Methods For Using LST Retrieved By Satellite Remote-Sensings To Investigate Agroclimatical Thermal Distribution

Agroclimatic regionalization has been made through observational data over the last decades. However, the representative for a specific region keeps questionable because the surface meteorological stations are not enough to cover the region. In order to get regional distribution of agriclimatic thermal resource in Guangxi province, the day-time LST (Land Surface Temperature) was firstly estimated by using weather satellite remote-sensing technique.The spatial distribution of yearly and monthly day-time LST in clear sky was then imaged for the period from 1997 to 2000. The main conclusions are shown as follows.(1) An algorithm was established to calculate the day-time LST in Guangxi. Based on the theory of retrieving LST through satellite remote-sensing and the characters of semi-tropical climate, topography, vegetation and the NOAA/AVHRR data in Guangxi, the split-window algorithms for retrieving the LST from space, including the Kerr algorithm, the Becker & Li algorithm, the Qin algorithm, the Franca & Cracknell algorithm and some others, were analyzed and compared. The results suggested that the Becker & Li algorithm be suitable to retrieve the day-time LST in Guangxi.(2) The real-time LST images of Guangxi were obtained. Firstly, the system for receiving and disposing weather-satellite data provided by the National Satellite Meteorology Center was used to distill spectrum data of Channel-1, Channel-2, Channel-4 and Channel-5 from NOAA/AVHRR IB data, and the spectrum data were transferred to local area file by the method of projection. Secondly, the day-time-pixel LST was employed to the Becker&Li algorithm, and to convert the numerical LST value to grey. Thirdly, the real-time LST images of Guangxi were obtained.(3) The clear-sky day-time-averaged LST in Guangxi were imaged. To obtain the statistical boilerplate of LST according to the asymmetry distribution of cloud, we compared the images of the averaged temperature, which were respectively imaged by using satellite remote sensing and by using the general weather data, and analyzed the frequency of real-time LST figures by employing appropriate templets. The referenced standard of year-averaged LST was obtained by averaging these statistical boilerplate values. The result indicated that the real-time LST image was representative of thecon-esponding area in Guangxi. For the cloudy region, the pixel values were substituted by the image data of same period and close time after being calculated. The calculation was based on the correlation of clear sky image with cloudy. At last, clear-sky day-time-averaged LST image of Guangxi were made.(4) The distribution of thermal resource was characterized. The validity of averaged LST image was confirmed by comparing the temperature image with the regionalized image at the same period. Based on the validity, we analyzed the distribution character of thermal resources in Guangxi by using LST image. Comparing the results from mis research with the temperature image from the second agriclimatic regionalization, it is indicated that the LST image made by the satellite remote sensing in this research is more extensive, more particular and clearer than that from the second agroclimatic regionalization to express the distribution of thermal resource.