Spatio-temporal prediction of leaf area index of rubber plantation using HJ-1A/1B CCD images and recurrent neural network

Author:

Chen Bangqian,Wu Zhixiang,Wang Jikun,Dong Jinwei,Guan Liming,Chen Junming,Yang Kai,Xie Guishui

Funder

Danzhou Investigation & Experiment Station of Tropical Crops, Ministry of Agriculture, P.R. China

Earmarked Fund for China Agriculture Research System

Fundamental Research Funds for Rubber Research Institute

Natural Science Foundation of Hainan Province

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference69 articles.

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2. Neural network estimation of LAI, fAPAR, fCover and LAIxCab, from top of canopy MERIS reflectance data: principles and validation;Bacour;Remote Sens. Environ.,2006

3. Beale, M.H., Hagan, M.T., Demuth, H.B., 2011. Neural Network Toolbox User’s Guide. MathWorks Inc., Natick, MA. .

4. Comparison of regression and geostatistical methods for mapping leaf area index (LAI) with Landsat ETM+ data over a boreal forest;Berterretche;Remote Sens. Environ.,2005

5. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density;Broge;Remote Sens. Environ.,2000

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