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The Cloud Detection, Land Cover Patterns and Land Surface Temperature Retrieved from Remotely Sensed Data of HJ-1B

Author: HanChunFeng
Tutor: ChenYouFei;ZhangYouShui
School: Fujian Normal University
Course: Cartography and Geographic Information Systems
Keywords: HJ-1B satellite Cloud detection Surface temperature (LST) Normalized Difference Vegetation Index ( NDVI ) Percentage of impervious surface (FIS) Vegetation coverage (FVC)
CLC: TP79
Type: Master's thesis
Year: 2010
Downloads: 150
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Abstract


HJ-1 star ascended to heaven, and successful shooting, promote the development of China's remote sensing cause. For China's own space satellite, its application to become the focus of the present study. Shooting time, atmospheric conditions, and the impact of the natural geographic and environmental conditions of the study area, making the image quality of the study area there are different HJ-1B image area in Fujian Province. Cloud covered pixel, thereby reducing the utilization rate of the image, in order to avoid the cloud like surface parameters inversion, the papers were two aspects illustrates the application of HJ-1B satellite data from the real cloud detection with surface temperature inversion. Correct separation of cloud and clear sky is the inversion of the pre-treatment of a variety of atmospheric and surface parameters must work, is the basis of a large number of research work, as well as other product development. Cloud identification product results accurate or not directly affect the other parameters of the inversion results, the cloud identification must be the product of HJ-1 satellite in the series, the papers from the visible - near infrared angle of departure of its HJ-1B the visible reflectance threshold detection, the detected effect is ideal. The final go cloud image is also in line with this thesis, the following surface parameters inversion requirements. Surface temperature, vegetation cover, surface albedo surface biophysical parameters is an important factor for global material and energy cycles, climate change, and energy balance. Remote sensing quantitative research is one of the hot spots. Accompanied by the rapid development of China's economy and the urbanization process, the thermal environment spatial distribution of the underlying surface by surface land cover patterns are also becoming more and more significant. Due to the complexity of the underlying surface itself, regardless of the surface parameters inversion, land cover model of the urban heat island effect relationship study there are still difficulties to be overcome. Therefore, on the basis of previous studies, select a suitable algorithm HJ-1B Star quantitative extraction of land cover parameters and surface temperature, and then proceed from the point of view of the different levels of the same class, analyzing the various land cover parameters Xiadian The distribution of surface thermal environment space, the spatial distribution pattern to provide a basis for the study of the thermal environment. The advantage of the new data source quantitative retrieval of surface parameters is very necessary. The study selected for the study area in Fuzhou HJ-1B satellite data as of February 23, 2010, the data source, Jimenez-Munozoz Sobrino algorithm to realize the true surface temperature inversion. Estimation methods of surface emissivity IGBP (International Geosphere-Biosphere Program) land type classification, according to different classes emissivity emissivity estimates of their study area, thereby inversion the real temperature of the surface. Use of the spectral characteristics of the red band and near-infrared bands, to extract NDVI in the study area using NDVI binary model to extract the vegetation coverage of the study area (Fractional Vegetation Cover, FVC), as well as urban impervious surface information. The acquisition of surface parameters, and quantitative analysis of the relationship between surface temperature and other surface parameters (vegetation coverage, impervious surface density, NDVI) from multiple angles, using simple linear relationship between surface temperature and other parameters model is not appropriate, relatively speaking, for the different grades of the same ground class analysis of the effect of the parameters on the spatial distribution of the surface temperature is more obvious. Impervious surface and NDVI using stable combination of urban heat environment spatial distribution of its research to provide a means and method of the inversion.

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