Multitemporal remotely sensed data provide an accurate, economical means to analyze the changes in land cover over time. Land cover change in the region of Baiyang Lake that is the biggest freshwater lake in North China effects local eco-environment intensely. Based on the Landsat (TM) data for 1987, 1991, 1996, and 2002, and employing the maximum-likelihood method, the land cover was classified into seven types, farmland, forest land, urban land, village, water body, wetland and bare land. The overall classification accuracies averaged 86% and the Kappa coefficient is 0.75. Then the transition matrix of The LCC was obtained by overlaying land post-classification map. Between 1987 and 2002 the amount of farmland decreased from 63.9% to 58% of the total land area, wetland decreased from 4.5% to 3.3%, while forest land increased from 2.6% to 3.3%, urban land increased from 1.2% to 2.6%, village increased from 26.1% to 29.1%, water body increased from 1.3% to 3.3%, the amount of bare land was unchanged. Land cover change can not take place independently but has certain linkages with the socioeconomic factors and mutations in natural conditions. Precipitation controlled the area of water and wetland, and human practice process restricted conversions of farmland, urban land, village and forest land.
In this study, we demonstrate that the conventional temperature/vegetation drought index (TVDI) approach tends to overstate the degree of drought condition in areas with dense vegetation. This is because the TVDI approach may specify points with significant evapotranspiration (ET) activities (i.e. points with soil water content significantly above the wilting point) as the drought points in these areas. To overcome this shortcoming, we construct a new drought index, termed evapotranspiration/vegetation drought index (EVDI), using evapotranspiration distribution derived from the remote sensing data. We apply both TVDI and EVDI approaches to calculate drought indices for a dominantly crop farming region, Luancheng County, in Hebei Province of China at the season of high fractional vegetation cover. We use Landsat7 ETM<sup>+</sup> data to derive the surface temperature, the fractional vegetation cover and evapotranspiration distribution, and compute both TVDI and EVDI maps for this region. Result comparison and analyses show that the TVDI map overstates the drought condition. The EVDI map is a more accurate representation of the real condition.
According to the ground resolution characteristic of Thematic Mapper (TM) image, we correspondingly measured the relative chlorophyll contents in four key developmental stages of winter wheat in the Lower plain of the Hai River Basin, North China, and explored their correlation with the reflected spectral values that can be obtained from TM image. Considering not only NDVI but also the relative content of the chlorophyll, 31 RS variables were selected and the relationship between the variables and the relative content of chlorophyll was established. Regression models were built for quantitatively predicting winter wheat growing condition from TM images. Also the spatiotemporal variability of the winter wheat growth status at heading and booting stages were analyzed by geostatictics approach. The correlated spatial variability of the relative content of chlorophyll existed in the case study area, and the range of correlative distance was from 145.4 to 320.0m. The spatially structured variances were between 75% and 21% of the total variances, and the empirical semivariograms in the four stages could be simulated in spherical models. The result showed that it is feasible to use TM data for real-time and highly accurate monitoring of crop growth status and nutrient management of farmland ecosystems.