Physically based retrieval of crop characteristics for improved water use estimates

Abstract

The increasing scarcity of water from local to global scales requires the efficient monitoring of this valuable resource, especially in the context of a sustainable management in irrigated agriculture. In this study, a two-source energy balance model (TSEB) was applied to the Barrax test site. The inputs of leaf area index (LAI) and fractional vegetation cover (fCover) were estimated from CHRIS imagery by using the traditional scaled NDVI and a look-up table (LUT) inversion approach. The LUT was constructed by using the well established SAILH + PROSPECT radiative transfer model. Simulated fluxes were compared with tower measurements and vegetation characteristics were evaluated with in situ LAI and fCover measurements of a range of crops from the SPARC campaign 2004. Results showed a better retrieval performance for the LUT approach for canopy parameters, affecting flux predictions that were related to land use.