The spatial distribution of traditional villages is a key factor for rural revitalization and sustainable development. However, the rapid expansion of cities has resulted in the disappearance and decline of many traditional villages. Therefore, for the protection of traditional villages, it is necessary to analyze the spatio-temporal differentiation characteristics and driving factors. In this study, a total of 500 traditional villages were selected in Shaanxi Province. With the support of spatial analysis tools such as ArcGIS and Geo-detector, the spatial differentiation and its driving factors were analyzed. It was found that traditional villages showed a three-core distribution mode, indicating a typical aggregation distribution of tendency. In Shaanxi, the directional evolution of traditional villages was characterized by a spatial and temporal trajectory toward the north, and then towards the south. In addition, traditional villages existed in areas with underdeveloped economies, far from the cities and close to water sources, with an elevation over 500 m and a slope less than 25°. Traditional villages in Shaanxi Province are experiencing uneven spatio-temporal evolution due to regional cultural differences and uneven economic development in southern, central, and northern areas. It is possible to provide strategies for the development, protection, and utilization of traditional villages and promote the development of rural revitalization based on the traditional villages.

Traditional villages (TVs) are physical manifestations of traditional culture, and their spatial structure embodies the essence of regional culture. The spatial form of TVs in the Ando Tibetan area can be used to understand the historical evolution, turnover, and inheritance of traditional culture in the region. This study uses four typical TVs in the Huangnan Prefecture (HNP). Using the fractal theory, spatial syntax theory, GIS, and geomorphological statistical analysis, this study analyses the spatial morphology structure of TVs of the Huangnan Tibetans. Analyses are conducted from the perspectives of external morphology and internal structure. A quantitative system of spatial morphology of TVs is constructed. This study found that three out of the four sample villages in the HNP have high fractal values (>1.5046) and belong to the strongly structured agglomeration morphology regarding overall morphological characteristics. Furthermore, the public space patches exhibit a more complex spatial morphology and typical fractal characteristics. The morphological characteristics of the village boundaries in the four sample villages exhibit band-like, mass-like, and point-like characteristics. The types of belt and mass tend to point to Muhesha (MHS), JaJia (JJ), and Shuangpengxi (SPX), while Tufang (TF) does not exhibit a clear tendency. The over-spatial permeability of the village is poor, making it hard to perceive the overall space. The average depth, degree of integration, and village selection are concentrated in the central area and the primary and secondary roads. The geometrical center is the core of the village’s degree of integration. This study presents traditional Ando Tibetan villages’ complex and diverse spatial morphology, providing scientific references for their protection, development, and utilization.

During the molybdenite mining process, conveyor belts stretching for miles are used to transport ore between the blasting sites, crushing stations, and the concentrator plant. In order to ensure the safety and stability of the industrial production process, this paper introduces a foreign matter detection method based on deep learning for the belt conveyor. Aiming at the problems of insufficient feature extraction capabilities in existing machine vision-based foreign body detection methods and poor detection accuracy due to imbalanced positive and negative samples, an improved foreign body detection method for anchorless frame-type metal mine belt conveyors is proposed. This method introduces atrous convolution in the pooling layer to increase the receptive field of feature extraction and improve the ability of extracting feature details of foreign objects. By optimizing the ratio of positive and negative samples in the training process, the overall loss function value of the algorithm is reduced to ensure the accuracy of foreign body recognition. Finally, the improved model is trained after enhancing and labeling the sample dataset. The experimental results show that the average mean accuracy of foreign body detection (MAP) is 90.9%, better than existing methods. It can be used as an effective new method for detecting foreign objects on molybdenum mine belt conveyors.

The exploration of the coupling trend between urban agglomeration development (UAD) and land surface temperature (LST) expansion is of great significance, and it is of scientific value for the regulation of the thermal environment of urban agglomerations, the optimization of urban spatial planning, and the achievement of sustainable urban development. This study employs an array of remote sensing datasets from multiple sources—employing a multi-faceted approach encompassing an overall coupling situation analysis model, a coordination and evaluation system, a geographically weighted spatial autocorrelation algorithm, and landscape pattern quantification indicators—to explore the mutual feedback mechanism and spatial coupling characterization of LST and UAD in the Guanzhong Plain Urban Agglomeration (GZPUA). The results of the study can provide data support for urban spatial planning and thermal environment regulation. The results indicate the following findings: (1) In the GZPUA, the nighttime light (NTL) and land surface temperature (LST) centroids show a significant tendency toward approaching one another, with a spatial offset decreasing from 45.0 km to 9.1 km at the end, indicating a strengthening trend in the photothermal system’s coupling synergy. (2) The coordination of light and heat in the study area exhibits significant non-equilibrium development, with a dynamic trend of urban development space shifting towards the southwest. It confirms the typical regional response law of rapid urbanization. (3) The Moran’s I index of the photothermal system in the study area increased from 0.289 to 0.335, an increase of 15.9%. The proportion of “high–high” (H-H)/“low–low” (L-L)-type regions with clustering distribution of cold and hot spots reaches 58.01%, and their spatial continuity characteristics are significantly enhanced, indicating a significant trend of spatial structural integration between urban heat island effect and construction land expansion.

Rapid urbanization and global warming have led to a series of ecological and health problems caused by the deterioration of urban thermal environment (UTE). Using a comprehensive analysis of meteorological and remote sensing data for Shaanxi Province, a model of urban thermal differentiation (UTD) was developed, and the spatio-temporal characteristics of UTE in different regions were analyzed. Using the Geo-explore model, natural and socio-economic factors were chosen to explain the spatio-temporal distribution changes in UTE. The results showed that the UTD and Geo-explore models can be used to estimate spatio-temporal differentiation characteristics and change patterns of UTE. This method can describe UTE’s spatial distribution and change characteristics well, making it suitable for multiple-perspective evaluations. In Shaanxi Province, the spatio-temporal distribution of UTE shows a decreasing trend from south to north and east to west. After 2000, the UTD showed a relatively stable performance in the Southern, Central, and Northern regions. The atmospheric temperature (AT) varied greatly across regions due to different factors. UTE mitigation and improved urban design can be achieved using this method.

In the face of the dual challenges of global climate change and rapid urbanization, optimizing the ecosystem services of urban green spaces has become a key strategy for building resilient and sustainable cities. This is particularly crucial in ecologically fragile arid and semi-arid regions. To accurately assess the thermal regulation function of urban green spaces, this study selected 20 parks in Xi’an, China. Combining remote sensing and Geographic Information System (GIS) technology, we adopted four established cooling indicators—Park Cooling Area (PCA), Park Cooling Efficiency (PCE), Park Cooling Intensity (PCI), and Park Cooling Gradient (PCG)—to systematically evaluate the thermal regulation functions of urban parks and their landscape-driving mechanisms. The results indicated that the average cooling amplitude of the parks was 2.53 °C, with an effective influence distance reaching 323.9 m, exhibiting a significant spatial gradient decay. We found a non-linear trade-off between green space scale and efficiency: while large parks provided a wider absolute cooling range, small and medium-sized parks demonstrated higher efficiency per unit area. Furthermore, a blue-green synergistic configuration significantly enhanced the mitigation of the urban heat island effect. The study confirmed that Park Area (PA), Park Perimeter (PP), and the Normalized Difference Vegetation Index (NDVI) significantly promoted cooling effects, whereas landscape fragmentation inhibited ecological benefits. This study elucidates the comprehensive regulation mechanism of urban parks on the urban microclimate, providing planning guidance for implementing Nature-based Solutions (NbS) and achieving climate-adaptive development in arid and semi-arid cities within the context of urban renewal.