4.7 Article

Dynamic identification of summer cropping irrigated areas in a large basin experiencing extreme climatic variability

期刊

REMOTE SENSING OF ENVIRONMENT
卷 154, 期 -, 页码 139-152

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2014.08.016

关键词

Irrigation; Image classification; Remote sensing; Random Forest; Mapping

资金

  1. CSIRO through a Divisional postdoctoral fellowship
  2. Water Information Research and Development Alliance (WIRADA)

向作者/读者索取更多资源

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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