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Reconstructing Vegetation Temperature Condition Index Based on the Savitzky-Golay Filter

机译:基于Savitzky-Golay滤波器重建植被温度条件指数

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Vegetation temperature condition index (VTCI) is a near-real-time drought monitoring approach which is derived from normalized difference vegetation index (NDVI) changes in a given region to land surface temperature (LST) changes of pixels with a given NDVI value. It can be physically explained as the ratio of temperature differences among the pixels which have the same NDVI values. Due to the noise in the NDVI and LST, results of VTCI have much deviation. The Savitzky-Golay filter, a weighted moving average filter as a polynomial of a certain degree, is applied to smooth out noise in NDVI and LST time-series. VTCI were taken into Guanzhong Plain of Shaanxi Province of each 10-days from March to May in 2007 and 2008 as the study data. In order to reconstruct VTCI space-time (temporal and spatial) series data, the Savitzky-Golay filter was used to reconstruct the VTCI time-series of each pixel in remote sensing images. Then, the results were extended to the surface from the point. The results show that the Savitzky-Golay filter could improve the quality of VTCI and could get a better drought monitoring result.
机译:植被温度条件指数(VTCI)是近实时的干旱监测的办法,从归一化植被指数(NDVI)衍生的变化在给定的区域中的地表温度(LST)与给定的NDVI值的像素的变化。它可以作为具有相同NDVI值的像素之间的温度差的比率来物理地说明。由于在NDVI和LST噪声,VTCI的结果有很大的偏差。所述Savitzky-Golay滤波,加权移动平均滤波器作为多项式一定程度的,被施加到在NDVI和LST时序噪声平滑。 VTCI被带进每10天的陕西省关中平原,从三月到五月在2007年和2008年的研究数据。为了重建VTCI时空(时间和空间)系列数据时,Savitzky-Golay滤波被用来重建在遥感图像的VTCI时间序列的各像素的。然后,结果被扩展到由点的表面。结果表明,Savitzky-Golay滤波可以改善VTCI的质量,可以得到更好的干旱监测结果。

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