## 1 Introduction  
China has relied primarily on coal as its energy source for a long time [1]. With rapid socioeconomic development, the demand for coal has consistently growth. Despite some efforts in industrial restructuring, eliminating outdated industrial capacities, and adjusting the energy structure adjustments having been implemented in recent years, the annual production of raw coal consistently remained at a high level from 3.50 to 3.90 billion tons [2, 3]. In China, open-pit mines are primarily located in the arid and semiarid northern regions, where the ecological conditions are poor. This exacerbates a series of secondary environmental issues in these areas, such as a decrease in soil moisture (SM) content and elevated surface temperatures [4; 5]. Therefore, the effectiveness of ecological restoration in mining areas directly impacts the nation's ecological security. Coal mining operations significantly disrupt vegetation and ecological systems surrounding the mining sites, leading to substantial losses in ecosystem services, such as vegetation degradation and soil nutrient depletion. SM plays a crucial role in vegetation growth and the land-atmosphere cycle [6; 7], and long-term coal mining operations in the mining areas have altered the original landforms and disrupted the surface hydrological environment, severely affecting the distribution of groundwater systems. In particular, in arid and semiarid regions, SM is a critical factor in the study of ecological restoration in mining areas [8; 9]. In general, SM monitoring methods primarily include field monitoring and remote sensing [10; 11]. Field monitoring methods are characterized by their flexibility and high accuracy, but they are time-consuming and labor-intensive, making large-scale continuous monitoring challenging [12; 13]. In contrast to traditional measurement methods, remote sensing offers the advantages of real-time, wide-area, and synchronous monitoring [14; 15]. Remote sensing techniques facilitate the monitoring of SM through microwave remote sensing [16; 17] or optical (visible and infrared) and thermal infrared remote sensing [18]. Microwave remote sensing is minimally affected by cloudy and foggy weather and has strong penetration capabilities [19; 20]. However, its spatial resolution is relatively coarse, which cannot meet the fine-scale monitoring requirements of small-scale mining areas [21; 22]. The use of radiometric measurements in the visible and infrared wavelengths has been suggested as a solution to overcome this problem. Optical remote sensing leverages the spectral reflectance of soil and the spectral characteristics of vegetation leaves, demonstrating significant potential for indirectly estimating SM at finer spatial resolutions [23]. In recent years, various methods have been investigated to combine vegetation and temperature indices for drought detection [24; 25], such as the temperature vegetation dryness index (TVDI) [26], the vegetation supply water index (VSWI) [27; 28], and soil vegetation atmosphere transfer (SVAT) [29; 30]. These indicators are crucial for evaluating and monitoring sustainable management in open-pit mining areas. Some scholars have used an improved TVDI to enhance the accuracy of SM inversion or to conduct the long-term monitoring and analysis of SM in mining areas, providing important guidance for the protection of the ecological environment in these areas [31]. The variation in SM around mining areas is influenced by a combination of factors, including natural conditions, mining activities, and other human activities. Recent studies have found that coal mining activities, including both underground and open-pit mining, significantly alter SM dynamics. Specifically, underground mining-induced subsidence leads to reductions in SM and nutrient content, increasing spatial variability [32; 33; 34]. Likewise, open-pit mining affects soil environments by disrupting soil water circulation in the aeration zone, which can further impact vegetation growth and recovery [35].