ABSTRACT

Land surface temperature (LST) retrieval from thermal infrared (TIR) remote sensing image requires atmospheric and land surface emissivity (LSE) data that are sometimes unattainable. To overcome this problem, a hybrid algorithm is developed to retrieve LST without atmospheric correction and LSE data input, by combining the split-window (SW) and temperature–emissivity separation (TES) algorithms. The SW algorithm is used to estimate surface-emitting radiance in adjacent TIR bands, and such radiance is applied to the TES algorithm to retrieve LST and LSE. The hybrid algorithm is implemented on five TIR bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Analysis shows that the hybrid algorithm can estimate LST and LSE with an error of 0.5–1.5 K and 0.007–0.020, respectively. Moreover, the LST error of the hybrid algorithm is equivalent to that of the original ASTER TES algorithm, involving 1%–2% uncertainty in atmospheric correction. The hybrid algorithm is validated using ground-measured LST at six sites and ASTER LST products, indicating that the temperature difference between the ASTER TES algorithm and the hybrid algorithm is 1.4 K and about 2.5–3.5 K compared to the ground measurement. Finally, the hybrid algorithm is applied to at two places.

要从热红外（TIR）遥感图像检索地表温度（LST），需要有时无法获得的大气和地表发射率（LSE）数据。为了克服这个问题，通过组合分割窗口（SW）和温度-发射率分离（TES）算法，开发了一种混合算法来检索LST，而无需进行大气校正和LSE数据输入。SW算法用于估计相邻TIR波段中的表面发射辐射，并将这种辐射应用于TES算法以检索LST和LSE。混合算法是在先进星载热发射和反射辐射计（ASTER）的五个TIR波段上实现的。分析表明，混合算法可以估计LST和LSE的误差分别为0.5–1.5 K和0.007–0.020。此外，混合算法的LST误差与原始ASTER TES算法的LST误差相同，在大气校正中涉及1％–2％的不确定性。混合算法在六个站点使用地面测量的LST和ASTER LST产品进行了验证，表明与地面测量相比，ASTER TES算法和混合算法之间的温度差为1.4 K和约2.5-3.5K。最后，将混合算法应用于两个地方。