Journal
REMOTE SENSING OF ENVIRONMENT
Volume 154, Issue -, Pages 139-152Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2014.08.016
Keywords
Irrigation; Image classification; Remote sensing; Random Forest; Mapping
Funding
- CSIRO through a Divisional postdoctoral fellowship
- Water Information Research and Development Alliance (WIRADA)
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Globally, irrigation accounts for more than two thirds of freshwater demand. Despite their importance, the geographic distribution and water use of many important irrigated areas remains uncertain. This paper advances a methodology to map summer cropping irrigated areas experiencing extreme climate and different management practices in the Murray-Darling Basin (Australia). A Random Forest classification model was implemented to austral hemisphere summer irrigated areas for the water-years 2004/05 to 2010/11. The methodology used training samples from Landsat TM/ETM + reflectance data and monthly time-series of remotely-sensed observations from the MODerate resolution Imaging Spectroradiometer (MODIS). The covariates included in the classification model characterised the monthly dynamics and rates of change of: (i) the vegetation phenology via the recurrent and persistent absorbed fractions of photosynthetically active radiation (fPAR(rec), and fPAR(per), respectively); (ii) water use via remotely-sensed estimates of actual evapotranspiration (ETa), precipitation (P) and the difference between ETa and P. Observed agreement - in terms of the kappa coefficient - for correctly classified pixels in the training sample was 96%. Independent comparisons of yearly irrigated area estimates showed linear relationships with Pearson's correlation coefficients (r) generally greater than 0.7 for: (i) reported areas; (ii) areas with available metered water withdrawals; and (iii) estimates of agricultural yields. Sequential covariate optimisation suggested that the most important predictors to identify of irrigation areas included the emergence-senescence period (as determined by the fPAR(rec) and corresponding rates of change) and the ETa surplus over P during this period. The latter can be important when identifying supplementary irrigation due to periodically unreliable water supply in areas with otherwise high precipitation that are in-phase with summer crop growth. Crown Copyright (C) 2014 Published by Elsevier Inc All rights reserved.
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