Method For Retrieval Of Land Surface Temperature From NPP-VIIRS Thermal Infrared Data

Land surface temperature(LST)is an important index to study the physical change process of land surface at the regional or global scale.It has been widely used in meteorology,geology,ecology,hydrology and other research fields.Accurately and efficiently obtaining surface temperature data is of great significance for global climate change,agricultural drought monitoring and meteorological forecasting.With the rapid development of remote sensing technology,surface-temperature data with high spatial-temporal resolution can be obtained on a large scale from Earth observation satellites.The National Polar-orbiting Partnership(NPP)satellite is a new generation of Earth observation system operated by the United States and was launched on October 28,2011.The Visible Infrared Imaging Radiometer Suite(VIIRS)is an important sensor mounted on the NPP satellite and is mainly used to detect surface,ocean and atmosphere.Compared with other satellite data,VIIRS has higher spatial resolution and can acquire thermal infrared images with a resolution of 750 meters,providing a new data source for surface temperature inversion research.The split window algorithm is the most common method for inversion of surface temperature.It mainly uses two thermal infrared channels to invert the surface temperature.After years of research and improvement,it has developed various forms of split window algorithms.Since few people used the VIIRS data for comparative analysis of multiple split-window algorithms in the past,this paper uses the two thermal infrared channel data of M15 and M16 on the VIIRS sensor to calculate the radiance and the brightness temperature,using multiple forms of split window algorithms.Inversion obtained multiple sets of surface temperature data,and then verified the results with measured data from two field observation sites in Hailar and Urad Front Banner.The accuracy of each algorithm was compared and the algorithm with higher inversion accuracy was obtained.At the same time,aiming at the problem that the inversion accuracy of VIIRS surface temperature products is not high,an alternative method for inversion of surface temperature is proposed.The main findings are as follows:(1)Based on the radiation transmission model and the atmospheric profile database,the coefficients of the split-window algorithm under different conditions are obtained through simulation,and the simulation accuracy between the algorithms is compared.The accuracy of each algorithm under the vertical observation conditions is 1.3 K.The BL95 has the highest inversion accuracy,reaching 0.45 K.Overall,the accuracy of the quadratic term algorithm is higher than that of the linear formal algorithm.In some cases,adding the water vapor term can improve the accuracy of the algorithm.(2)Using actual satellite data,the ground surface emissivity is inferred by the NDVI threshold method,and the surface temperature data is finally calculated.The accuracy of the surface temperature obtained by inversion is compared with the actual measured data of field stations.The results show that the inversion accuracy of the split-window algorithm is higher in regions with high vegetation coverage and lower in bare soil coverage.In Hailar region,the BL95 algorithm has the highest inversion accuracy,which can reach 1.23 K.In Urad Front Banner region,the inversion accuracy of each algorithm is generally poor.The error of PR84 algorithm can reach 3.66 K.But the error of BL95 algorithm is the smallest,which is 1.66 K.(3)Through the field measurement data,the accuracy of surface temperature products issued by VIIRS was compared and verified,and the accuracy was found to be poor.In regions with high vegetation coverage,the accuracy of the error was 2.51 K.In the bare soil region,the accuracy error was 5.75 K.Aiming at the defects of the VIIRSsurface temperature product algorithm,this paper proposes an alternative method for inversion of surface temperature.Surface emissivity was estimated according to the Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)Global Emissivity Dataset(GED)product.Compared with the measured data,the accuracy of the surface temperature data obtained by inverting the method proposed in this paper is higher,with an accuracy of 1.10 K in the vegetation coverage area and an accuracy of 1.71 K in the bare soil coverage area.The results show that this method is significantly better than the algorithm used for the released VIIRS surface temperature product.