Crop yield prediction using multipolarization radar and multitemporal visible / infrared imagery

Wilkinson, Graeme G and Davies, I. C. (2006) Crop yield prediction using multipolarization radar and multitemporal visible / infrared imagery. Glyndŵr University Research Online.

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Abstract

This paper describes research undertaken on the improvement of within-field late season yield forecasting for crops such as wheat using multi-temporal visible/infrared satellite imagery and multi-polarization radar satellite imagery. Experiments have been carried out using ASAR imagery from Envisat combined with nine bands of ASTER imagery from the NASA Terra satellite. An experimental test site in an agricultural area in the county of Lincolnshire, UK, has been used. The satellite imagery has been integrated using artificial neural networks which have been trained as predictors of the spatial distributions of yield per unit area in a variety of fields. Ground truth data in the form of yield maps from GPS-enabled combine harvesters have been used to train the neural networks and to evaluate accuracy. The results show that the combinations of ASTER and ASAR imagery can provide enhanced yield predictions with overall correlations of up to 0.77 between predicted and actual yield patterns. The results also show that the use of dual polarization radar data alone is not sufficient to give reasonable yield predictions even in a multi-temporal mode. It has also been shown that varying the architectures of the neural networks with ensembles can improve the overall results.

Item Type: Other
Additional Information: ©Copyright 2009 SPIE Society of Photo'Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.This paper was given at the SPIE Conference 6359 Remote Sensing for Agriculture, Ecosystems, and Hydrology VIII conference in Stockholm in september 2006. The SPIE conference paper is available at http://dx.doi.org/10.1117/12.689955
Keywords: Agriculture, remote sensing, yield prediction, radar imagery, multi-temporal data, multi-polarization.
Divisions: ?? GlyndwrUniversity ??
Depositing User: ULCC Admin
Date Deposited: 05 Oct 2011 09:13
Last Modified: 11 Dec 2017 20:05
URI: http://glyndwr.repository.guildhe.ac.uk/id/eprint/97

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