Monitoring Rice Agriculture in the Sacramento Valley, USA With Multitemporal PALSAR and MODIS Imagery

Abstract

Rice agriculture is an important crop that influences land-atmosphere interactions and requires substantial resources for flood management. Multitemporal acquisition strategies provide an opportunity to improve rice mapping and monitoring of hydroperiod. The objectives of this study were to 1) delineate rice paddies with Phased Array L-band Synthetic Aperture Radar (PALSAR) fine-beam single/dual (FBS/D) mode measurements and 2) integrate multitemporal, ScanSAR Wide-Beam 1 (WB1)- and Moderate Resolution Imaging Spectroradiometer (MODIS)- observations for flood frequency mapping. Multitemporal and multiscale PALSAR and MODIS imagery were collected over the study region in the Sacramento Valley, California, USA. A decision-tree approach utilized multitemporal FBS (HH polarization) data to classify rice fields and WB1 measurements to assess paddy flood status. High temporal frequency MODIS products further characterized hydroperiod for each individual rice paddy using a relationship between the Enhanced Vegetation Index (EVI) and the Land Surface Water Index (LSWI). Validation found the PALSAR-derived rice paddy extent maps and hydroperiod products to possess very high overall accuracies (95% overall accuracy). Agreement between MODIS and PALSAR flood products was strong with agreement between 85-94% at four comparison dates. By using complementing products and the strengths of each instrument, image acquisition strategies and monitoring protocol can be enhanced. The results highlight how the integration of multitemporal PALSAR and MODIS can be used to generate valuable agro-ecological information products in an operational context.