Search Results (7)

Tourists’ near-field passive perception and identification in mountain areas faces challenges related to long distances, small targets, varied-pose scenarios, facial occlusion, etc. To address this issue, this paper proposes an innovative technical framework based on a face-to-body (F2B) two-step iterative method aimed at enhancing the passive perception and tracking of tourists in complex mountain environments by integrating and coordinating body features with facial features. The F2B technical framework comprises three main components: target feature acquisition, multi-feature coupled re-identification, and target positioning and tracking. Initially, the faces and bodies of tourists are extracted from real-time video streams using the RetinaFace and YOLOX models, respectively. The ArcFace model is then employed to extract the facial features of the target tourists, linking them with the faces detected by RetinaFace. Subsequently, a multi-feature database is constructed using the Hungarian algorithm to facilitate the automatic matching of the face and body of the same tourist. Finally, the Fast-ReID model and a spatial position algorithm are utilized for the re-identification of tourist targets and tracking their dynamic paths. Based on public and actual scene datasets, deployment and testing in the Yimeng Mountain Scenic Area have demonstrated that the accuracy index AP of the F2B model reaches 88.03%, with a recall of 90.28%, achieving an overall identification accuracy of approximately 90% and a false alarm rate of less than 5%. This result significantly improves the accuracy of SOTA facial recognition models in the complex environments of mountainous scenic spots. It effectively addresses the challenges associated with the low identification accuracy of non-cooperative targets in these areas through a ground video sensing network. Furthermore, it offers technical support for spatiotemporal information regarding near-field passive perception and path tracking of tourists in mountain scenic spots and showcasing broad application prospects. Full article

The collaborative use of camera near-field sensors for monitoring the number and status of tourists is a crucial aspect of smart scenic spot management. This paper proposes a near-field perception technical system that achieves dynamic and accurate detection of tourist targets in mountainous scenic areas, addressing the challenges of real-time passive perception and safety management of tourists. The technical framework involves the following steps: Firstly, real-time video stream signals are collected from multiple cameras to create a distributed perception network. Then, the YOLOX network model is enhanced with the CBAM module and ASFF method to improve the dynamic recognition of preliminary tourist targets in complex scenes. Additionally, the BYTE target dynamic tracking algorithm is employed to address the issue of target occlusion in mountainous scenic areas, thereby enhancing the accuracy of model detection. Finally, the video target monocular spatial positioning algorithm is utilized to determine the actual geographic location of tourists based on the image coordinates. The algorithm was deployed in the Tianmeng Scenic Area of Yimeng Mountain in Shandong Province, and the results demonstrate that this technical system effectively assists in accurately perceiving and spatially positioning tourists in mountainous scenic spots. The system demonstrates an overall accuracy in tourist perception of over 90%, with spatial positioning errors less than 1.0 m and a root mean square error (RMSE) of less than 1.14. This provides auxiliary technical support and effective data support for passive real-time dynamic precise perception and safety management of regional tourist targets in mountainous scenic areas with no/weak satellite navigation signals. Full article

Cableways have been widely used in industrial areas, cities, and scenic spots due to their advantages, such as being a convenient mode of transportation, time-saving, labor-saving, and low cost, as well as offering environmental protection. To ensure the safe operation of a cableway, based on the characteristic that the velocity of the cableway bracket is approximately zero in a static deformation monitoring environment, a deformation monitoring method called zero velocity update (ZUPT)-based GNSS/IMU tightly coupled algorithm with the constraint of the Earth’s rotation angular velocity was proposed. The proposed method can effectively solve the problem of a single GNSS being unable to output attitude, which is directly related to the status of wire ropes and cable cars. Meanwhile, ZUPT is used to restrain the Kalman filter’s divergence when IMU is stationary. However, the improvements of ZUPT on attitude are not obvious, so the constraint of the Earth’s rotation angular velocity was applied. The performance of the proposed method was evaluated through monitoring the cableway bracket of the Yimeng Mountain Tourism area in Shandong. Compared with the ZUPT-based GNSS/IMU tightly coupled algorithm (ZUPT-TC), the proposed method can further constrain the error accumulation of IMU while stationary and, therefore, it can provide reliable position and attitude information on cableway brackets. Full article

Non-homogeneous soil’s high gravel content (also known as the “soil-rock dual structure”) may render it more prone to erosion and the significant development of gullies. In order to reveal the morphological characteristics and erosion rate of gullies in “soil-rock dual structure” areas, this study focused on the Shagou Reservoir basin in the Yimeng mountain area as the study area. Based on a complete digital orthophoto map (DOM, 0.03 m) and a digital elevation model (DEM, 0.03 m) acquired by an unmanned aerial vehicle (UAV), the researchers calculated the length (L), top width (TW), depth (D), area (A) and volume (V) of 19 gullies and built and optimized the volume estimation model. The DOM and the DEM were used to modify the morphological parameters of 43 gullies extracted from high-resolution remote sensing (RS) stereopair images (Worldview, 0.5 m), and the development and evolution of gully erosion were evaluated in large scale. The results showed that: (1) after correction, the average relative errors of parameters L, TW, D and A computed from the UAV data and the high-resolution RS stereopair image data fell below 0.005%; (2) the mean of TW/D was 5.20, i.e., the lateral erosion development of gullies far outweighed the downcutting erosion. The retrogressive erosion, lateral erosion and downcutting erosion rates of gullies were 0.01~0.83 m/a (averaged at 0.23 m/a), 0.01~0.68 m/a (averaged at 0.25 m/a) and 0.01~0.19 m/a (averaged at 0.09 m/a), respectively, between 2014 and 2021; (3) the volume-area (V-A) model for gullies is the optimal one (p < 0.01, R² = 0.944).A total of 90.7% of the gully volume was growing at an erosion rate of 0.42~399.39 m³/a and the total erosion rate of the gullies was 3181.56 m³/a from 2014 to 2021. These research findings can serve as a basis for the quantitative modeling of gully erosion in water-eroded locations with a large-dimension “soil-rock dual structure”. Full article

Analyzing cultivated land input behavior (CLIB) at the scale of rural households links with cultivated land-use efficiency (CLUE), this study examined the Yimeng Mountain area in northern China, supported by field survey data from 737 rural households. This research systematically analyzed the characteristics of CLIB of different types of rural households, measured the CLUE of different types of rural households by using a data envelopment analysis (DEA) model, and explored the influence of CLIB on CLUE based on the Tobit regression model. The results show (1) significant differences in the characteristics of the CLIB of different types of rural households in the Yimeng Mountain area. Among them, the highest land, labor, and capital inputs were I part-time rural households (I PTRH), followed by full-time rural households (FTRH). In contrast, II part-time rural households (II PTRH) and non-agricultural rural households (NARH) had higher levels of non-agricultural employment; however, their input levels gradually declined. (2) The CLUE of the sample rural households was generally low and had considerable potential for improvement. Regarding the types of rural households, as the degree of part-time employment increased, the CLUE showed an inverted U-shaped trend of first increased and then decreased, namely, I PTRH > FTRH > II PTRH > NARH. This finding indicates that appropriate part-time employment could help to promote investment in agricultural production and improve the CLUE. (3) The CLIB of rural households had significant effects on CLUE; the literacy of the agricultural labor force, yield-increasing input per unit area, per capita household income, share of agricultural income, operation scale of cultivated land, effective irrigation rate of cultivated land, and soil and water conservation rate of cultivated land had positive effects on improving CLUE. Even so, there was still significant heterogeneity in the degree of influence of different rural household types. The study concluded with some policy recommendations from the perspective of different rural household types to provide references for optimizing farming inputs and improving CLUE. Full article

Using typical counties in the Yimeng Mountain area of northern China as an example, this paper analyzed the household and agricultural input characteristics of different types of peasant households using survey data from 262 farm households. The target minimization of the total absolute deviations (MOTAD) model was applied to determine the optimal combinations in the allocation of agricultural input factors and production for different types of at-risk peasant households to obtain the ideal agricultural income. The relevant results are twofold. (1) The agricultural input behaviors of different types of peasant households vary significantly. The highest levels of agricultural land, labor, and yield-increasing and labor-saving inputs included I part-time peasant households (I PTPH), followed by full-time peasant households (FTPH), while the input levels of II part-time peasant households (II PTPH) and non-agricultural peasant households (NAPH) with higher levels of non-agricultural employment gradually decreased. In general, an increase in peasant households’ part-time employment revealed an inverted U-shaped trend in the agricultural input level, with a trajectory of I PTPH > FTPH > II PTPH > NAPH. (2) The current agricultural inputs and production combinations of different types of peasant households have room for improvement. It is necessary to adjust agricultural inputs and optimize production combinations to obtain target incomes. Overall, all types of peasant households must streamline labor inputs and increase capital inputs, except for I PTPH, for which capital inputs should be reduced. Following optimization, economic crops gradually replace grain crops, and the optimal agricultural incomes of peasant households will be improved. The study results provide practical policy insights for reducing agricultural production risks and improving agricultural production incomes. Full article

Soil extracellular enzymes are considered key components in ecosystem carbon and nutrient cycling, and analysing their stoichiometry is an effective way to reveal the resource limitations on soil microbial metabolism. In this study, the soil and litter of Quercus acutissima plots, Pinus thunbergii plots, Quercus acutissima–Pinus thunbergii mixed-plantation plots, herb plots, and shrub plots in the state-owned Dawa Forest Farm in the Yimeng Mountain area were studied. The total carbon (C), nitrogen (N), and phosphorus (P) contents of litter and the physical and chemical properties of soil were analyzed, along with the activities of four extracellular enzymes related to the soil C, N, and P cycle: β-1,4-glucosidase (BG), β-1,4-N-acetylglucosaminidase (NAG), L-leucine aminopeptidase (LAP), and acid phosphatase (AP). The extracellular enzyme stoichiometric model was used to study and compare the metabolic limitations of soil microorganisms in different plots, and the driving factors of microbial metabolic limitations were explored by redundancy and linear regression analyses. The results showed that the values of BG/(NAG + LAP) were all higher than 1, the values of (NAG + LAP)/AP all lower than 1, and the vector angles of the five plots all greater than 45°, which indicated that the soil microorganisms were relatively limited by C and P. Redundancy and linear regression analysis revealed that soil physical properties (e.g., soil moisture) and litter total C make greater contributions to soil extracellular enzymes and stoichiometry than the other investigated soil parameters, whereas soil chemical properties (e.g., soil organic C and available P) predominantly controlled vector properties. Therefore, microbial metabolism limitations are greatly regulated by soil physical and chemical properties and litter total C and N. Compared with the forest plots, the soil microbial C (1.67) and P (61.07°) limitations of herb plots were relatively higher, which means that the soil microbial communities of forest plots are more stable than those of herb plots in the Yimeng Mountain area. Forest plots were more conducive than other plots to the improvement of soil microbial ecology in this area. This study could be important for illuminating soil microbial metabolism and revealing soil nutrient cycling in the Yimeng Mountain area ecosystem of China. Full article