The accurate measurement of diameter at breast height (DBH) is one of the essential tasks for biomass estimation at an individual tree scale. This paper aims to explore the potential of unmanned aerial vehicle (UAV) based light detection and ranging (LiDAR) for trunk point extraction and direct DBH measurement. First, the trunk point cloud for each tree is extracted based on UAV LiDAR data by the multiscale cylindrical detection method. Then, the DBH is directly measured from the point cloud via the multiscale ring fitting. Lastly, we analyze the influence of scanning angle and mode on trunk point extraction and DBH measurement. The results show that the proposed method can obtain high accuracy of trunk point extraction and DBH measurement with real (R² = 0.708) and simulated (R² = 0.882) UAV LiDAR data. It proves that the UAV LiDAR data is feasible to directly measure the DBH. The highest accuracy was obtained with the scanning angles ranging from 50 to 65 degrees. Additionally, as the number of routes increases, the accuracy increases. This paper demonstrates that the UAV LiDAR can be used to directly measure the DBH, providing the scientific guidance for UAV path planning and LiDAR scanning design.

Tropospheric delay is one of the key factors that may affect high-precision satellite navigation and positioning and water vapor retrieval performance. Its variation in the vertical direction is much greater than that in the horizontal direction. Therefore, the vertical profile model of zenith total delay (ZTD) is important for the spatial interpolation of high-precision ZTD products and the development of ZTD models. However, in China, low spatial and temporal resolutions remain persistent in ZTD vertical profile models and limit their application. In this study, ZTD vertical profile grid models (CZTD-H model: CZTD-HM and CZTD-HE models) were developed by considering the time-varying height scale factor for China and employing ZTD layered profile information with high temporal-spatial resolution calculated using MERRA-2 data and ERA5 data based on the integration method during 2012–2016. The CZTD-H model accuracy was verified using the global navigation satellite system (GNSS) data acquired from the Crustal Movement Observation Network of China (CMONOC) and radiosonde data as reference and was compared with the canonical GPT3 model accuracy. The applicability of CZTD-HM and CZTD-HE models was discussed. The results showed that: (1) CZTD-HM and CZTD-HE models exhibited excellent performance for ZTD layered vertical interpolation in northwestern and southeastern China, respectively. Among ZTD layered profiles from 84 radiosonde stations, the RMSE of ZTD data interpolated using CZTD-HM and CZTD-HE models improved by 12.9/16.23% and 13.8/17.16% compared with GPT3-1 and GPT3-5 models, respectively. (2) The CZTD-H model maintained high performance for the spatial interpolation of GGOS grid ZTD data. Validation with ZTD data from 249 GNSS stations showed that the RMSEs of both CZTD-HM and CZTD-HE models improved by 2.8 mm (19.7%) and 2.6 mm (18.6%) compared with those of the GPT3-1 and GPT3-5 models, respectively. The CZTD-HE model showed excellent performance in summer among all the models. Only the location and day of the year were required for the application of the CZTD-H model, which showed excellent ZTD vertical correction performance in China. With the different performances of the CZTD-HE and CZTD-HM models in China, the ERA5 model can be recommended for practical applications. Therefore, these results can provide a reference for the data source selection of ZTD vertical profile model construction on the basis of high-precision reanalysis data, GNSS real-time high-precision positioning, and GNSS meteorology in China.

Ecology and environmental suitability are widely used in urban ecology and regional ecology. However, there is still a lack of systematic evaluation method system for the research impacts of tourism development and tourism resource development on ecology and environment in ecologically sensitive scenic spots. Taking Lijiang River Basin, an ecologically sensitive area with typical karst landforms, as an example, this paper analyses the ecological and environmental suitability of tourism development from the perspective of space. In this paper, TM image and DEM model were firstly used to extract NDVI, slope, slope aspect and other related data. Then, based on the characteristics of the study area, the data of each factor was graded and assigned with a grade value, and the spatial situation of each single factor was analyzed, and superposition was carried out at last. Meanwhile, the study area is divided into three levels for tourism development, namely, unsuitable area, sub-suitable area and suitable area.

Automated positioning of transmission tower keypoints is crucial for drone-based intelligent inspection systems. This paper proposes TPKE (Transmission Pylons Keypoint Extraction), a novel framework designed to extract multiple transmission tower keypoints from LiDAR point clouds. The method targets two core components: insulator string endpoints and ground wire hanging points. For insulator positioning, TPKE introduces adaptive density clustering, a morphological “concavity” index (η) for V-shaped insulators, and a “positioning-verification-compensation” strategy for handling missing data. For ground wire positioning, it combines local geometric feature analysis with spatial orthogonal projection. Using semantic segmentation for preprocessing, the framework reliably identifies components from complex transmission corridor point clouds. Validated on 1427 towers across 14 types, TPKE achieves an MAE of 0.0747 m for insulators and 0.0696 m for ground wires. It maintains centimeter-level accuracy even under challenging conditions like sparse point clouds. With an average processing time of 3.03 s per tower, the method demonstrates high efficiency, significantly reducing manual annotation workload while supporting autonomous navigation for transmission line maintenance.

Detecting spatiotemporal changes in ecological environment quality (EEQ) is of great importance for maintaining regional ecological security and supporting sustainable economic and social development. However, research on EEQ detection from a remote sensing perspective is insufficient, especially at the basin scale. Based on two indices, namely, the Ecological Index (EI) and the Remote Sensing Ecological Index (RSEI), we established a dual model, combining the remote sensing ecological comprehensive index (RSECI) and its differential change model, to study the spatiotemporal evolutionary characteristics of EEQ in the Lijiang River Basin (LRB) from 2000 to 2020. The RSECI combines the following five indicators: greenness, wetness, heat, dryness, and aerosol optical depth. The results of this study show that the area of good and excellent EEQ in the LRB decreased from 3676.22 km² in 2000 to 2083.89 km² in 2020, while the area of poor and fair EEQ increased from 80.81 km² in 2000 to 1375.91 km² in 2020. From 2000 to 2020, the change curve of the EEQ difference in the LRB first rose, fell, and then rose again. The wetness and greenness indicators had positive effects on promoting EEQ, while the heat, aerosol optical depth, and dryness indicators had restraining effects. The results of stepwise regression analysis showed that, among the selected indicators, wetness and greenness were the key factors for improving the EEQ in the LRB during the study period. The RSECI approach and the difference change model proposed in this study can be used to quantitatively evaluate the EEQ and facilitate the analysis of the spatial and temporal dynamic changes and difference changes in EEQ.

The ecological system service is closely related to the citizens' welfare and serves as the bridge connecting the ecological system and the social system. To achieve sustainable development, we must protect the ecological environment. The paper marks off different land utilization types of the Lijiang River basin based on the remote sensing technique, and borrows ideas from other research findings and combines the practical situation of Lijiang River basin to correct the service unit price of ecological system type of the Lijiang River basin, then calculates the service value of ecological system for the basin in turn. The findings show that the total value of the service function of ecological system for the Lijiang River basin is 7195.22×106 Yuan. In terms of the service function of the ecological system, the woodland's service function value accounts the largest proportion in the whole ecological system, being 85.26% of the total value. In terms of the service function type of the ecological system, the soil formation and protection are the most significant, with value of 1340.00×106 Yuan, which accounts for 18.62%. The ecological service value's sequence in ascending order is: Food production <entertainment culture < raw material < waste disposal < climate regulation < gas conditioning < biological diversity protection <headwater conservation < soil formation and protection. The research is of important theoretical guidance and practical meaning for the monitoring over the ecological environment of Lijiang River basin and the sustainable development of tourism.