HR: 17:15h
AN: B24B-06    [Abstracts]
TI: Hyperspectral Study of the Arctic Tundra Ecosystem Using an Automated Robotic Cart System
AU: * Goswami, S
EM: sgoswami2@miners.utep.edu
AF: University of Texas at El Paso, 500 West University Ave, El Paso, TX 79968, United States
AU: Gamon, J A
EM: jgamon@gmail.com
AF: California State University, 5151 State University Dr., Los Angeles, CA 90032, United States
AU: Houser, P
EM: pihouser@miners.utep.edu
AF: University of Texas at El Paso, 500 West University Ave, El Paso, TX 79968, United States
AU: Matharasi, K
EM: kuldeep22011984@gmail.com
AF: University of Texas at El Paso, 500 West University Ave, El Paso, TX 79968, United States
AU: Tweedie, C E
EM: ctweedies@utep.edu
AF: University of Texas at El Paso, 500 West University Ave, El Paso, TX 79968, United States
AB: Our study in the NSF Biocomplexity project is carried on by collecting spectral data with the help of an automated robotic tram system over the drying arctic lake bed. The robotic cart samples three 300 meter long transects spread across the lake basin automatically, taking reflectance measurements at each meter using a dual detector spectrometer designed to correct for changing sky conditions. Surface reflectance data were collected for three consecutive years for 2005, 2006 and 2007 as part of the project, which provides a baseline dataset of surface conditions. Three spectral indices, Normalized Difference Vegetation Index (NDVI), a measure of vegetation ‘greenness', the Photochemical Reflectance Index (PRI), a measure of carotenoid pigment levels, and the Water Band Index (WBI), a measure of vegetation moisture content, are calculated from the optical data collected to study the surface conditions of the lakebed. Comparison of three years NDVI data showed different greenness conditions of the surface. Peak season NDVI values were the lowest in 2005 compared to 2006 and 2007. WBI values for the two dry years 2005 and 2007 were similar for all the tramlines except for the beginning of the season. PRI values for the two dry years 2005 and 2007 had similar trends for all the tramlines except for the beginning of the season. This tram system along with the cyberinfrastucture tools that we are developing gives us the opportunity for developing a technology to the next level to facilitate the research in the field of environmental science and terrestrial ecology.
DE: 0480 Remote sensing
SC: Biogeosciences [B]
MN: 2007 Fall Meeting