A remote sensing study of the NDVT-Ts relationship and the transpiration from sparse vegetation in the sahel based on high-resolution satellite data

This article proposes a nara approach for estimation of the transpiration rate in sparse canopies. The method relies on a combination of techniques; some of which having a successful background of solid experimental and theoretical justification, while others having only recently been introduced as promising tools for the extraction of environmental information from satellite data. The transpiration rate (lambda E-v) is calculated by applying an energy balance approach to the vegetation component of the land surface: lambda E-v=R-n(v)-H-v, where R-n(v) is the net radiation absorbed by the vegetation, and H-v is the sensible heat flux between the leaves and the air within the canopy. R-n(v) is calculated through the use of remote sensing and standard meteorological data by combining a conventional method for estimation of the land surface net radiation with a ground-calibrated function of NDVI (normalized differential vegetation index). H-v is assessed as a linear function of the temperature difference between vegetation (T-v) and the mean canopy air stream (To) Because the surface temperature (T-s) recorded by satellite contains combined information of both soil and vegetation, T-v is evaluated on the basis of the linear NDVI-T-s relationship for individual surface types. T-0 is assessed utilizing recent evidence that (T-s-T-0) is linearly related to the difference in surface temperature and air temperature above the canopy (Ts-T-u), with the slope coefficient depending only on canopy structure. The method is tested using remote sensing data ranging from ground-based, airborne, and satellite recordings. The modeled transpiration rates compared well to measurements of sapflow data and latent heat fluxes recorded for a wide range of surface types (agricultural crops, natural vegetation, forest vegetation). (C) Elsevier Science Inc., 1999.