Sugarcane growth monitoring through spatial cluster and temporal trend analysis of radar and optical remote sensing images

Abstract

During the 2014-2015 sugarcane growth season in São Paulo, Brazil, a considerable dataset was acquired consisting of space-based remote sensing images from radar and optical sensors, together with intensive ground measurements. In this work, images from the Sentinel-1, Radarsat-2 and Landsat-8 satellites are used to test the effectiveness of satellite-based indicators in sugarcane growth monitoring. A two-fold hypothesis testing is applied, in order to find statistically significant emerging hot spots and cold spots, both in space and time. Especially the comparison of results from the radar and optical sensors gives an insight into the difference in capability of these sensors to detect spatial and temporal patterns and trends.