ALBERT

Description: A flight mission of NASA GSFC's Laser Vegetation Imaging Sensor (LVIS) is planned for June-August 2003 in the Amazon region of Brazil. The goal of this flight mission is to map the vegetation height and structure and ground topography of a large area of the Amazon. This data will be used to produce maps of true ground topography, vegetation height, and estimated above-ground biomass and for comparison with and potential calibration of Synthetic Aperture Radar (SAR) data. Approximately 15,000 sq. km covering various regions of the Amazon will be mapped. The LVIS sensor has the unique ability to accurately sense the ground topography beneath even the densest of forest canopies. This is achieved by using a high signal-to-noise laser altimeter to detect the very weak reflection from the ground that is available only through small gaps in between leaves and between tree canopies. Often the amount of ground signal is 1% or less of the total returned echo. Once the ground elevation is identified, that is used as the reference surface from which we measure the vertical height and structure of the vegetation. Test data over tropical forests have shown excellent correlation between LVIS measurements and biomass, basal area, stem density, ground topography, and canopy height. Examples of laser altimetry data over forests and the relationships to biophysical parameters will be shown. Also, recent advances in the LVIS instrument will be discussed.

Description: The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized forest AGB sampling errors by 15 - 38%. Furthermore, spaceborne global scale accuracy requirements were achieved. At least 80% of the grid cells at 100m, 250m, 500m, and 1km grid levels met AGB density accuracy requirements using a combination of passive optical and SAR along with machine learning methods to predict vegetation structure metrics for forested areas without LiDAR samples. Finally, using either passive optical or SAR, accuracy requirements were met at the 500m and 250m grid level, respectively.

Description: The GRACE mission has been in orbit now for three years and now regularly produces snapshots of the Earth s gravity field on a monthly basis. The convenient standard approach has been to perform global solutions in spherical harmonics. Alternative local representations of mass variations using mascons show great promise and offer advantages in terms of computational efficiency, minimization of problems due to aliasing, and increased temporal resolution. In this paper, we discuss the results of processing the GRACE KBRR data from March 2003 through August 2005 to produce solutions for GRACE mass variations over mid-latitude and equatorial regions, such as South America, India and the United States, and over the polar regions (Antarctica and Greenland), with a focus on the methodology. We describe in particular mascon solutions developed on regular 4 degree x 4 degree grids, and those tailored specifically to drainage basins over these regions.

Description: Although temperate mountain glaciers comprise less than 1% of the glacier-covered area on Earth, they are important because they appear to be melting rapidly under present climatic conditions and, therefore, make significant contributions to rising sea level. In this study, we use ICESat observations made in the last 1.5 years of southern Alaska glaciers to estimate ice elevation profiles, ice surface slopes and roughness, and bi-annual and/or annual ice elevation changes. We report initial results from the near coastal region between Yakutat Bay and Cape Suckling that includes the Malaspina and Bering Glaciers. We show and interpret ice elevations changes across the lower reaches of the Bagley Ice Valley for the period between October 2003 and May 2004. In addition, we use off-nadir pointing observations to reference tracks over the Bering and Malaspina Glaciers in order to estimate annual ice elevation change. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Shuttle Radar Topography Mission (SRTM) derived DEMs are used to estimate across track regional slopes between ICESat data acquisitions. Although the distribution and quantity of ICESat elevation profiles with multiple, exact repeat data is currently limited in Alaska, individual ICESat data tracks, provide an accurate reference surface for comparison to other elevation data (e.g. ASTER and SRTM X- and C-band derived DEMs). Specifically we report the elevation change over the Malaspina Glacier's piedmont lobe between a DEM derived from SRTM C-band data acquired in Feb. 2000 and ICESat Laser #2b data from Feb.-March 2004. We also report use of ICESat elevation data to enhance ASTER derived absolute DEMs. Mountain glaciers generally have rougher surfaces and steeper regional slopes than the ice sheets for which the ICESat design was optimized. Therefore, rather than averaging ICESat observations over large regions or relying on crossovers, we are working with well-located ICESat footprint returns to estimate glacier ice elevations and surface characteristics. Additional information is included in the original extended abstract.