Land surface temperature retrieval from HJ-1B IRS supported by MODIS

HJ-1B (Huan Jing = Environment) IRS (Infrared Scanner) is one of the key instruments onboard HJ-1B satellite, launched by China in 2008. The 150m and 300m resolutions in four spectral bands wavelength ranging from near-infrared to thermal infrared, and the four days revisit period, make it attractive for researching the global change by providing the parameter of LST (Land Surface Temperature). LST retrieval requires a background value of Land Surface Emissivity (LSE). But for lack of a red band on HJ-1B IRS, LSE calculation faces a great challenge with the traditional methods. A method using the high quality data outputs of 16 days combined MODIS (MODerate Resolution Imaging Spectroradiometer ) NDVI (Normalized Difference Vegetation Index) was presented to calculate the LSE. To decrease the effect of pixels mismatch from two kinds of data, a method of Pixel Number Percentage Matching (PNPM) was proposed, this method matches the pixels of MODIS and HJ-1 IRS by counting the percentage of different level of NDVI. It can effectively decrease the LSE errors caused by the mismatch of two kinds of data. Two prevalent methods for LST deriving were chosen to calculate LST from HJ-1B IRS, one is developed by Qin and Karnieli, hereafter referred to as “QK&B”, the other is developed by Jiménez-Muñoz and Sobrin hereafter referred to as “JM&S”. LST retrieved from HJ-1 IRS was compared with MODIS LST products, which have been validated to have a high precision, result showed, that LST retrieved from HJ-1B IRS LST by the two algorithms are highly in conformity with the MODIS LST products.