Abstract:

In order to timely and accurately retrieve land surface temperature changes from the remote sensing image data, to develop planting plan for Liaoning region, determine the structure of cultivation and provide technical support, the author took the Liaoning Province as the test field, measured the ground surface data with the EOS/MODIS thermal infrared remote sensed data and relevant practical and established the land surface temperature retrieval model. Split window algorithm using two-factor model and universal single-channel algorithm, Liaoning Province, the surface temperature inversion. Meteorological stations measured by the ground temperature and the temperature inversion to obtain the fitted regression equation, reuse of the temperature inversion simulate the real surface temperature. Comparison of the two algorithms, the author derived split-window algorithm was more suitable for the surface temperature of the Liaoning region inversion.