Leaf area is an important plant canopy structure parameter with important ecological significance. Light detection and ranging technology (LiDAR) with the application of a terrestrial laser scanner (TLS) is an appealing method for accurately estimating leaf area; however, the actual utility of this scanner depends largely on the efficacy of point cloud data (PCD) analysis. In this paper, we present a novel method for quantifying total leaf area within each tree canopy from PCD. Firstly, the shape, normal vector distribution and structure tensor of PCD features were combined with the semi-supervised support vector machine (SVM) method to separate various tree organs, i.e., branches and leaves. In addition, the moving least squares (MLS) method was adopted to remove ghost points caused by the shaking of leaves in the wind during the scanning process. Secondly, each target tree was scanned using two patterns, i.e., one scan and three scans around the canopy, to reduce the occlusion effect. Specific layer subdivision strategies according to the acquisition ranges of the scanners were designed to separate the canopy into several layers. Thirdly, 10% of the PCD was randomly chosen as an analytic dataset (ADS). For the ADS, an innovative triangulation algorithm with an assembly threshold was designed to transform these discrete scanning points into leaf surfaces and estimate the fractions of each foliage surface covered by the laser pulses. Then, a novel ratio of the point number to leaf area in each layer was defined and combined with the total number of scanned points to retrieve the total area of the leaves in the canopy. The quantified total leaf area of each tree was validated using laborious measurements with a LAI-2200 Plant Canopy Analyser and an LI-3000C Portable Area Meter. The results showed that the individual tree leaf area was accurately reproduced using our method from three registered scans, with a relative deviation of less than 10%. Nevertheless, estimations from only one scan resulted in a deviation of >25% in the retrieved individual tree leaf area due to the occlusion effect. Indeed, this study provides a novel connection between leaf area estimates and scanning sensor configuration and supplies an interesting method for estimating leaf area based on PCD.

Timber volume is an important ecological component in forested landscapes. The application of terrestrial laser scanning (TLS) to volume estimation has been widely accepted though few species have well-calibrated taper functions. This research uses TLS technology in poplar (Populus × canadensis Moench cv. ‘I-72/58’) to extract stem diameter at different tree heights and establish the relationship between point cloud data and stem curve, which constitutes the basis for volume estimation of single trees and the stand. Eight plots were established and scanned by TLS. Stem curve functions were then fitted after extraction of diameters at different height, and tree heights from the point cloud data. Lastly, six functions were evaluated by R² and RMSE. A modified Schumacher equation was the most suitable taper function. Volume estimates from the TLS-derived taper function were better than those derived using the stem-analysis data. Finally, regression analysis showed that predictions of stem size were similar when data were based on TLS versus stem analysis. Its high accuracy and efficiency indicates that TLS technology can play an important role in forest inventory assessment.

With the accelerated process of urbanization, air pollution has become increasingly severe. Garden plants can trap atmospheric particulate matter, which is of great significance for improving the urban ecological environment and promoting sustainable development. To investigate the dust retention effect of typical transportation green spaces in Nanjing, this study focuses on thirteen garden plants on Xuanwu Avenue in Nanjing. The dust retention capacity of these plants was determined using the wash-off method, while the microstructure of their leaf surfaces was observed using scanning electron microscopy. The results are as follows: Firstly, per unit leaf area, Liriope spicata, Ophiopogon japonicus, and Viburnum odoratissimum demonstrate solid dust retention abilities. Additionally, Viburnum odoratissimum, Prunus serrulata var. Lannesiana, and Liriope spicata show strong dust retention abilities per single leaf. Moreover, Platanus acerifolia, Viburnum odoratissimum, and Cinnamomum camphora have strong dust retention abilities per plant. Viburnum odoratissimum, Platanus acerifolia, and Prunus serrulata var. Lannesiana exhibit the most substantial dust retention capacities. Secondly, there is a significant negative correlation between dust retention per plant and the potassium content, while a significant positive correlation is observed with plant height, canopy height, and leaf width. Furthermore, there is a highly significant positive correlation between dust retention per unit leaf area and stomatal length and a highly significant negative correlation with leaf length. The surface microstructure of the blade mainly increases the dust retention capacity of the blade by increasing the friction of the leaf surface. Lastly, specific leaf surface microstructures, such as grooved epidermis and trichomes, enhance plants’ dust retention capacity. Consequently, for the future configuration of road green spaces in Nanjing, a mixed planting mode of trees, shrubs, and grass is recommended. Priority should be given to selecting plants with strong overall dust retention capabilities, such as Platanus acerifolia, Viburnum odoratissimum, and Prunus serrulata var. Lannesiana, to alleviate air pollution, improve the urban ecological environment, and achieve sustainable development.

Wetlands support biodiversity and hydrological regulation; bird communities are sensitive indicators of environmental change. However, evidence linking bird-community patterns to restoration remains limited in the lower Yangtze floodplain wetlands. We aimed to characterize bird-community composition and spatiotemporal diversity in Longpao Yangtze Wetland and examine their association with restoration history. We conducted monthly surveys from November 2024 to September 2025 using line transects, point observations, and Unmanned Aerial Vehicle (UAV) monitoring. Combined records described species composition, standardized field records provided diversity indices, and historical records showed interannual patterns. We recorded 197 species in the combined inventory, including 5 Class I and 30 Class II nationally protected species; standardized surveys recorded 144 species. Winter migrants and Palearctic species were the largest residency and zoogeographical groups, respectively. Diversity was highest in spring and lowest in autumn, although autumn included one survey. Heterogeneous transects YX6 and YX3 had higher diversity. Recorded richness increased from 59 species (2019) to 197 (2025), coinciding with restoration. Longpao Wetland supports diverse birds of conservation concern, emphasizing the value of heterogeneous habitats. Unequal seasonal effort and inconsistent historical methods preclude causal inference. Future research should use standardized long-term monitoring and quantitative habitat analyses to guide hydrological management, habitat enhancement, and community co-management.