In preparation for Canada's launch of the RADARSAT-Constellation, this study examines the use of VV-VH intensities to estimate the Leaf Area Index (LAI) of corn. LAI is indicative of crop productivity. Two implementations of the Water Cloud Model performed equally well in estimating corn LAI over sites in Poland and Canada with correlation coefficients over 0.8 and Root Mean Square Errors and Mean Average Errors of 0.72-0.73 m2m-2 and 0.47-0.54 m2m-2, respectively. This research will continue to pull in data from other international sites. If results remain robust, a strong case can be made to use an integration of Sentinel-1 and RCM for operational crop condition monitoring.

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39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Department of Geography and Environmental Studies

McNairn, H. (Heather), Hosseini, M. (Mehdi), DIngle-Robertson, L. (Laura), Davidson, A. (Andrew), Mitchell, S, & Dabrowska-Zielinska, K. (Katarzyna). (2019). Retrieval of Crop Biophysical Parameters Using C-Band: Preparing for the Radarsat-Constellation. In International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 5847–5850). doi:10.1109/IGARSS.2019.8898936