The Mid-Yellow River region has been facing serious problems such as the most extensive soil erosion and water loss in the world, water shortage, flood disasters, ecological and environmental degradation. Evapotranspiration is a key component in the energy and water balance and plays an important role in the water cycle of the Mid-Yellow River region. Study on evapotranspiration and water consumption of vegetation (including forests and grasslands) over the Mid-Yellow River region will give basic knowledge of water supply and demand as well as water-consuming characteristics of vegetation. This study will also contribute to rationally develop and use limited water resources in the Mid-Yellow River region, and therefore, it has theoretical and practical significance. In this paper, based on Remote Sensing and GIS techniques, evapotranspiration and water consumption by vegetation were estimated in the Mid-Yellow River region. First, after the geometric correction, radiometric calibration and false color composition, Landsat TM Remote Sensing image in 2000 were interpreted carefully and the vegetation distribution data in the Mid-Yellow River region were gained. Then, by the ArcGIS 8.3 Software, the total area of various vegetation types was figured out and the 1km-Grid dataset was established by which the proportions and ratios of every type of vegetation on the scale of one square kilometer have been expressed. Finally, based on the meteorological data and the Penman-Monteith Method, evapotranspiration and water consumption for various types of vegetation were estimated. The results showed that in the Mid-Yellow River region, water consumption by forests and grasslands were 31.41 billion m3 and 44.08 billion m3 respectively.
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.
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.