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Assessing the relationship between shire winter crop yield and seasonal variability of the MODIS NDVI and EVI images

Fontana, D.C., Potgieter, A.B. and Apan, A. (2007) Assessing the relationship between shire winter crop yield and seasonal variability of the MODIS NDVI and EVI images. Applied GIS, 3 (7). ISSN 1832-5505

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Publisher URL: http://epress.monash.edu.au/contacts.html


Australian researchers have been developing robust yield estimation models, based mainly on the crop growth response to water availability during the crop season. However, knowledge of spatial distribution of yields within and across the production regions can be improved by the use of remote sensing techniques. Images of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, available since 1999, have the potential to contribute to crop yield estimation. The objective of this study was to analyse the relationship between winter crop yields and the spectral information available in MODIS vegetation index images at the shire level. The study was carried out in the Jondaryan and Pittsworth shires, Queensland , Australia . Five years (2000 to 2004) of 250m resolution, 16-day composite of MODIS Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images were used during the winter crop season (April to November). Seasonal variability of the profiles of the vegetation index images for each crop season using different regions of interest (cropping mask) were displayed and analysed. Correlation analysis between wheat and barley yield data and MODIS image values were also conducted. The results showed high seasonal variability in the NDVI and EVI profiles, and the EVI values were consistently lower than those of the NDVI. The highest image values were observed in 2003 (in contrast to 2004), and were associated with rainfall amount and distribution. The seasonal variability of the profiles was similar in both shires, with minimum values in June and maximum values at the end of August. NDVI and EVI images showed sensitivity to seasonal variability of the vegetation and exhibited good association (e.g. r = 0.84, r = 0.77) with winter crop yields.

Item Type:Article
Corporate Creators:Department of Employment, Economic Development and Innovation (DEEDI), Agri-Science, Crop and Food Science , Emerging Technologies
Business groups:Crop and Food Science
Additional Information:© Monash University E-Press
Keywords:Yield estimation models; remote sensing; wheat; barley
Subjects:Plant culture > Field crops > Grain. Cereals
Science > Statistics > Simulation modelling
Live Archive:29 Jan 2009 01:33
Last Modified:03 Sep 2021 16:43

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