hotspot globally. Moreover, implementing CLQ evaluation and revealing its spatiotemporal changes can provide key information for stakeholders to understand and manage CLQ. Research on CLQ evaluation generally includes three steps: defining the CLQ, constructing a CLQ evaluation system, and grading CLQ evaluation results [10]. The definition of CLQ is the basis of evaluation, but there is currently no unified definition for the CLQ [11; 12]. In most previous studies, the soil quality or soil fertility of cultivated land received the greatest attention and has often been considered as equivalent to the CLQ [13; 14; 15]. However, cultivated land is a semi-artificial and semi-natural ecosystem, and the CLQ should be the integration of multiple qualities [16]. Therefore, some other elements of CLQ have gradually attracted attention, such as field management [17; 15], ecological environment [18; 19], and productivity [20; 21]. Because of the complexity of CLQ, it should be evaluated from multiple dimensions [10]. Constructing a scientific evaluation indicator system is helpful for reflecting the comprehensive characteristics of CLQ [22]. The Chinese government has always attached great importance to the protection and improvement of CLQ [23]. Therefore, a series of CLQ indicator systems has been proposed [24; 25; 26], which emphasizes the productivity capacity and ecological environment of cultivated land. Simultaneously, many scholars have also constructed a variety of evaluation indicator systems with different functions and purposes. The evaluation indicator systems developed in these studies are mainly characterized by soil quality/fertility [27; 28; 29], natural quality/conditions [30; 31; 32], utilization conditions [12; 33], productivity capacity [15; 21; 34], ecological environment [10; 18; 19], and economic level [12]. However, the quantification methods of these indicators in existing studies were not suitable for regional scales or cannot reflect the spatial details of CLQ. It is still a major challenge to obtain a large number of ground-measured data to evaluate CLQ at a large regional scale [35; 36]. To efficiently evaluate CLQ, remote sensing data with a wide coverage have been used to characterize some of the attributes of CLQ. For example, [PERSON] et al. [35] and [PERSON] et al. [37] used different vegetation indexes extracted from remote sensing images to represent the soil fertility and soil moisture of cultivated land. [PERSON] et al. [14] and [PERSON] et al. [38] evaluated soil quality using visible and near-infrared spectroscopy. [PERSON] et al. [34] used gross primary productivity (GPP) based on Moderate Resolution Imaging Spectroradiometer (MODIS) data to characterize the productivity of cultivated land. However, these studies mainly used remote sensing data to characterize a single attribute of the CLQ. Few studies have comprehensively evaluated the CLQ based on remote sensing data. In addition, the CLQ has obvious spatiotemporal heterogeneity [27]. It is crucial to reveal the spatiotemporal changes in the CLQ and to identify its main influencing factors to improve CLQ [11; 39]. [PERSON] et al. [40] revealed the spatiotemporal characteristics of the production function, ecological function, and social function of the cultivated land in Shenyang city. However, its spatial resolution was low (10 \(\times\) 10 km), resulting in the spatial details of CLQ being poorly displayed. [PERSON] et al. [27] carried out a study on the spatiotemporal evaluation of CLQ at a finer spatial scale (plot scale), but the authors assumed that there was no change in the CLQ grade during the study period. At present, there is still a lack of research on the spatiotemporal evaluation of CLQ at a fine spatial scale (e.g., 30 \(\times\) 30 m).