NDLI: A data-based mechanistic assimilation method to estimate time series LAI

Content Provider	IEEE Xplore Digital Library
Author	Hongmin Zhou Ping Chen Jindi Wang Shunlin Liang Libiao Guo Kai Zhang
Copyright Year	2013
Description	Author affiliation: State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China (Hongmin Zhou; Ping Chen; Jindi Wang; Shunlin Liang; Libiao Guo; Kai Zhang)
Abstract	In recent years, time series remote sensing data products have been assimilated into the coupled crop growth model and the radiative transfer model to improve the time series LAI estimation. However, due to the large number of input parameters to the crop growth model, the applications of the crop growth models for regional use is restricted. This paper proposed a data-based mechanistic assimilation method for estimation of the time series LAI from Moderate Resolution Imaging Spectroradiometer (MODIS) data. By coupling a revised universal data-based mechanistic model (LAI_UDBM) with a vegetation canopy radiative transfer model (PROSAIL), The proposed method applies the Ensemble Kalman Filter (ENKF) method to improve the estimation accuracy. Results indicate that the time series LAI estimated by this approach is superior to the MODIS LAI. Furthermore, because the model does not require the historical observation of every pixel, it is applicable over a wider range of uses.
Sponsorship	IEEE Geosci. Remote Sens. Soc.
Starting Page	2133
Ending Page	2136
File Size	3741225
Page Count	4
File Format	PDF
ISBN	9781479911141
ISSN	21536996
DOI	10.1109/IGARSS.2013.6723235
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-21
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data models MODIS Time series analysis Estimation Agriculture Reflectivity Remote sensing radiative transfer model LAI data-based mechanistic method data assimilation
Content Type	Text
Resource Type	Article

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