首页> 外文会议>Asian Conference on Remote Sensing >APPLICATION OF SATELLITE DATA AND GEOGRAPHIC INFORMATION SYSTEM FOR DROUGHT RISK AREA ANALYSIS IN BANDANLANHOI DISTRICT, SUKHOTHAI PROVINCE
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APPLICATION OF SATELLITE DATA AND GEOGRAPHIC INFORMATION SYSTEM FOR DROUGHT RISK AREA ANALYSIS IN BANDANLANHOI DISTRICT, SUKHOTHAI PROVINCE

机译:卫星数据和地理信息系统在苏凯岛班省兰山区旱地区旱灾区分析中的应用

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The objectives of this study are application of satellite data and geographic information system for drought risk area analysis in Bandanlanhoi district, Sukhothai province. The study area covered 100 Sq.km and some part of villages number 1, 2, 3, 4, 5, 6 and 7 which belonged to Bandan subdistrict, villages number 1, 2, 3, 4 and 8 which belonged to Lanhoi subdistrict, village number 1 which belonged to Wungtako subdistrict, villages number 2 and 4 which belonged to Wungluek subdistrict and villages number 1 and 2 which belonged to Nongyapong subdistrict. Satellite data was applied for creation spatial data and other data such as land use and distance from water body were used for determination the drought risk area. Geographic Information System was applied to simulation spatial data such as rainfall, rainy days, relative humidity, temperature, groundwater potential, distance from water body, slope, elevation and soil drainage data. The procedure of stepwise regression model, All physical spatial data cause of drought risk area had been analysed by the stepwise regression model and showed that the well soil drainage and rainfall are important parameters. Especially, The well soil drainage is the most important parameter for determination drought risk area. Drought model was calculated from all spatial parameters by running stepwise multiple regression. The result of map accuracy was showed 58% correction.
机译:本研究的目的是在苏凯岛省班丹省省兰省地区的卫星数据和地理信息系统中应用卫星数据和地理信息系统。该研究区域涵盖了100平方米的村庄,属于Bandan Subdistrict的村庄1,2,3,4,5,6和7,属于Lanhoi子公司的村庄1,2,3,4和8,属于Wungtako Subdistrict的村庄1,属于Wungluek子公司的村庄2和4个属于Nongyapong子公司的村庄1和2。卫星数据被应用于创建空间数据,其他数据如土地利用和水体距离,用于确定干旱风险区域。地理信息系统应用于仿真空间数据,如降雨,雨天,相对湿度,温度,地下水势,距水体,坡度,海拔和土壤排水数据的距离。逐步回归模型的步骤,逐步回归模型分析了干旱风险区域的所有物理空间数据原因,并显示了井土排水和降雨是重要的参数。特别是,井土排水是确定干旱风险区域最重要的参数。通过运行逐步多元回归从所有空间参数计算干旱模型。映射精度的结果显示为58%的校正。

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