Use of data assimilation technique for improveing the retrieval of leaf area index in time-series in alpine wetlands

Author

Quan, Xingwen ; He, Binbin ; Xing, Minfeng

Author_Institution

Sch. of Resources & Environ., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

fYear

2012

fDate

22-27 July 2012

Firstpage

754

Lastpage

756

Abstract

Leaf area index (LAI) is one of the key vegetation indices for many biological and physical processes in plant canopies. In this study, an assimilation technique was used to simulate the LAI´s varying in time series in an alpine wetland located in western China. The Terra MODIS 16 day composite surface reflectance products at 250 m resolution in 2010 with high quality were used. LAI was retrieved based on the ACRM canopy reflectance model and LUT algorithm. An experiential LOGISTIC model was fitted using the retrieved LAI, and the ensemble Kalman filter algorithm was introduced to assimilate the estimated LAI into the LOGISTIC model to update the model state.

Keywords

Kalman filters; data assimilation; time series; vegetation; vegetation mapping; ACRM canopy reflectance model; LUT algorithm; Terra MODIS; alpine wetland; assimilation technique; biological processes; composite surface reflectance products; data assimilation technique; ensemble Kalman filter algorithm; experiential LOGISTIC model; leaf area index; physical processes; plant canopies; time series; vegetation indices; western China; Data models; Heuristic algorithms; Indexes; Logistics; Reflectivity; Remote sensing; Time series analysis; Alpine wetlands; Data assimilation; LOGISTC model; Leaf area index; ensemble Kalman filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International

Conference_Location

Munich

ISSN

2153-6996

Print_ISBN

978-1-4673-1160-1

Electronic_ISBN

2153-6996

Type

conf

DOI

10.1109/IGARSS.2012.6351455

Filename

6351455