基于HJ-1B热红外数据的干旱区陆面温度反演与比较

Inversion and Comparison of Arid Land Surface Temperature Based On HJ-1B Thermal Infrared Data

基于HJ-1B卫星热红外数据,利用辐射传输方程法、单窗算法和普适性单通道算法3种单通道算法,对新疆干旱区的陆面温度进行反演,并利用MODTRAN 4.0模型对各算法进行了模拟验证。结果表明：3种算法都能得到较高精度的陆面温度反演结果,平均误差为-0.75-0.51 K,均方根误差（RMSE）为-0.17-0.13 K。与MODIS陆面温度产品的交叉比较验证表明,基于HJ-1B热红外数据的反演结果与基于MODIS数据的陆面温度产品之间的平均偏差为-1.88-0.83 K,均方根误差为3.8 K,确定系数大于0.8,具有较高的相关性。

Land surface temperature（ LST） is of great significance to the hydrology,ecology,environment,biogeochemical and global climate change research. Remote sensing can provide 2D land surface temperature distribution information,and can be quickly synchronously to obtain a large area of land surface temperature. Thermal remote sensing can quickly access to the LST data over a large area. Due to less atmospheric water content,LST retrieval from remote sensing data in arid areas is relatively less impacted by atmospheric condition,which enables the singlechannel algorithms achieve better inversion result. The HJ-1B satellite only acquires thermal data at a single channel,thus the comparison and assessment of the three mono-channel algorithms for LST retrieval are significant for either algorithm selection or usability test of the HJ-1B thermal data. In this study the radiative transfer equation algorithm,the mono-channel algorithm and the generalized single-channel algorithm were selected to retrieve the LST of the arid areas in Xinjiang based on the HJ-1B satellite thermal infrared images（ IRS4）. The results simulated by MODTRAN 4. 0 show that three inversion algorithms can achieve high accuracy of LST estimation from the HJ-1B /IRS4 image data in the Shihezi and surrounding areas,with an average error of-0. 75 to 0. 51 K,RMSE of-0. 17 to 0. 13 K,respectively. Comparison between the LST derived from the HJ-1B data using the three algorithms and the MODIS LST product,indicates that the average error is-1. 88-0. 83 K,and the root-mean-square error is 3. 8K with a higher determination coefficient of greater than 0. 8.