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The extraction method of surface temperature in agricultural area using Satellite Remote Sensing and GIS Myung-Hee Jo, Hyoung-Sub Kim Urban Information Cadastral Engineering of Kyungil University mhjo@bear.kyungil.ac.kr star618@dreamwiz.com Hyang-Hee Um Meteorological Research Institute hhum@metri.re.kr Joon-Bum Kim Korea Forest Research Institute JBKIM99@foa.go.kr Introduction Today the gathering information, which is synthetic and systemic, is possible from social activities to natural environment based on divers spatial information technology such as GIS and remote sensing. It, therefore, is processing not only the forecast of meteorological environment in the whole scale of the earth, but also the study about the local area, being possible to get the input datum which need that relative meteorological models have been developed with remote sensing for the decades. The purpose of this study is that the development of the area by the urbanization of the agricultural area interprets more reasonably influencing the area of meteorological environment characteristic, fractionating both the diverse civilization and the environmental information of the nature around the basin of Ansung-watershed area based on population distribution information in addition to the observation of AWS (Automatic Weather Station) around the basin, and also analyzes systemically the pattern of the landcover change, surface temperature as well as NDVI distribution in the agricultural area, applying the technique of GIS spatial analysis and the multi-temporal of Landsat TM satellite image for Ansung-watershed area of Korea. 
Fig. 1 Study area The data and method of study This study applied the data such as multi temporal of Landsat TM image (May 20th 1987, May 20th 1993, May 7th 2000), 1:25,000 digital map, topographic map, AWS observation information of in site(1996∼1999), population statistics information to analyze more systemically the meteorological environment characteristic in the basin of Ansung-watershed (585.188㎢).
To analyze the temperature distribution characteristic in the area of the study object which is spatial-temporal by applying ERDAS Imagine 8.5, it extracted the surface temperature using the value of the radiance got from the value of DN(Digital Number) in Landsat TM band 6. At the same time in classifying landcover, selected the training area using the 1:25,000 digital map as well as topographical map, and it was classified into the 6 classes such as forest, paddy field, field, stream, urban, barren with Maximum Likelihood method of the supervised classification applying Landsat TM false color image (band 4/3/2) after the survey of ground truth. In addition produced NDVI to analyze the vegetation vitality chart around the basin. To analyze the more detail environmental information about basin of Ansung-watershed and surrounding area, this study constructed GIS DB such as administration boundary, drainage network, contour, and road network with both 1:25,000 digital map and topography map using ARC/INFO 8.1, ArcView 3.2. And also produced river density, stream frequency, catchments concentration chart, and bifurcation getting the stream order in the basin by Strahler (1957) stream order calculation formula by using the stream network of these built GIS DB. The aspect and slope map based on the digital elevation model using both contours at intervals of 10m and elevation points were also calculated. This study prepared choroplethe map with population statistics information, which was constructed with DB from 1995 to 2000. 
Information was converted to vector data in contour to use AreView 3.2, using the point data of both longitude and latitude in the network of AWS meteorological observation which has 2 points in the basin of Ansung-watershed area and 5 points around the basin, building as well as classifying the data by day and month which obtained the information such as the highest average temperature, the lowest average temperature, the average temperature, the highest temperature, the lowest temperature, the average wind velocity, the maximum wind velocity, the maximum wind direction, precipitation generating the number of day.
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