Jialingjiang river is one of major-soil erosion watershed of the Yangtze river, its basin area and average annual runoff account respectively for 15.8% and 15.6% of the total amount of the Yangtze river upstream the Yichang hydrologic station, but its sediment production accounts, for 25.5%. Severe soil erosion is not only a big threat to the downstream ecological environment but also a critical factor in the future operation of the Three Gorge reservoir. Therefore, the government has already been developing a number of soil and water conservation projects in this watershed since 1989. Its two main upstream tributaries Bailongjiang and Xihanshui are the most severe soil erosion prone areas, which were selected in this study. Two time series of Landsat TM images in 1992 and 1996 were used to investigate the dynamic variation of soil erosion in the area. An Arc/Info GIS based dynamic spatial information system was developed for data storage and manipulation with its user interface compiled with GeoMedia and Visual Basic.

In this paper, the instantaneous temperature field was produced based on classifying of TM6 data using computer. The conditions of water and temperature were analyzed according to these maps. It was studied that relation between the instantaneous temperature and the conditions of water and temperature in Mountain Area. It was discussed that the formed mechanism of conditions of water and temperature and characteristic of water and temperature climate. The Mountain Area's zones of conditions water and temperature were divided. The ecological adaptability in zones of water and temperature conditions was evaluated after field survey. All of these supplied basis for fully utilization of water and temperature resources, optimizing natural environment, adjusting agriculture planting structure, promoting economic sustainable development.

In this paper, authors distinguish the situation of urban landuse from aerial photograph of 1998. The urban land quality was evaluated. Based on this, the urban landuse area of different style was optimized by SD Model and multi-object plan model. Space disposition of urban land was completed with own program on computer.

The paper introduces how to identify, conform and apply the resouce of terrestrial heat in Xiazhuang of Handan by remote sensing interpretation, exploration and drill technique, trys to find the method of utilizing remote sensing technology and reveal its wide prospect. It transforms the last accomplishment of remote sensing technology into applicable plan of project construction. It's a successful example in small area resources investigation and development by remote sensing technology.

This paper first introduces how to get basic information through remote sensing interpretation and field works, then describes the method of inputting remote sensing investigation results and other geographical, social and economic information into GIS based on consolidate software and hardware environment. At last, using GIS special functions to analyze the status of land use and social economy in Chongqing City.

This paper deals with the techniques for improving image classification by extracting geometric attributes of objects. In this paper, we first introduce one kind of symmetry transform called directional symmetry transform, which can provide more geometric information about objects. Based on it, we present one algorithm for improving image classification by determining scale factors relating to supervised learning. The results show that the number of the mixed pixels can be efficiently reduced by using the proposed method.

Logistic method is a nonlinear regression analysis method, which is based on the Logistic model. Usually, It is used to forecast and classify the unknown units into the known types. Other than the common classification methods, it can respectively calculate the probabilities which one unit belongs to the different known types, then, classify and forecast all the units of the unknown research field. In this paper, firstly we introduce the keystone of Logistic method, then, classify the two different remote sensing image data of the two different fields in The Inner Mongolia Autonomous Region by this method, finally discuss about a few factors which affect remote sensing image classification using logistic method.

The formation mechanism of seismic disaster information of building in remote sensing image is discussed in the paper. A series of special parameters which reveal the building seismic disaster information are brought forward based on study of the image grey scale and image texture characteristics. Statistical analysis of test image sub-sections of different styles shows the average value, standard deviation and variance of grey scales are the effective indicators for recognition and classification of building seismic disaster in digital images, the texture inverse difference matrix and texture correlation can be used as the supplementary indicators.

In this article, natural environment restricted soil productivity of Changqing county, a county of Jinan city,has been evaluated based on the ten-singular factor-evaluation. During the studying, technique of GIS and RS were fully and widely used in order to ensure the precision and improve the work efficiency. Owe to the rationality of evaluation scheme and the advancement of studying technique, the result of calculation by mathematical model was precisely expressed as grid map which the size of single grid is 900 square meter. At last, the soil of the county was classified scientifically according to the calculation result and the bright outlook about the applications were briefly discussed.

Land use change is a result of complex interaction between natural factor and various human work, and soc-economic factor are the important drive force in short term. The study area is Qianguo county of Jilin province lies in northeast of China. To discuss the progress of land use change and the soc-economic driving mechanism of these changes since 10 years in study area, we analyze TM image of 1987 and 1996, and related statistic data by using spatial analysis, statistic analysis and the method integrated image data with vector data. The result shows that farmland area increased significantly while forest and grassland area decreased, and others changed a little. The main driving forces lead to these changes are agriculture production, breeding production, agriculture population and food production.