NDLI: A methodology for estimating Leaf Area Index by assimilating remote sensing data into crop model based on temporal and spatial knowledge

Content Provider	Springer Nature Link
Author	Zhu, Xiaohua Zhao, Yingshi Feng, Xiaoming
Copyright Year	2013
Abstract	In this paper, a methodology for Leaf Area Index (LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge. Firstly, sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona (SCE-UA) optimization method based on phenological information, which is called temporal knowledge. The calibrated crop model will be used as the forecast operator. Then, the Taylor’s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer (MODIS) multi-scale data, which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model (ACRM) model. The calibrated LAI result was used as the observation operator. Finally, an Ensemble Kalman Filter (EnKF) was used to assimilate MODIS data into crop model. The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products. The root mean square error (RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation (0.3795), and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265. All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.
Starting Page	550
Ending Page	561
Page Count	12
File Format	PDF
ISSN	10020063
Journal	Chinese Geographical Science
Volume Number	23
Issue Number	5
e-ISSN	1993064X
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2013-08-03
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	assimilation temporal and spatial knowledge Leaf Area Index (LAI) crop model Ensemble Kalman Filter (EnKF) Geography (general)
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Geography, Planning and Development

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