基于VTCI空间尺度上推方法的干旱影响评估

发布时间：2018-05-17 19:15

  本文选题：条件植被温度指数 + 空间尺度上推　； 参考：《农业机械学报》2017年02期

【摘要】：基于关中平原Aqua MODIS条件植被温度指数(VTCI)的干旱监测结果,分别采用分布式和聚合式的主导类变异权重法(DCVW)、算术平均值变异权重法(AAVW)和中值变异权重法(MPVW)对市域单元内VTCI进行空间尺度上推,以获取冬小麦主要生育期聚合后的加权VTCI;以加权VTCI与冬小麦产量间的回归分析精度为参考,选择最为合适的空间尺度上推方法。结果表明:采用分布式获得的加权VTCI与冬小麦产量的回归分析结果整体优于聚合式获得的结果。在分布式的上推过程中,MPVW获得的加权VTCI与冬小麦产量间的回归分析精度较低,DCVW和AAVW的精度均较高,其中DCVW获得的加权VTCI与冬小麦产量间回归分析的决定系数R2达0.64,精度最高,说明采用分布式DCVW对市域单元内VTCI进行空间尺度上推得到的加权VTCI最为合理。
[Abstract]:Based on the drought monitoring results of Aqua MODIS condition vegetation temperature index in Guanzhong Plain, Using distributed and aggregated dominant class variation weight method, arithmetic mean variation weight method and median variation weight method to push up the spatial scale of VTCI in the city area, respectively. Taking the weighted VTCI after the aggregation of the main growth stages of winter wheat and the precision of regression analysis between weighted VTCI and winter wheat yield as the reference, the most suitable spatial scale push-up method was selected. The results showed that the result of regression analysis of weighted VTCI and winter wheat yield obtained by distributed method was better than that obtained by aggregate formula. The precision of regression analysis between weighted VTCI obtained by MPVW and winter wheat yield was lower than that of AAVW, and the coefficient of determination between weighted VTCI obtained by DCVW and winter wheat yield was 0.64, the precision was the highest. It is shown that the weighted VTCI with distributed DCVW is the most reasonable in spatial scale for the VTCI in the city area.
【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;
【分类号】：S127
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本文编号：1902530