Relationship Between Remote Sensing Image Information Capacity And Surface Thermal Environment

China is now in the rapid development of urbanization, which exerts lasting and far-reaching impact on urban microclimate urbanization, vegetation cover status and ecological security. With the changing on the statues and types of the vegetation cover and physicochemical properties of the earth surface causing changes on exchange process of water and hot energy, those made alters on urban "heat " environmental systems.Remote sensing image information capacity is the development of computer graphics on remote sensing image processing, reflect the degree of variation between pixels through statistical calculations gray value of remote sensing image; remote sensing capacity have an effective response of the image information with a numerical value, which is a dimensionless value. Remote sensing image information capacity calculation model is built on the theory of multi-dimensional histogram based on the range of different constraint values which can effectively characterize its remote sensing image quality or surface complexity, the value is mainly affected by changes in image intensity values, factors affecting their size are:landforms, the relationship between land cover objects, terrain and so on.Based on in-depth research of the image information capacity, this paper analyzes the evaluation and results of existing remote sensing image information capacity calculation procedures for different image. It takes the Guanzhong Plain in Shaanxi Province as an example, Landsat8OLI multispectral data and TIRS thermal infrared data as the primary data source for remote sensing and GIS spatial analysis of quantitative inversion for technical support, different vegetation indices were calculated simultaneously using different the ground temperature calculation method, the temperature of the surface condition of Xi’an city were analyzed and evaluated, and spatial analysis and statistical analysis methods were adopted to calculate the coupling relationship among Landsat8data capacity, vegetation index and surface temperature. The main conclusions of the study are:1Based on the characteristics of the research capacity on remote sensing image, it analyzed the model in response to changes of the image, indicating that the information capacity could reflect that these image processing methods can be adopted to improve the image quality.2Depending on the temperature inversion methods, analyzed the two inversion methods of Landsat8, showed that the surface temperature inversion single window algorithm is the most suitable algorithm for TIRS sensor data.3It discussed the coupling relationship between surface capacity and several vegetation indexes, indicating the index precision of remote sensing image information, NDVI and vegetation coverage reached more than0.8, the correlation is above0.85.4Studies have shown that correlation of the information capacity and surface temperature is above0.93, indicating that the information capacity of surface is sensitive to the changes in temperature.5It demonstrated the relationship between information capacity and surface temperature; broaden the meaning of the image information capacity in geography, which were introduced to a wider range of research areas.