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A drought analysis method based on modis satellite imagery and AWS data

机译:基于modis卫星图像和AWS数据的干旱分析方法

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This study analyzed the ongoing drought situation in South Korea using MODIS satellite data and AWS ground observation data. In order to analyze the drought, the Scaled Drought Condition Index (SDCI) was calculated utilizing concurrent precipitation, temperature and vegetation factors. Unlike conventional research that utilizes only satellite data, we utilized AWS ground-based observation data that has advantages in terms of data accuracy and collection stability. Precipitation and temperature inputs were sourced from AWS ground observation data while vegetation coverage was obtained from MODIS NDVI data. SDCI was applied to data on June 5, 2012 when the drought was severe. The results of the SDCI were compared with high-land vegetable harvest analysis, and showed a positive mutual correlation.
机译:这项研究使用MODIS卫星数据和AWS地面观测数据分析了韩国持续的干旱情况。为了分析干旱,利用同时发生的降水,温度和植被因子计算了干旱比例指数(SDCI)。与仅使用卫星数据的传统研究不同,我们利用了基于AWS的地面观测数据,该数据在数据准确性和收集稳定性方面具有优势。降水和温度输入来自AWS地面观测数据,而植被覆盖率则来自MODIS NDVI数据。当干旱严重时,将SDCI应用于2012年6月5日的数据。 SDCI的结果与高地蔬菜收成分析进行了比较,并显示出正相关。

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