecs.umass.edu
To help meet the needs of NASA’s planned DESDynI-R mission, we have been investigating the use of segmentation algorithms to make best use of the mapping capabilities of synthetic aperture radar and the fundamental structural sensitivity of lidar, to make large-scale and regional estimates of forest biomass and vegetation structure. In order to achieve this goal, we have studied three sites in detail: 1.) The Harvard Forest, 2.) The Howland Forest , and 3.) The Injune region in Eastern Australia. The availability of ground validation resources for these sites is extensive, with airborne and spaceborne SAR and lidar available. The sites have been singled out for investigation because of the diversity of forest structure and their relatively flat terrain. Flat terrain is an important characteristic for establishing a fundamental sensitivity between the remote sensing observables and the forest physical characteristics of interest.
Segmentation has been used for this work in order to aggregate regions of like-response to the SAR observations, and then to relate the regions to structural observations made by lidar. By using NASA’s UAVSAR and LVIS high resolution assets for prototyping, it has been possible to separate the effects associated with inherent instrumental error sources (e.g. radar speckle) from natural variations in the target characteristics. Using the extensive observations that have been collected by the Japanese Aerospace Exploration Agency’s ALOS/PALSAR, it has been possible to extrapolate how these results could be applied to a spaceborne instrument such as DESDynI. Further, by examining the different forest types at Injune, Howland and Harvard Forests, our team has been able to investigate in which structural and biomass regimes such a method could be successfully applied, and which not.
Additional work will also be shown regarding the development of large-scale mapping of forest stand height over the state of Maine using interfeormetric coherence derived from ALOS PALSAR data collected in 2007 and 2010. These heights are compared with LVIS RH100 metrics for the Howland and Penobscott forests in central Maine. Results such as this provide a demonstration of how interferometric correlation from a repeat-pass satellite mission (such as DESDynI-R) can be used for characterizing forest stand height over large geographic areas.
Presentation Type: Poster
Session: Poster Session 2-A
(Wed 11:00 AM)
Associated Project(s):
Poster Location ID: 77
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