A Simple Real LST Reconstruction Method Combining Thermal Infrared and Microwave Remote Sensing Based on Temperature Conservation

Author:

Zhang Yunfei123,Li Xiaojuan123,Zhang Ke1,Wang Lan1,Cheng Siyuan1,Song Panjie1

Affiliation:

1. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

2. Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China

3. Laboratory Cultivation Base of Environment Process and Digital Simulation, Beijing 100048, China

Abstract

The land surface temperature (LST), defined as the radiative skin temperature of the ground, plays a critical role in land surface systems, from the regional to the global scale. The commonly utilized daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST product at a resolution of one kilometer often contains missing values attributable to atmospheric influences. Reconstructing these missing values and obtaining a spatially complete LST is of great research significance. However, most existing methods are tailored for reconstructing clear-sky LST rather than the more realistic cloudy-sky LST, and their computational processes are relatively complex. Therefore, this paper proposes a simple and effective real LST reconstruction method combining Thermal Infrared and Microwave Remote Sensing Based on Temperature Conservation (TMTC). TMTC first fills the microwave data gaps and then downscales the microwave data by using MODIS LST and auxiliary data. This method maintains the temperature of the resulting LST and microwave LST on the microwave pixel scale. The average Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R2 of TMTC were 3.14 K, 4.10 K, and 0.88 for the daytime and 2.34 K, 3.20 K, and 0.90 for the nighttime, respectively. The ideal MAE of the TMTC method exhibits less than 1.5 K during daylight hours and less than 1 K at night, but the accuracy of the method is currently limited by the inversion accuracy of microwave LST and whether different LST products have undergone time normalization. Additionally, the TMTC method has spatial generality. This article establishes the groundwork for future investigations in diverse disciplines that necessitate real LSTs.

Funder

Natural Science Foundation of China

Beijing Outstanding Young Scientist Program

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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