Loess Plateau is a unique region in the world where the human activities are very intensive and the eco-environment is highly frangible. During the past two decades, the Land Use/Cover Change has been considered as one of the most important reasons for the eco-environment degeneration in Loess Plateau. In this paper, land use data in 1990, 1995 and 2000 were got based on the Landsat TM Remote Sensing images, and the 1km-grid land use change data of 1990-1995,
1995-2000 and 1990-2000 was made using the data management and spatial analysis techniques of ArcGIS 8.3 software. Furthermore, statistical tabular data of Grain for Green Project on county level in recent years were joined in the administrative regionalism spatial data. Based on all of these data, temporal-spatial characteristics of land use change in Loess Plateau were studied in detail, and its driving forces were discussed either. It turned out that land use change in different periods had very different characteristics. On the whole, from 1990 to 2000, farmland and built-up increased
greatly, and forest, grassland, water body and unused land decreased remarkably. On the contrary, conversions from farmland and unused to forest or grassland has become the dominant land use change process since 2000. The regional social-economic development and the national macro-control policy have been the most important driving forces of land use change since 1990. Especially, from 2000 to now, the widely implemented Grain for Green Project, under which farming on fragile land gives way to forestation, has become and will remain the most radical and effective driving force to both the land use change and the regional eco-environment restoration.
<i></i>Landsat TM/ETM+ sensor data has proven to be a highly effective data source for vegetation and land use classification at both global and regional scales. In this study, based on land cover classification, we conducted computer-aided analysis of degradation sequence of the meadow grassland in Xilin River Basin, Inner Mongolia, using 4 sets of Landsat TM/ETM+ images (WRS 124-39 and 124-30) acquired on Jul.31, 1987, Aug.11, 1991, Sep. 27, 1997 and May 23, 2000, respectively. Primarily, 17 sub-class land cover types were recognized, including 9 grassland types at community level: <i>F. sibiricum steppe</i>, <i>S. baicalensis</i> steppe, <i>A. chinensis </i>+ forbs steppe, <i>A. chinensis </i>+ bunchgrass steppe, <i>A. chinensis + Ar. frigida </i>steppe, S. grandis + <i>A. chinensis steppe, S. grandis </i>+ bunchgrass steppe, <i>S. krylavii </i>steppe, <i>Ar. frigida </i>steppe and 8 non-grassland types: active cropland, harvested cropland, urban area, wetland, desertilized land, saline and alkaline land, cloud, water body + cloud shadow. Then we created thematic maps of the areal change and spatial variation of the meadow grassland in Xilin River Basin, Inner Mongolia. We used Geographical Information System (GIS) tools to create thematic maps of the meadow grassland and then analyzed its degradation sequence (or the evolution route). Driven by overgrazing, the meadow grassland ecosystem in Xilin River Basin, Inner Mongolia had undergone and was undergoing degradation evolution; the evolution route was from meadow grassland (<i>F. sibiricum </i>steppe, S. baicalensis steppe), via temperate grassland (<i>A. lymus </i>+ bunchgrass steppe, <i>A. lymus </i>+ forbs Steppe, <i>A. lymus </i>+ <i>S. grandis </i>steppe, <i>S. grandis </i>+ bunchgrass steppe, <i>S. grandis </i>+ forbs steppe and <i>A. lymus </i>+ <i>Ar. frigida </i>steppe) to desert grassland (<i>S. krylavii </i>steppe and <i>Ar. frigida </i>steppe). Results of this study show that increasing human population and accelerated social-economic development has caused dramatic degradation and fragmentation to the grassland ecosystems in Xilin River Basin.
Vegetation phenology is an important variable in a wide variety of Earth and atmospheric science applications. The role of remote sensing in phenological studies is increasingly regarded as a key to understanding large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for forest phenology analysis. The phenology of forest covering Northeast China and its spatial characteristics were investigated using MODIS normalized difference vegetation index (NDVI) data. Threshold-based method was used to estimate three key forest phenological variables: start of growing season (SOS), end of growing season (EOS) and the growing season length (GSL). The spatial pattern of key phenological stages were mapped and analyzed. The derived phenological variables were validated by referring to previous research achievements in this study area. The phenological pattern of Changbaishan Reserve was compared with the distribution of forest types. Results indicate that spatial characteristics of vegetation phenology are corresponding with the distribution of vegetation types and the phenology information can be used to improve vegetation classification accuracy as an auxiliary variable.