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.
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
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BM model provid a very good explanation of the relationship between time-series reflectance and LAI. The LAI estimated by LAI
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BM model is better than MODIS LAI in terms of data quality and continuity.
LIU Wendi 中国科学院空天信息创新研究院 数字地球重点实验室;可持续发展大数据国际研究中心;中国科学院大学
LIU Liangyun 中国科学院空天信息创新研究院 数字地球重点实验室;可持续发展大数据国际研究中心;中国科学院大学
TANG Yijie 同济大学 测绘与地理信息学院
相关机构
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
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences
International Research Center of Big Data for Sustainable Development Goals