Based on land-use datum (at scale of 100,000) of the interpretation of Landsat Thematic Mapper in 1980, 1995 and 2000, which came from environmental database of the Chinese Academy of Sciences, the authors investigated land-use change and influential factors by the combined use of geographic information systems (GIS) method, Markov model and canonical correlation analysis (CCA) statistical method. The results showed that, in the periods 1980-2000, crop land
increased by 0.58 percent (4278.86 hectares), of which 92.93 percent was transformed from grassland and 7.07 percent from forestland. Urban or built-up land increased by 26.23 percent (687.45 hectares), of which 77.35 percent was transformed from cropland. Rural residential land increased by 5.17 percent (1324.37 hectares). Forestland and water land decreased in area. Grassland decreased by 0.57 percent (5706.77 hectares). Secondly, transition rate of landscape spatial pattern among the landscape elements from 1995 to 2000 was slower than that from 1980 to 1995. Land use types as cropland, grassland, woodland and rural residential land were the primary change types from 1995 to 2000. Thirdly, both natural and social economic factors influenced land use pattern. The population and per capita grain yield were positively correlated to rural residential pattern. The spatial distribution of grassland and cropland showed strong positive correlation to annual rainfall and annual air temperature, and negative association to annual per capita net income of rural residents. The poor annual per capita net income of rural residents and investment in capital construction restricted the extended area of urban build-up land. Therefore, the drought is not proportional to pattern of urban build-up land. The study verified the analysis conclusion of influential factors by redundancy degree of CCA. The integration of remote sensing data, GIS, Markov process and CCA provided a comprehensive method to analyze land use pattern and process with influential factors.
Proc. SPIE. 5544, Remote Sensing and Modeling of Ecosystems for Sustainability
KEYWORDS: Environmental monitoring, Remote sensing, Inspection, Geographic information systems, Pollution, Data acquisition, Data processing, Reconnaissance, Global Positioning System, Environmental management
Application of geo-information science methods in ecotourism development was discussed in the article. Since 1990s, geo-information science methods, which take the 3S (Geographic Information System, Global Positioning System, and Remote Sensing) as core techniques, has played an important role in resources reconnaissance, data management, environment monitoring, and regional planning. Geo-information science methods can easily analyze and convert geographic spatial data. The application of 3S methods is helpful to sustainable development in tourism. Various assignments are involved in the development of ecotourism, such as reconnaissance of ecotourism resources, drawing of tourism maps, dealing with mass data, and also tourism information inquire, employee management, quality management of products. The utilization of geo-information methods in ecotourism can make the development more efficient by
promoting the sustainable development of tourism and the protection of eco-environment.