Use of ETM+ thermal band to identify irrigation patterns in the Aral Sea basin, Kazakhstan

Paraskevi Perdikou; Christopher Clayton; Diofantos Hadjimitsis

doi:10.1117/12.463088

17 March 2003 Use of ETM+ thermal band to identify irrigation patterns in the Aral Sea basin, Kazakhstan

Paraskevi Perdikou, Christopher Clayton, Diofantos Hadjimitsis

Proceedings Volume 4879, Remote Sensing for Agriculture, Ecosystems, and Hydrology IV; (2003) https://doi.org/10.1117/12.463088
Event: International Symposium on Remote Sensing, 2002, Crete, Greece

Abstract

Landsat TM thermal bands have generally not been used for land-use classification because of their inferior spatial resolution. But thermal band data is potentially useful, highlighting reductions in temperature associated with recent irrigation, and between the different stages of growth of the crops. This paper presents the results of a remote sensing study for land use classification, based upon Landsat 7 ETM+ data, aimed at estimating irrigation water demand on the basis of the areas cultivated with different types of crops, and local irrigation practices. A time series of images has been acquired for an area along the Syr Darya River (Kazakhstan), one of the two major rivers feeding the Aral Sea. Once the fourth largest inland sea in surface area in the world, the Aral Sea has been reduced to less than 20% of its original volume as a result of large-scale irrigation, causing extensive environmental damage. A rational method of managing irrigation is urgently required if the sea is to return to its former condition. This paper explores the use of the Landsat ETM+ thermal bands alongside those more commonly used for agricultural land classification. Strategies for determining irrigation water demand are discussed, and observations are compared with ground truth.

Citation Download Citation

Paraskevi Perdikou, Christopher Clayton, and Diofantos Hadjimitsis "Use of ETM+ thermal band to identify irrigation patterns in the Aral Sea basin, Kazakhstan", Proc. SPIE 4879, Remote Sensing for Agriculture, Ecosystems, and Hydrology IV, (17 March 2003); https://doi.org/10.1117/12.463088

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