The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure...The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure was: (1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images; (2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated; (3) the relationship models between LAI and biomass were built and annual branch, stem, root and maximum leaf biomass over the landscape were simulated; (4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained. The simulation was based on spatial analysis module GRID in ArcInfo software. The method is also a kind of scaling method from patch scale to landscape scale. A case study of Changbai Mountain Nature Reserve was dissertated. Analysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995.展开更多
This study conducted computer-aided image analysis of land use and land cover in Xilin River Basin, Inner Mongolia, using 4 sets of Landsat TM/ETM+ images acquired on July 31, 1987, August 11, 1991, Sep...This study conducted computer-aided image analysis of land use and land cover in Xilin River Basin, Inner Mongolia, using 4 sets of Landsat TM/ETM+ images acquired on July 31, 1987, August 11, 1991, September 27, 1997 and May 23, 2000, respectively. Primarily, 17 sub-class land cover types were recognized, including nine grassland types at community level: F.sibiricum steppe, S.baicalensis steppe, A.chinensis+ forbs steppe, A.chinensis+ bunchgrass steppe, A.chinensis+ Ar.frigida steppe, S.grandis+ A.chinensis steppe, S.grandis+ bunchgrass steppe, S.krylavii steppe, Ar.frigida steppe and eight non-grassland types: active cropland, harvested cropland, urban area, wetland, desertified land, saline and alkaline land, cloud, water body + cloud shadow. To eliminate the classification error existing among different sub-types of the same gross type, the 17 sub-class land cover types were grouped into five gross types: meadow grassland, temperate grassland, desert grassland, cropland and non-grassland. The overall classification accuracy of the five land cover types was 81.0% for 1987, 81.7% for 1991, 80.1% for 1997 and 78.2% for 2000.展开更多
基金One Hundred Talents Program of CAS No.CXIOG-C00-01+1 种基金 National Natural Science Foundation of China No.39970613
文摘The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure was: (1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images; (2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated; (3) the relationship models between LAI and biomass were built and annual branch, stem, root and maximum leaf biomass over the landscape were simulated; (4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained. The simulation was based on spatial analysis module GRID in ArcInfo software. The method is also a kind of scaling method from patch scale to landscape scale. A case study of Changbai Mountain Nature Reserve was dissertated. Analysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995.
基金Knowledge Innovation Project of CAS No.KZCX02-308+1 种基金 The NASA Land Use and Land Cover Change Program No.NAG5-11160
文摘This study conducted computer-aided image analysis of land use and land cover in Xilin River Basin, Inner Mongolia, using 4 sets of Landsat TM/ETM+ images acquired on July 31, 1987, August 11, 1991, September 27, 1997 and May 23, 2000, respectively. Primarily, 17 sub-class land cover types were recognized, including nine grassland types at community level: F.sibiricum steppe, S.baicalensis steppe, A.chinensis+ forbs steppe, A.chinensis+ bunchgrass steppe, A.chinensis+ Ar.frigida steppe, S.grandis+ A.chinensis steppe, S.grandis+ bunchgrass steppe, S.krylavii steppe, Ar.frigida steppe and eight non-grassland types: active cropland, harvested cropland, urban area, wetland, desertified land, saline and alkaline land, cloud, water body + cloud shadow. To eliminate the classification error existing among different sub-types of the same gross type, the 17 sub-class land cover types were grouped into five gross types: meadow grassland, temperate grassland, desert grassland, cropland and non-grassland. The overall classification accuracy of the five land cover types was 81.0% for 1987, 81.7% for 1991, 80.1% for 1997 and 78.2% for 2000.
