FOREST BIOMASS MAPPING FROM PRISM TRIPLET, PALSAR AND LANDSAT DATA

The loss of sensitivity at higher biomass levels is a common problem in biomass mapping using optical multi-spectral data or radar backscattering data due to the lack of information on canopy vertical structure. Studies have shown that adding implicit information of forest vertical structure improves the performance of forest biomass mapping from optical reflectance and radar backscattering data. LiDAR, InSAR and stereo imager are the data sources for obtaining forest structural information. The potential of providing information on forest vertical structure by stereoscopic imagery data has drawn attention recently due to the availability of high-resolution digital stereo imaging from space and the advances of digital stereo image processing software. The Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observation Satellite (ALOS) has acquired multiple global coverage from June 2006 to April 2011 providing a good data source for regional/global forest studies.

In this study, five PRISM triplets acquired on June 14, 2008, August 19 and September 5, 2009; PALSAR dual-pol images acquired on July 12, 2008 and August 30, 2009; and LANDSAT 5 TM images acquired on September 5, 2009 and the field plot data collected in 2009 and 2010 were used to map forest biomass at 50m pixel in an area of about 4000 km²in Maine, USA ( 45.2 deg N 68.6 deg W). PRISM triplets were used to generate point cloud data at 2m pixel first and then the average height of points above NED (National Elevation Dataset) within a 50m by 50m pixel was calculated. Five images were mosaicked and used as canopy height information in the biomass estimation along with the PALSAR HH, HV radar backscattering and optical reflectance vegetation indices from L-5 TM data. A small portion of this region was covered by the Land Vegetation and Ice Sensor (LVIS) in 2009. The biomass maps from the LVIS data was used to evaluate the results from combined use of PRISM, PALSAR and LANDSAT data.

The results show that the canopy height index from PRISM stereo images significantly improves the biomass mapping accuracy and extends the saturation level of biomass, and results in a biomass map comparable with those generated from LVIS data.