HR: 15:05h
AN: B33F-06    [Abstracts]
TI: Mapping and monitoring of crop intensity, calendar and irrigation using multi-temporal MODIS data
AU: * Xiao, X
EM: xiangming.xiao@unh.edu
AF: University of New Hampshire, 39 College Road Institute for the Studies of Earth, Oceans and Space, Durham, NH 03824 United States
AU: Boes, S
EM: stephen.boles@unh.edu
AF: University of New Hampshire, 39 College Road Institute for the Studies of Earth, Oceans and Space, Durham, NH 03824 United States
AU: Mulukutla, G
EM: gopal.mulukutla@unh.edu
AF: University of New Hampshire, 39 College Road Institute for the Studies of Earth, Oceans and Space, Durham, NH 03824 United States
AU: Proussevitch, A
EM: alex.proussevitch@unh.edu
AF: University of New Hampshire, 39 College Road Institute for the Studies of Earth, Oceans and Space, Durham, NH 03824 United States
AU: Routhier, M
EM: mike@meridian.sr.unh.edu
AF: University of New Hampshire, 39 College Road Institute for the Studies of Earth, Oceans and Space, Durham, NH 03824 United States
AB: Agriculture is the most extensive land use and water use on the Earth. Because of the diverse range of natural environments and human needs, agriculture is also the most complicated land use and water use system, which poses an enormous challenge to the scientific community, the public and decision-makers. Updated and geo-referenced information on crop intensity (number of crops per year), calendar (planting date, harvesting date) and irrigation is critically needed to better understand the impacts of agriculture on biogeochemical cycles (e.g., carbon, nitrogen, trace gases), water and climate dynamics. Here we present an effort to develop a novel approach for mapping and monitoring crop intensity, calendar and irrigation, using multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) image data. Our algorithm employed three vegetation indices that are sensitive to the seasonal dynamics of leaf area index, light absorption by leaf chlorophyll and land surface water content. Our objective is to generate geospatial databases of crop intensity, calendar and irrigation at 500-m spatial resolution and at 8-day temporal resolution. In this presentation, we report a preliminary geospatial dataset of paddy rice crop intensity, calendar and irrigation in Asia, which is developed from the 8-day composite images of MODIS in 2002. The resultant dataset could be used in many applications, including hydrological and climate modeling.
DE: 0315 Biosphere/atmosphere interactions (0426, 1610)
DE: 0402 Agricultural systems
SC: Biogeosciences [B]
MN: Fall Meeting 2005