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基于LTDRAVHRR和MODIS观测的全球长时间序列叶面积指数遥感反演

DOI: 10.3724/SP.J.1047.2015.01304, PP. 1304-1312

Keywords: 植被,叶面积指数,全球,长时间序列,遥感反演

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Abstract:

叶面积指数是描述土壤-植被-大气之间物质和能量交换的关键参数,获取大区域长时间序列叶面积指数有助于研究气候变化条件下植被的响应及反馈。本文利用MODIS观测和经过重新处理的地表长时间数据集(LandLongTermDataRecord)LTDRAVHRR数据,生成了全球1981-2012年叶面积指数数据。算法通过建立二者之间像元级关系,利用高质量MODIS观测约束历史AVHRR数据的反演,这有助于减小2种存在显著差别传感器反演结果的不一致性,也有助于提高AVHRR反演质量。首先算法利用高质量MODIS地表反射率反演2000-2012年叶面积指数,然后利用多年每8d的LTDRAVHRR地表反射率数据计算简单比植被指数(SimpleRatio,SR),利用SR平均值和MODISLAI平均值建立像元级AVHRRSR-MODISLAI关系。在此基础上,实现1981-1999年AVHRRLAI反演,最终得到全球1981-2012年叶面积指数数据。本算法反演的AVHRR和MODISLAI与全球植被的空间分布吻合,能表征主要生物群系类型的季节变化特征,2个数据集一致性较好,并且与NASAMODISLAI标准产品(MOD15A2)的空间分布和季节变化曲线吻合较好。

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