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Drought detection in semi-arid regions using remote sensing of vegetation indices and drought indices

机译:利用近距离感应植被指数和干旱指数的半干旱区干旱检测

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Drought is a serious climatic condition that affects nearly all climatic zones worldwide, with semi-arid regions being especially susceptible to drought conditions because of their low annual precipitation and sensitivity to climate changes. Drought indices such as the Standardized Precipitation Index (SPI) have been developed for quantifying drought conditions. Usually, calculation of drought indices requires a long record of climatic data, which may not be available because of the inaccessibility of a region and a lack of human activity. Remote sensing of semi-arid vegetation can provide vegetation indices which can be used to link drought conditions when correlated with various drought indices. Spectral reflectance measurements of creosote and black gramma grass were taken between January and November 2003 in the Sevilleta National Wildlife Refuge of New Mexico and various vegetation indices were derived. Each vegetation index was correlated with the SPI of various weekly timescales at varying time-lag intervals calculated from 1999 to seek the best vegetation index that can be used as the best indicator of SPI conditions. The results show a strong linear correlation between the vegetation indices NDVI, Greenness Index, ARVI and drought index SPI at various SPI measurements with various lag times.
机译:干旱是一种严重的气候条件,影响全世界的所有气候区,半干旱地区由于其年降水量低和对气候变化的敏感性而特别容易受到干旱条件的影响。已经开发出用于量化干旱条件的制定标准化降水指数(SPI)等干旱指标。通常,干旱指数的计算需要很长的气候数据记录,这可能无法获得,因为区域的难以进入和缺乏人类活动。半干旱植被的遥感可以提供植被指数,可用于在与各种干旱指数相关时连接干旱条件。 2003年1月至11月在2003年1月和11月在新墨西哥州的塞维利亚国家野生动物避难所之间采取了光谱反射率测量,各种植被指数得到了各种植被指数。每个植被指数以不同于1999年计算的不同时间滞后间隔,每个植被指数都与各个每周时间尺度的SPI相关联,以寻求最佳植被指数,可作为SPI条件的最佳指标。结果表明,植被索引NDVI,绿色指数,ARVI和干旱指数SPI在各种滞后时间的各种SPI测量之间存在强烈的线性相关性。

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