全国农作物叶面积指数遥感估算方法

    Method for estimating crop leaf area index of China using remote sensing

    • 摘要: 目前对农作物叶面积指数LAI的遥感估算研究多是针对单一作物或是作物种植结构单一的区域,该文运用大尺度农作物叶面积指数的遥感估算方法,在像元尺度上对4个代表性实验站的LAI与归一化植被指数(NDVI)的相互关系进行了回归分析后,得到4种代表性作物种植结构的LAI估算模型,然后结合全国农作物种植结构数据对模型外推,建立了一个全国尺度的遥感模型,并估算了全国作物LAI。该文使用“863”项目山东遥感应用综合试验中的作物LAI观测数据进行了验证,结果表明该模型较其它估算模型达到了较高的精度,最大相对误差为39%,平均的相对误差为19%。该模型的计算结果已经在“中国农情遥感速报”系统中得到了广泛的应用。

       

      Abstract: The recent researches on estimating crop leaf area index(LAI) with remote sensing were mostly concerned about only single type of crop or a region whose crop planting structure is simple. The large scale crop LAI estimating method was used in the research. After analyzing the relationship between observed LAI and NDVI in four representative observing areas in China, LAI estimating models for four representative crop planting structures were built. Country-scale crop LAI estimating model of China was derived for the first time by extrapolating the four models with zonal data of China for different crop planting structures. The crop LAI of China was computed with the model and the result was validated with the observed crop LAI data obtained in 863's integrated experiment for RS in Shandong Province. The results of validation show that max relative error of the model is 39% while the average error of it was 19%, which means the model achieves a high precision. The result of the model has been widely used in "China Crop Watch System with Remote Sensing".

       

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