应用中值融合模型的条件植被温度指数降尺度转换研究

发布时间：2018-06-24 13:20

  本文选题：干旱遥感监测 + MODIS数据　； 参考：《农业机械学报》2017年06期

【摘要】：为获得基于Landsat卫星遥感数据更为精确的定量化干旱监测结果,以陕西省关中平原为研究区域,基于Aqua MODIS数据反演的1 km空间分辨率的条件植被温度指数(VTCI)的定量化干旱监测结果(MODIS-VTCI)和Landsat OLI/TIRS数据反演的30 m空间分辨率的VTCI相对干湿监测结果(Landsat-VTCI),应用降尺度的中值融合模型(MFM)将基于MODIS数据反演的VTCI降尺度至30 m空间分辨率的VTCI定量化干旱监测,并对其结果进行验证。结果表明,应用降尺度的中值融合模型转换的VTCI定量化干旱监测结果(MFM-VTCI)与Landsat-VTCI的空间分布及纹理特征相似,两者间的相关系数和结构相似度均较大,均方根误差、差值影像及差值频数分布图所呈现的结果与定量化干旱监测结果和相对干湿监测结果间的系统误差相符,表明Landsat-VTCI与MFM-VTCI间的可比性较强。MFM-VTCI与累计降水间的相关性和MODIS-VTCI与累计降水间的相关性相近,均大于Landsat-VTCI与累计降水间的相关性,表明MFM-VTCI是定量化的干旱监测结果。
[Abstract]:In order to obtain more accurate quantitative drought monitoring results based on Landsat satellite remote sensing data, the Guanzhong Plain of Shaanxi Province is taken as the research area. 1 km spatial resolution conditional vegetation temperature index (VTCI) based on Aqua MODIS data inversion, quantitative drought monitoring results (MODIS-VTCI) and 30 m spatial resolution relative dry and wet monitoring results (Landsat-VTCI) of Landsat OLI / TIRS data. The value Fusion Model (MFM) is used to quantify the drought monitoring with VTCI downscaling to 30 m spatial resolution based on MODIS data. The results are verified. The results show that the VTCI quantitative drought monitoring results (MFM-VTCI) and Landsat-VTCI are similar to Landsat-VTCI in spatial distribution and texture characteristics. The correlation coefficient and structural similarity between them are large, and the root mean square error (RMS). The results of difference image and difference frequency distribution map are consistent with the systematic error between quantitative drought monitoring results and relative dry and wet monitoring results. The results show that the correlation between Landsat-VTCI and MFM-VTCI is stronger. The correlation between MFM-VTCI and accumulated precipitation and between MODIS-VTCI and accumulated precipitation is similar, which is higher than that between Landsat-VTCI and accumulated precipitation, which indicates that MFM-VTCI is a quantitative result of drought monitoring.
【作者单位】： 中国农业大学信息与电气工程学院;陕西省气象局;
【基金】：国家自然科学基金项目(41371390)
【分类号】：Q948;TP79
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本文编号：2061659