采用DBM方法的时间序列LAI建模与估算

陈平; 王锦地; 梁顺林

doi:10.11834/jrs.20121133

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专辑

采用DBM方法的时间序列LAI建模与估算
A data-based mechanistic approach to time-series LAI modeling and estimation
2012年16卷第3期页码：505-519
纸质出版日期： 2012 ，
DOI： 10.11834/jrs.20121133

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[1]陈平,王锦地,梁顺林.采用DBM方法的时间序列LAI建模与估算[J].遥感学报,2012,16(03):505-519.

A data-based mechanistic approach to time-series LAI modeling and estimation[J]. Journal of Remote Sensing, 2012,16(3):505-519.
[1]陈平,王锦地,梁顺林.采用DBM方法的时间序列LAI建模与估算[J].遥感学报,2012,16(03):505-519. DOI： 10.11834/jrs.20121133.

A data-based mechanistic approach to time-series LAI modeling and estimation[J]. Journal of Remote Sensing, 2012,16(3):505-519. DOI： 10.11834/jrs.20121133.

摘要

运用DBM（Data Based Mechanistic）方法

使用MODIS数据

建立了遥感观测反射率数据与叶面积指数（LAI）在时间序列上的统计关系模型（LAI

BM模型）

并结合部分Bigfoot站点实测LAI数据进行了模型检验。结果显示

LAI

BM模型能够较好表达时间序列反射率与LAI的动态变化关系。LAI

BM模型使用遥感观测数据实时估算得到的LAI

在数据质量和时间连续性上比MODISLAI有改进。

Abstract

A data-based mechanistic （DBM） modeling approach is used to model the statistical relationship between time-series reflectance and leaf area index （LAI）. This relationship model is referred to as LAI

BM model. Moderate Resolution Imaging Spectroradiometer （MODIS） data products are utilized as example data to implement DBM modeling and validation. LAI field measurements from the Bigfoot project were used to further validate LAI

BM model. The results show that LAI

BM model provid a very good explanation of the relationship between time-series reflectance and LAI. The LAI estimated by LAI

BM model is better than MODIS LAI in terms of data quality and continuity.