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CD-37 Abstract

Spatially-explicit Estimates of Forest Biomass in the Amazon Basin using MODIS and the Geoscience Laser Altimeter System

Michael Lefsky — Colorado State University (US-PI)

Lidar remote sensing has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. We propose to use lidar waveforms from the Geoscience Laser Altimeter System (GLAS) to estimate canopy height and aboveground forest carbon storage for each GLAS waveform in the Amazon basin and to combine those point estimates with images from the MODIS sensor to develop spatially continuous datasets. We will compare the new biomass estimates with spatially explicit data layers from previous studies in the region and use an existing bookkeeping C flux model to evaluate the sensitivity of C flux estimates associated with land cover change in the region to the new biomass estimates.



Despite engineering problems with the GLAS sensor, over 300 million ICESat waveforms have been collected, with nearly 1 million currently available for the Amazon basin. With no other global lidar data collection scheduled for the near future, GLAS data represents a unique source of information on regional-to-global scale forest canopy height and aboveground biomass. GLAS waveforms have an approximate footprint diameter of 70 m and have been generated at 170 m intervals for tracks about 30 km apart at the equator. Processing of GLAS data to create reliable estimates of forest height is complicated by elements of sensor design related to its primary mission—the topographic mapping of the ice sheets of Greenland and Antarctica – and on-going issues associated with instrument performance. Our work to date on the problem has resulted in an algorithm that uses topography from 90 m Shuttle Radar Topography Mission (SRTM) digital elevation models to correct for ground slope effects and create unbiased estimates of stand height. To achieve spatially continuous coverages of biomass, we will employ both multi-phase sampling to create statistical summaries of lidar-estimated attributes over the study region, and statistical data fusion with MODIS data. Comparisons with existing biomass estimates will include surfaces derived from inventory data, interpolations based on climatic gradients and ecosystem carbon models driven by remote sensing data. An evaluation of the sensitivity of the regional carbon flux associated with land cover change to the new biomass estimates will use the Woods Hole Research Center Bookkeeping model. Besides contributing towards the scaling of biomass related field measurements, the mapping the canopy height and biomass of the Amazon has other practical and theoretical justifications, including the testing of various regional carbon models and supplying aerodynamic roughness to climate models.



The proposed work addresses two major issues that are directly relevant to the carbon storage and exchange component of LBA: (1) are the undisturbed ecosystems of Amazonia functioning as a net carbon sink? and (2) how much carbon is lost as a result of land cover and land use changes such as the clearing of forest for agriculture and selective logging? (LBA Science Planning Group 1996). It will directly contribute to ESE’s “Carbon Cycle, Ecosystems and Biogeochemistry” focus and to NASA’s role in LBA. This proposal demonstrates the feasibility of the ESE identified need for a capability to measure “Global vegetation 3-D structure, biomass and disturbance”. The proposed work falls within the NASA objective, “Conduct a program of research and technology development to advance Earth observation from space, improve scientific understanding, and demonstrate new technologies that can improve Earth observation systems”.



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