Dynamics Simulation Of Angular Effects On The Forest Canopy Temperature Observed By Remote Sensing Methods

Land surface temperature (LST) is an important variable in the interchange process of energy and mass between surface and atmosphere, which has great significance for global climate change, forest fire and drought monitoring and so on. Thermal infrared remote sensing is most commonly used for surface temperature extraction. However, the observed land surface temperature from remote sensing is usually the mixed product of various ground objects with a complex spatial distribution. There exists prominent angular effects and temporal and spatial variation characteristics, thus becomes an important factor that affects the accuracy of temperature retrieving in pixel scale. It is the only way to solve the angular effects, if we can make clear angular variations of surface temperature observed by remote sensing, which thus can help to improve the forest resources monitoring ability.Taking forest canopies as examples, the temporal and spatial distribution of component temperature and directional brightness temperature (DBT) in the forest microclimate environment were studied with three-dimensional thermal radiative transfer model and three-dimensional microclimate model. The main results are as following:1) The field experimental data of Dongsheng Bajia country park in Haidian district, Beijing and Huailai remote sensing test site in Hebei province were used to support the calibration and accuracy validation of component temperature of ENVI-met model. The comparison between simulation and observation show that ENVI-met can effectively simulate the 3-D spatial distribution (R2≈0.93, RMSE ≈2.1 K) and diurnal variation of LS component temperature. The model can be effectively extended in complex vegetation scenes. However, we also found a few limitations of ENVI-met, including low running efficiency, semi-fixed meteorological data, and lower temperature difference.2) We coupled ENVI-met and RAPID via the key parameter of component temperature, which is scaled up to directional brightness temperature. The thermal extension module of RAPID was used to simulate the directional brightness temperature in pixel scale. And the simulation accuracy was validated with different thermal sensor images of Multi-resolution. The results show that coupling model can simulate high resolution surface temperature images and corresponding directional brightness temperatures (R2>0.90, RMSE<2.5 K).3) ENVI-met and RAPID models were linked to simulate the temporal and spatial variations of surface thermal emission directivity (TED). The results show that, for tall forest canopies in typical forest environment, DBT differences between view zenith angle of 0 and 55 deg are mostly lower than zero, which has obvious diurnal and seasonal variations. The diurnal variation of thermal emission directionality exist apparent peak value in summer days, while the linear trend is even more obvious for the other three seasons. The law still needs to be verified in other more complex scenes.4) A forecasting method was proposed based on global numerical forecast product NCEP, optical image and Lidar data. The coupling model and forecasting method can theoretically estimate TED in any vegetated area, which provides prior knowledge to correct the directionality TIR images.