Land surface temperature (LST) is a key parameter when monitoring land surface processes. However, cloud contamination and the tradeoff between the spatial and temporal resolutions greatly impede the access to high-quality thermal infrared (TIR) remote sensing data. Despite the massive efforts made to solve these dilemmas, it is still difficult to generate LST estimates with concurrent spatial completeness and a high spatio-temporal resolution. Land surface models (LSMs) can be used to simulate gapless LST with a high temporal resolution, but this usually comes with a low spatial resolution. In this paper, we present an integrated temperature fusion framework for satellite-observed and LSM-simulated LST data to map gapless LST at a 60-m spatial resolution and half-hourly temporal resolution. The global linear model (GloLM) model and the diurnal land surface temperature cycle (DTC) model are respectively performed as preprocessing steps for sensor and temporal normalization between the different LST data. The Landsat LST, Moderate Resolution Imaging Spectroradiometer (MODIS) LST, and Community Land Model Version 5.0 (CLM 5.0)-simulated LST are then fused using a filter-based spatio-temporal integrated fusion model. Evaluations were implemented in an urban-dominated region (the city of Wuhan in China) and a natural-dominated region (the Heihe River Basin in China), in terms of accuracy, spatial variability, and diurnal temporal dynamics. Results indicate that the fused LST is highly consistent with actual Landsat LST data (in situ LST measurements), in terms of a Pearson correlation coefficient of 0.94 (0.97-0.99), a mean absolute error of 0.71-0.98 K (0.82-3.17 K), and a root-mean-square error of 0.97-1.26 K (1.09-3.97 K).
翻译:地表温度(LST)是监测地表进程的一个关键参数。然而,云层污染以及空间和时间分辨率之间的平衡极大地阻碍了获得高质量的热红外线遥感数据。尽管为解决这些困境做出了巨大努力,但仍难以得出同时的空间完整性和高空时空分辨率的LST估计值。地表模型(LSMs)可用于模拟无缝LST,具有高时间分辨率,但这通常伴随着低空间分辨率。在本文中,我们为卫星观测和LSM-3的精确度模拟LST数据提供了一个综合的温度聚变框架,用于在60米的空间分辨率和半小时分辨率下绘制无差距的LST。尽管全球线性模型(GloLMM)和地表温度周期(DTC)分别作为传感器和时间分辨率数据标准化的预处理步骤进行。LST、MMM(MID)和CFLS-S-Sloral-Sloral Floral-Seral-Seral-Seral-Servical Servical Serval-S,在中国的LS-Silal-S-Sil-Silal-Silental-Silal-Silal-de-Silvial-deal-deal-Sild-ILVismal-I)区域中,一个以Lmal-Sl-Sl-Sl-Sl-Sl-Sl-S-S-S-Sl-S-S-Sl-Sl-Sl-Sl-Sl-SUD-Sl-Sl-Sl-Sl-I-I-S.I-S-I-I-S-S-I-S-S-S-S-I-I-I-S-I-I-S-S-I-I-I-I-I-I-I-I-I-I-I-Sl-I-I-I-I-S-S-S-SI-S-S-S-S-I-S-S-S-I-I-S-I-S-S-S-S-S-S-I-I-S-I-S-S-I-I-I-I-I-I-I