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Carbon Cycle & Ecosystems

The overall goal of the proposed research is to investigate technological options and data fusion algorithms for ecosystem structure measurements from the proposed NASA DESDynI mission. The experiments described in this proposal are possible given the timely confluence of highly relevant remote sensing and ground reference data sets. Through collaboration with the leading geospatial information company in Chile, Digimapas Chile, we will have access to 75,000 km2 of 1-meter resolution full-waveform small footprint lidar (SFPL) data and 0.5 m resolution digital orthophoto imagery covering the commercial forests of Arauco, one of the largest cellulose producers in Latin America. Arauco is a collaborator on this proposal and will provide access to relevant timber survey data, which is regularly acquired across their land holdings. The SFPL acquisitions commenced in October of 2006 and are scheduled to be completed in mid-2008. The area covered with the SFPL data has also been mapped by the ALOS/PALSAR at several resolutions and acquisition modes. In addition, multi-spectral optical imagery from ALOS/AVNIR-2 and CBERS-2, as well as lidar data from ICESat/GLAS are available for use. All remote sensing data will have been acquired during a very narrow time frame spanning less than two years. Given the size of the study area (75,000 km2), the availability of very high resolution lidar and optical imagery, and the dense network of field reference data, very realistic simulations of spaceborne lidar sampling design covering multi-scene radar and optical imagery can be conducted. In turn, these simulations provide an ideal framework within which to test various approaches to DESDynI lidar/radar data fusion leading to canopy height and aboveground biomass retrievals. Data fusion will be accomplished using randomForest, a state-of-the art statistical modeling approach based on ensemble machine learning techniques. Four specific objectives are proposed to achieve this overall goal: (1) Evaluate multi-sensor data-fusion strategies for canopy height (CH) and aboveground biomass (AB) retrieval. (2) Study the effect of lidar sampling density on the accuracy of CH and AB predictions. (3) Study the effect of lidar footprint size on the accuracy of CH and AB predictions. (4) Study the effect of radar resolution on the accuracy of CH and AB predictions. One of several key DESDynI mission science questions involves the performance of off-nadir multi-beam lidar data for CH and AB retrieval. As part of the proposed research, approximately 300 km2 of Arauco forest holdings will be remapped with Digimapas Chile’s SFPL at off-nadir angles of up to 10o. This acquisition will facilitate an investigation into how the off-nadir pointing affects the lidar waveforms and hence the accuracy of CH and AB predictions. The proposed work addresses the following research needs identified in the DESDynI Workshop Report (2007): (1) studies to develop and evaluate algorithms and analysis strategies that address the merger of lidar and radar measurements (data fusion), and (2) studies to quantify the effects of sampling design and measurement accuracy, frequency, and resolution on the ability to improve our quantitative knowledge of global carbon dynamics and ecosystem structure and function. This focused study was designed as a two-year project so as to make results available as early as possible for the purposes of informing the development of the DESDynI mission concept.

Project PI: Josef Kellndorfer/The Woods Hole Research Center

Woods Hole Research Center 149 Woods Hole Road Falmouth, MA 02540-1644

Phone: 508-444-1540

Fax: 508-444-1840

Eamil: josefk@whrc.org

http://www.whrc.org/about/cvs/jkellndorfer.html

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Started: Aug 09, 2010

Last Activity: Dec 10, 2010

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