Determination of regional distribution of crop transpiration and soil water use efficiency using quantitative remote sensing data through inversion

A two-layer model used to get the estimated values of crop transpiration by inversion using remote sensing data, which has been proved effective at some agricultural-ecological stations, is first discussed. An important part of it is the temperature separation model (in which the surface temperature in a mixed pixel is separated into soil surface temperature and crop canopy surface temperature) on the basis of bi-temporal radiometric temperature in a mixed pixel and its thermal inertia. To improve the inversion, the authors put forward some new algorithms, including an algorithm for the estimation of regional emissivities, a static feedback algorithm using surface temperature for the extension of air temperature at ecological stations to the region surrounding them and a spatial extension algorithm for calculating the wind speed 2 m above the ground with surface roughness and radiometric temperature. Finally, regional distributions of crop transpiration (CT) and soil water use efficiency (SWUE) in North China were calculated pixel by pixel using NOAA-AVHRR data and surface measurements and calibrations. The results provide a way to assess the effects of various agricultural practices on SWUE by using remote sensing data in North China in spring.