Articles | Volume 19, issue 1
https://doi.org/10.5194/hess-19-507-2015
https://doi.org/10.5194/hess-19-507-2015
Research article
 | 
28 Jan 2015
Research article |  | 28 Jan 2015

Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

P. Karimi and W. G. M. Bastiaanssen

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Cited articles

ABS – Australian Bureau of Statistics: Water Account, Australia – 2000–01, Canberra, 2004.
Abd El-Kawy, O. R., Rød, J. K., Ismail, H. A., and Suliman, A. S.: Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data, Appl. Geogr., 31, 483–494, https://doi.org/10.1016/j.apgeog.2010.10.012, 2011.
Aguirre-Gutiérrez, J., Seijmonsbergen, A. C., and Duivenvoorden, J. F.: Optimizing land cover classification accuracy for change detection, a combined pixel-based and object-based approach in a mountainous area in Mexico, Appl. Geogr., 34, 29–37, https://doi.org/10.1016/j.apgeog.2011.10.010, 2012.
Allen, R. G., Pereira, L., Raes, D., and Smith, M.: Crop evapotranspiration: guidelines for computing crop water requirements, Issues 56–57, Food and Agriculture Organization of the United Nations, Rome, Italy, 1998.
Allen, R. G., Tasumi, M., Morse, A., and Trezza, R.: A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning, Irrig. Drain. Syst., 19, 251–268, https://doi.org/10.1007/s10795-005-5187-z, 2005.