Title :
Biomass Estimation Based on the Fusion of ICESat GLAS and MODIS Data in the Chongming Eastern Tidal Flat of the Yangtze River
Author :
Chun Liu ; Neng Cai ; Hangbin Wu
Author_Institution :
Dept. of Surveying & Geo-Inf., Tongji Univ., Shanghai, China
Abstract :
Mapping of vegetation´s type, structure parameters and biomass are critical for understanding the vegetation´s significance in the carbon cycle, its response to an impact on regional ecological change. In this paper, we describe a new systematic methodology to measure vegetation height and aboveground biomass by remote sensing. For the entire study area, GLAS footprints were overlaid with MODIS land cover classes. The study area was stratified into homogeneous physiographic strata based on the MODIS cover vegetation types. Sparse ICESat data are first combined with MODIS-derived land cover information to provide contextual information for each observation, and to provide appropriate estimates of vegetation structure at 1° resolution. Next, assess their relationship with known biophysical attributes. The results of predicted aboveground biomass were in agreement on the amount and distribution after comparison with reference data, which showed that the predict model for GLAS successfully captured the change of aboveground biomass.
Keywords :
ecology; optical radar; radar altimetry; remote sensing by laser beam; remote sensing by radar; renewable materials; rivers; terrain mapping; vegetation mapping; Chongming Eastern tidal flat; GLAS data; GLAS footprints; LIDAR; MODIS cover vegetation types; MODIS data; MODIS land cover classes; MODIS-derived land cover information; Yangtze river; aboveground biomass; biomass estimation; biophysical attributes; carbon cycle; contextual information; homogeneous physiographic strata; reference data; regional ecological change; remote sensing; sparse ICESat data; structure parameters; systematic methodology; vegetation height; vegetation significance; vegetation structure; Biological system modeling; Biomass; Data models; MODIS; Remote sensing; Satellites; Vegetation mapping;
Conference_Titel :
Image and Data Fusion (ISIDF), 2011 International Symposium on
Conference_Location :
Tengchong, Yunnan
Print_ISBN :
978-1-4577-0967-8
DOI :
10.1109/ISIDF.2011.6024279