The aboveground biomass (AGB) of individual trees is a critical indicator for assessing urban forest productivity and carbon storage. In the context of global warming, it plays a pivotal role in understanding urban forest carbon sequestration and regulating the global carbon cycle. Recent advances in light detection and ranging (LiDAR) have enabled the detailed characterization of three-dimensional (3D) structures, significantly enhancing the accuracy of individual tree AGB estimation. This review examines studies that use LiDAR-derived 3D structural metrics to model and estimate individual tree AGB, identifying key metrics that influence estimation accuracy. A bibliometric analysis of 795 relevant articles from the Web of Science Core Collection was conducted using R Studio (version 4.4.1) and VOSviewer 1.6.20 software, followed by an in-depth review of 80 papers focused on urban forests, published after 2010 and selected from the first and second quartiles of the Chinese Academy of Sciences journal ranking. The results show the following: (1) Dalponte2016 and watershed are more widely used among 2D raster-based algorithms, and 3D point cloud-based segmentation algorithms offer greater potential for innovation; (2) tree height and crown volume are important 3D structural metrics for individual tree AGB estimation, and biomass indices that integrate these parameters can further improve accuracy and applicability; (3) machine learning algorithms such as Random Forest and deep learning consistently outperform parametric methods, delivering stable AGB estimates; (4) LiDAR data sources, point cloud density, and forest types are important factors that significantly affect the accuracy of individual tree AGB estimation. Future research should emphasize deep learning applications for improving point cloud segmentation and 3D structure extraction accuracy in complex forest environments. Additionally, optimizing multi-sensor data fusion strategies to address data matching and resolution differences will be crucial for developing more accurate and widely applicable AGB estimation models.

Amid global climate challenges and an urgent need for ecological protection, the northeastern black soil region—one of the world’s remaining “three major black soil regions”—confronts significant tensions between agricultural economic development and land ecological protection, threatening national food security. Based on the “production–ecology–life” (PLE) classification system, this study established a dual-dimensional evaluation for carbon metabolism and ESV in horizontal and vertical dimensions. The horizontal flow of carbon and ESV was traced across different ecosystems, while the spatial and temporal dynamics of carbon metabolism and ESV were analyzed vertically. Spatial autocorrelation analyses were employed to examine the interaction patterns between carbon metabolism and ESV. The findings reveal that (1) cropland production space remains the dominant spatial type, exhibiting fluctuating patterns in the size of other spatial types, with a notable reduction in water ecological space. (2) From 2000 to 2020, high-value carbon metabolism density areas were primarily concentrated in the central region, while low-value areas gradually decreased in size. Cropland production space and urban living space served as key compartments and dominant pathways for carbon flow transfer in the two periods, respectively. (3) The total ecosystem service value (ESV) showed a downward trend, decreasing by CNY 1.432 billion from 2000 to 2020. The spatial distribution pattern indicates high values in the center and northwest, contrasting with lower values in the southeast. The flow of ecological value from forest ecological space to cropland production space represents the main loss pathway. (4) A significant negative correlation exists between carbon metabolism density and ESV, with areas of high correlation predominantly centered around cropland production space. This study provides a scientific foundation for addressing the challenges facing the black soil region, achieving synergistic resource use in pursuit of carbon neutrality, and constructing a more low-carbon and sustainable spatial pattern.

Land use affects ecosystem stability and agricultural ecological security in black soil regions. Additional attention is required regarding the impact of different land-use patterns on black soil. However, the construction of sustainable agricultural ecological security in black soil environments is a dynamic process that depends on the reviews of experts and statistical analyses of literature data. This study quantitatively reviewed the past 20 years of the literature regarding black soil. Using the superposition of the expert knowledge map and machine clustering, knowledge regarding land use in black soil fields was classified structurally. Further, studies directly related to the spatiotemporal pattern of land use were identified, and frequently cited works of the literature were screened to build a dynamic knowledge network of black soil research. The results show that (1) the cooperative relationship among China, the United States, and Canada is the strongest, but the density of cooperation networks between other countries is low; (2) land-use research regarding black soil is divided into four research areas: soil microbial community and activity, soil erosion and ecological processes, ecological management of land use, soil organic matter, and element cycling; (3) the monitoring and management mode of land use in black soil areas should be established to include information management that incorporates knowledge of the cultivated land factor potential, grain production capacity assessment, soil erosion evaluation and prediction, and farmland landscape planning.

The carbon mitigation benefits of urban parks are expanding beyond traditional biological carbon sequestration to encompass the regulation of urban energy demand. Direct carbon sequestration capacity (DCSC), resulting from vegetation carbon fixation, and indirect carbon-saving capacity (ICSC), arising from reductions in building cooling energy consumption induced by summer cooling effects, represent two important pathways for carbon mitigation by urban parks. However, how landscape patterns and morphological spatial patterns jointly regulate DCSC and ICSC, and what nonlinear responses and interactions exist among different spatial indicators remain to be further investigated. Focusing on urban parks in the main urban area of Harbin, this study quantified DCSC and ICSC using multisource remote sensing data and revealed the spatial differences between these two carbon mitigation functions. By developing an analytical framework integrating explainable machine learning and nonlinear response modeling, this study identified the key indicators affecting DCSC and ICSC, the directions of their contributions, and their interactions. It further characterized the nonlinear responses of key indicator combinations and identified favorable ranges for the synergistic enhancement in both carbon benefits. The results showed that: (1) DCSC ranged from 0.96 to 946.75 kg C·day⁻¹, while ICSC ranged from 0.10 to 9,828.50 kg C·day⁻¹. Total ICSC across all parks was approximately 16 times the total DCSC, and both DCSC and ICSC were generally lower in urban parks located within the inner ring. (2) The relative contributions of landscape metrics and MSPA classes to the two carbon benefits differed markedly: landscape metrics made a greater explanatory contribution to ICSC, whereas MSPA classes made a relatively greater explanatory contribution to DCSC. Mean shape index (SHAPE_MN), patch density (PD), and Perforation were identified as key indicators with the potential to enhance both DCSC and ICSC. (3) From a synergistic perspective, interactions involving SHAPE_MN were prominent, with SHAPE_MN × PD ranking among the strongest for both responses, highlighting the importance of boundary complexity and spatial fragmentation. In addition, coordinating green space coverage, spatial continuity, boundary morphology, and the integrity of core spaces can effectively promote the synergistic enhancement in both carbon benefits. These findings provide a new planning basis for optimizing urban park structures in cold-region cities under spatial constraints and advancing the goal of urban carbon neutrality.