Remotely-Sensed Surface Temperature and Vegetation Status for the Assessment of Decadal Change in the Irrigated Land Cover of North-Central Victoria, Australia

Abstract

Monitoring of irrigated land cover is important for both resource managers and farmers. An operational approach is presented to use the satellite-derived surface temperature and vegetation cover in order to distinguish between irrigated and non-irrigated land. Using an iterative thresholding procedure to minimize within-class variance, the bilevel segmentation of surface temperature and vegetation cover was achieved for each irrigation period (Spring, Summer and Autumn). The three periodic profiles were used to define irrigation land covers from 2008–2009 to 2018–2019 in a key agricultural region of Australia. The overall accuracy of identifying farms with irrigated land cover amounted to 95.7%. Total irrigated land cover was the lowest (approximately 200,000 ha) in the 2008–2009 crop year which increased more than three-fold in 2012–2013, followed by a gradual decline in the following years. Satellite images from Landsat series (L-5, L-7 and L-8), Sentinel-2 and ASTER were found suitable for land cover classification, which is scalable from farm to regional levels. For this reason, the results are desirable for a range of stakeholders.