• DocumentCode
    3533901
  • Title

    Forest biomass retrieval from lidar and radar

  • Author

    Sun, G. ; Ranson, K. Jon

  • Author_Institution
    Univ. of Maryland, College Park, MD, USA
  • Volume
    5
  • fYear
    2009
  • fDate
    12-17 July 2009
  • Abstract
    The use of lidar and radar instruments to measure forest structure attributes such as height and biomass are being considered for future Earth Observation satellite missions. Combined use of lidar sampling data and complete global coverage of L-band SAR data for vegetation 3D structure mapping requires some new data processing and fusion technologies. In this study, the potential information on biomass from a lidar waveform and the required lidar samples for reliable biomass estimation were investigated using both model and real data. First, the Laser Vegetation Imaging Sensor (LVIS) data was used to generate an above-ground biomass map of the study site. The map was considered to represent the true biomass of the area. Then random samples were taken from the biomass image and the correlation between biomass and co-located SAR signature was studied. The proper model was used to extend the biomass from lidar samples into all forested areas in the study area. The new biomass map was compared with the original biomass map derived from LVIS data. The results showed the potential of the combined use of lidar samples and radar imagery for forest biomass mapping.
  • Keywords
    forestry; geophysical signal processing; optical radar; remote sensing by laser beam; remote sensing by radar; sensor fusion; vegetation mapping; Earth observation satellite missions; L-band SAR data; LVIS data; Laser Vegetation Imaging Sensor; Maine; USA; data fusion; data processing; forest biomass retrieval; forest height; forest structure measurement; lidar sampling data; synthetic aperture radar; vegetation 3D structure mapping; Artificial satellites; Biomass; Data processing; Instruments; L-band; Laser radar; Radar measurements; Sampling methods; Spaceborne radar; Vegetation mapping; DESDynI; biomass; forest; lidar; radar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009
  • Conference_Location
    Cape Town
  • Print_ISBN
    978-1-4244-3394-0
  • Electronic_ISBN
    978-1-4244-3395-7
  • Type

    conf

  • DOI
    10.1109/IGARSS.2009.5417671
  • Filename
    5417671