A data-based mechanistic approach to time-series LAI modeling and estimation. [J]. Journal of Remote Sensing 16(3):505-519(2012) DOI: 10.11834/jrs.20121133.
A data-based mechanistic approach to time-series LAI modeling and estimation
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
D
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
D
BM model. The results show that LAI
D
BM model provid a very good explanation of the relationship between time-series reflectance and LAI. The LAI estimated by LAI
D
BM model is better than MODIS LAI in terms of data quality and continuity.
关键词
叶面积指数时间序列MODISDBM
Keywords
leaf area indextime-seriesMODISdata-based mechanistic (DBM)
Beijing Normal University, State Key Laboratory of Remote Sensing Science
Beijing Engineering Research Center for Global Land Remote Sensing Products/Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University
Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University
International Institute for Earth System Science, Nanjing University