Net ecosystem productivity (NEP) is an important indicator for estimating regional carbon sources/sinks. The study focuses on a comprehensive computational simulation and spatiotemporal variation study of the NEP in the Yellow River basin from 2000 to 2020 using NPP data products from MODIS combined with a quantitative NEP estimation model followed by a comprehensive analysis of the spatiotemporal variation characteristics and dynamic procession persistence analysis based on meteorological data and land use data. The results show that: (1) The total NEP in the Yellow River basin had an overall increasing trend from 2000 to 2020, with a Theil–Sen trend from −23.37 to 43.66 gCm⁻²a⁻¹ and a mean increase of 4.64 gCm⁻²a⁻¹ (p < 0.01, 2-tailed). (2) Most areas of the Yellow River basin are carbon sink areas, and the annual average NEP per unit area was 208.56 gCm⁻²a⁻¹ from 2000 to 2020. There were, however, substantial spatial and temporal variations in the NEP. Most of the carbon source area was located in the Kubuqi Desert and its surroundings. (3) Changes in land use patterns were the main cause of changes in regional NEP. During the 2000–2020 period, 1154.24 t of NEP were added, mainly due to changes in land use, e.g., the conversion of farmland to forests and grasslands. (4) The future development in 83.43% of the area is uncertain according to the Hurst index dynamic persistence analysis. In conclusion, although the carbon−sink capacity of the terrestrial ecosystem in the Yellow River basin is increasing and the regional carbon sink potential is increasing in the future, the future development of new energy resources has regional uncertainties, and the stability of the basin ecosystem needs to be enhanced.

To protect and restore this downstream ecosystem, the Tarim River Basin Administration Bureau (TBAB) initiated the Ecological Water Compensation (EWC) project from 2000 to 2018. Revealing the mechanism of vegetation-hydroecological response processes in the lower reaches of the Tarim River before and after EWC work is conducive to water resource planning, utilization and protection. In this paper, the spatiotemporal responses of vegetation and groundwater to EWC were examined at the points, lines, and area (PLA) scale by coupling remote sensing techniques and field station observation data collected between 2000 and 2017. The findings indicated that (1) In general, the regional fractional vegetation coverage (FVC) increased significantly, and the average FVC growth rate was 3.5%/year from 2000 to 2017 (R² > 0.84, p < 0.01, 2-tailed). (2) The regional vegetation restoration process showed obvious fluctuations and stage characteristics, but the spatial scope of the significantly increased vegetation area was limited. Plants grew rapidly within 10 km of the river, while 10 km away from the water channel, no obvious change was observed. (3) Strong coupling relationships were identified among the FVC growth, EWC volume and groundwater depth variations (p < 0.05, 2-tailed). The response times of the regional vegetation and groundwater depth to EWC indicated one-year lags. The above results imply that the regional ecological environment was significantly improved over the study period, thus confirming that the EWC project made remarkable accomplishments. However, the effect of ecological restoration is not sufficiently stable at present. Vegetation restoration has mainly been centralized around the river channel and is greatly dependent on the annual EWC volume. In addition, the local conditions begin to degrade soon after an EWC project is terminated, and vice versa; when EWC commences, the FVC immediately begins to improve. Therefore, the current EWC achievements need to be further consolidated and strengthened in the future.

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.

As the most extensive terrestrial ecosystem, grassland exhibits substantial ecological functions and scientific research significance. Conducting a scientific assessment of the soil fertility of grasslands is of paramount importance for attaining sustainable grassland management, especially for the Tibetan Plateau, which has the most vulnerable ecosystem. This study endeavors to evaluate the soil fertility and spatial differentiation patterns of the natural grasslands in the Tibetan Plateau. Initially, we developed a Soil Fertility Evaluation Index (SFEI) for natural grasslands by integrating three representative soil indicators (total nitrogen, soil organic matter, and bulk density) and a vegetation indicator (fractional vegetation cover). The selection of these indicators followed the Minimum Data Set (MDS) principle, ensuring both ecological relevance and consistent data availability across all sampling plots in the Tibetan Plateau. Subsequently, validation based on field sampling data showed an overall accuracy of 69.89%. Moreover, the evaluation result revealed a clear eastward-increasing gradient in soil fertility, with low fertility in the western regions (e.g., Ngari and Nagqu) and medium-to-high fertility in the central and eastern regions (e.g., Lhasa, Yushu, and Golog), consistent with regional hydrothermal patterns. The proposed method offers a novel and practical framework for assessing soil fertility of natural grassland in the Tibetan Plateau, with significant implications for differentiated grassland management and ecological restoration.