Early-season crop area estimates for winter crops in NE Australia using MODIS satellite imagery

Potgieter, A. B., Apan, A., Hammer, G. and Dunn, P. (2010) Early-season crop area estimates for winter crops in NE Australia using MODIS satellite imagery. Isprs Journal of Photogrammetry And Remote Sensing, 65 4: 380-387. doi:10.1016/j.isprsjprs.2010.04.004


Author Potgieter, A. B.
Apan, A.
Hammer, G.
Dunn, P.
Title Early-season crop area estimates for winter crops in NE Australia using MODIS satellite imagery
Journal name Isprs Journal of Photogrammetry And Remote Sensing   Check publisher's open access policy
ISSN 0924-2716
Publication date 2010-07-01
Year available 2010
Sub-type Article (original research)
DOI 10.1016/j.isprsjprs.2010.04.004
Volume 65
Issue 4
Start page 380
End page 387
Total pages 8
Place of publication Netherlands
Publisher Elsevier BV
Language eng
Formatted abstract
To date, industry and crop forecasters have had a good idea of the potential crop yield for a specific season, but early-season information on crop area for a shire or region has been mostly unavailable. The question of “how early and with what accuracy?” area estimates can be determined using multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) imagery was investigated in this paper. The study was conducted for two shires in Queensland, Australia for the 2003 and 2004 seasons, and focused on deriving total winter crop area estimates (including wheat, barley and chickpea). A simple metric (View the MathML source), which measures the green-up rate of the crop canopy, was derived. Using the unsupervised k-means classification algorithm, the accumulated difference of two consecutive images (one month apart) for three EVI threshold cut-offs (View the MathML source, where i=250, 500 and 750) at monthly intervals from April to October was calculated. July showed the highest pixel accuracy with percent correctly classified for all thresholds of 94% and 98% for 2003 and 2004, respectively. The differences in accuracy between the three cut-offs were minimal and the T500 threshold was selected as the preferred cut-off to avoid measuring too small or too large fluctuations in the differential EVI values. When compared to the aggregated shire data (surveyed) on crop area across shires and seasons, average percent differences for the View the MathML source for July and August ranged from −19% to 9%. To capture most of the variability in green-up within a region, the average View the MathML source of July and August was used for the early-season prediction of total winter crop area estimates. This resulted in high accuracy (R2=0.96; RMSE = 3157 ha) for predicting the total winter crop from 2000 to 2004 across both shires. This result indicated that this simple multi-temporal remote sensing approach could be used with confidence in early-season crop area prediction at least one to two months ahead of anthesis.
Crown copyright © 2010 Published by Elsevier B.V.

Keyword Early-season
Crop area estimates
Simple metric
Multi-temporal
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2011 Collection
School of Agriculture and Food Sciences
 
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Created: Sun, 08 Aug 2010, 10:04:43 EST