Abstract

Thermal camera,widely used in situ measurement of land surface temperature(LST),has an advantage of obtaining component brightness temperature.A simultaneous airborne,satellite-borne,and ground-based remote sensing field campaign was carried out in the Heihe River Basin of northwest China from May to July,2008.The radiative temperatures were obtained by two portable infrared radiometers and one thermal camera at the maize field patches around the weather station in Yingke Oasis Area with three different sampling schemes.Average temperatures of the field patches were extracted with those data.The thermal camera′s data was processed as: Firstly,maize and the soil were separated by statistical threshold of radiative temperatures in thermal images,and then their mean radiative temperatures were calculated,respectively.Secondly,with the LAB color space transform technique,the vegetation fraction of each field patch is estimated from visible photos taken simultaneously.Finally,each patch′s mean radiative temperature was obtained by the sum of the component temperatures of maize and soil weighted by vegetation fraction cover.By comparing of the mean radiative temperatures obtained by the thermal camera and portable radiometers sampling in cross-row and along-row direction,we found that their differences are small,and between-1 and +1.But,both maximum and minimum temperatures of the three methods differ a lot.By simulation on different reliability levels,we also obtained the numbers of randomly sampled points on different pixel scales.Our result indicates that it is difficult to obtain an accurate mean brightness temperature of filed patch with just only 1-2 portable radiometers based on the general point-based measure scheme.To get more accurate data for the validation of LST retrieved in different remote sensing pixel scales,new methods and instruments with high temporal and spatial sampling frequencies are required.

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