Search Results (179)

Urban forests and green spaces are increasingly promoted as Nature-Based Solutions (NbS) to mitigate climate risks, enhance human well-being, and support resilient and sustainable cities. Focusing on the theme of optimizing urban green space ecosystem services to foster resilient and sustainable cities, this study systematically analyzes 861 relevant publications indexed in the Web of Science Core Collection from 2005 to 2025. Using bibliometric analysis and scientific knowledge mapping methods, the research examines publication characteristics, spatial distribution patterns, collaboration networks, knowledge bases, research hotspots, and thematic evolution trajectories. The results reveal a rapid upward trend in this field over the past two decades, with the gradual formation of a multidisciplinary knowledge system centered on environmental science and urban research. China, the United States, and several European countries have emerged as key nodes in global knowledge production and collaboration networks. Keyword co-occurrence and cluster analyses indicate that research themes are mainly concentrated in four clusters: (1) ecological foundations and green process orientation, (2) nature-based solutions and blue–green infrastructure configuration, (3) social needs and environmental justice, and (4) macro-level policies and the sustainable development agenda. Overall, the field has evolved from a focus on ecological processes and individual service functions toward a comprehensive transition emphasizing climate resilience, human well-being, and multi-actor governance. Based on these findings, this study constructs a knowledge ecosystem framework encompassing knowledge base, knowledge structure, research hotspots, frontier trends, and future pathways. It further identifies prospective research directions, including climate change adaptation, integrated planning of blue–green infrastructure, refined monitoring driven by remote sensing and spatial big data, and the embedding of urban green space ecosystem services into the Sustainable Development Goals and multi-level governance systems. These insights provide data support and decision-making references for deepening theoretical understanding of Urban Green Space Ecosystem Services (UGSES), improving urban green infrastructure planning, and enhancing urban resilience governance capacity. Full article

Remote sensing approaches to monitoring dryland ecosystem states and trends have been dominated by the binary distinction between degraded/non-degraded areas, leading to inconsistent results. We propose a different conceptual framework that better reflects the states and pressures of these ecosystems—ecological integrity—that is, the maintenance of ecosystem composition and its capacity to contribute to human needs and adapt to change. We systematically reviewed earth observation techniques for characterizing ecological integrity in trusted databases together with studies identified through expert-guided search. A total of 137 papers were included, and their metadata (i.e., location, year) and data (i.e., aspect of ecological integrity assessed, techniques employed) were analyzed. The results show that remote sensing ecological integrity is becoming an increasingly researched topic, especially in countries with extensive drylands. Vegetation was the most frequently monitored attribute and was often employed as an indicator of other attributes (i.e., soil and water quality) and as a key feature in approaches that aimed for a comprehensive ecosystem assessment. However, most of the literature employed the normalized difference vegetation index (NDVI) as a descriptor of vegetation characteristics (i.e., health, structure, cover), which has been shown not to be a good indicator of the litter/senescent vegetation components that tend to frequently dominate drylands. Methods to overcome this weakness have been identified, although more research is needed to demonstrate their application in ecological integrity monitoring. Specifically, knowledge gaps in the relationship between vegetation cover fractions (i.e., green, non-green, and bare soil), descriptors of ecosystem quality (e.g., soil condition or vegetation structure complexity), and management (i.e., how human intervention affects ecosystem quality) should be addressed. Notable potential has been identified in time series analysis as a means of operationalising remotely sensed vegetation fractional cover. Nevertheless, limitations in benchmarking must also be tackled for effective ecological integrity monitoring. Full article

The Semipalatinsk Test Site (STS), one of the most heavily contaminated nuclear test sites globally, presents critical challenges for ecological monitoring and restoration due to long-term radioactive pollution and soil degradation. This study applied the Remote Sensing Ecological Index (RSEI) model to systematically evaluate the spatiotemporal changes in ecological quality at STS from 2003 to 2023. The RSEI model integrated multi-indicator data, including NDVI (Normalized Difference Vegetation Index), LST (Land Surface Temperature), WET (Wetness), and NDBSI (Normalized Difference Built-up and Soil Index), enabling a comprehensive assessment of ecological dynamics. Results demonstrated a significant improvement in ecological quality, with the RSEI increasing by 29.59% (from 0.345 in 2003 to 0.447 in 2023). PCA results indicated that ecological recovery was primarily influenced by surface temperature, vegetation cover, and soil moisture, with radioactive residues further hindering recovery in severely contaminated zones. The proportion of “Poor” areas declined from 14.99% to 0.61%, while “Moderate” and “Good” areas expanded to 55.76% and 8.87%, respectively. Peripheral regions showed faster recovery due to effective natural and management interventions, while core high-contamination zones (Sary-Uzen) exhibited slower recovery due to persistent radioactive residues. This study highlights the applicability of RSEI for assessing ecological recovery in nuclear test sites and emphasizes the need for targeted remediation strategies. These findings provide valuable insights for global ecological management of nuclear test sites, supporting sustainable restoration efforts. Full article

Urban lakes are essential for ecological balance and urban development. This study developed a comprehensive framework to evaluate the ecosystem health of urban lakes in China. Nineteen representative lakes from four lake zones were examined using three decades of remote-sensing data combined with hydrological, water-quality, and aquatic–biological investigations. An extended DPSIR model guided the selection of 52 indicators, and a hierarchical weighting scheme was used: the analytic hierarchy process determined criterion-level weights, while principal component analysis with Softmax normalization was used for indicator-level weights. The established index system was applied to Xuanwu Lake and Erhai Lake, and an obstacle-degree model was used to identify key ecological constraints from 2010 to 2020. Results showed that urban lakes in the Yunnan–Guizhou Plateau and Eastern Plain zones were mainly constrained by eutrophication and intensive urbanization, with state- and impact-related indicators contributing most to the health index. The framework captured the decline of Xuanwu Lake, driven by poor water exchange and external nutrient loading, and its subsequent improvement following governance interventions, as well as the post-2014 degradation of Erhai Lake driven by climate-induced hydrological stress and non-point source pollution, providing a practical tool for diagnosing constraints and supporting adaptive, region-specific lake management. Full article

This review systematically analyzes 215 papers on the remote sensing monitoring of Spartina alterniflora (S. alterniflora) indexed in the Web of Science database to clarify research progress and future development directions in this field. We applied CiteSpace 6.3.R1 to conduct a bibliometric analysis of remote sensing literature on S. alterniflora, summarizing the technical methodologies across three major domains: distribution dynamics, parameter inversion, and ecosystem functions and services. We traced the technological evolution of multi-source remote sensing and artificial intelligence, and explored application prospects in addressing current challenges and supporting precision management. Our research indicates that the primary challenge lies in the complex and diverse spatiotemporal dynamics of S. alterniflora. To achieve timely monitoring of S. alterniflora changes and large-scale ecological impact assessments, it is essential to fully utilize the advantages of multi-source remote sensing big data. Harnessing artificial intelligence technologies to fully exploit the potential of remote sensing data, enhancing multi-source data fusion, and expanding sample libraries are essential to achieve comprehensive monitoring spanning spatial patterns, ecological processes, and ecosystem functions and services. These efforts will provide a scientific basis and decision-making support for the sustainable management of coastal wetlands. Full article

Mineral resource exploitation poses substantial pressure on regional ecological environments. The Xiaoxing’anling mineral belt—a critical ecological functional area and a major mineral-rich zone in China—exemplifies such environmental vulnerability. Conducting a scientific assessment of ecological changes in mining-affected regions is essential for balancing resource development and environmental protection. Based on the DPSIR (Driver-Pressure-State-Impact-Response) model, this study developed a comprehensive indicator system tailored for evaluating ecological changes in mining areas. Using the Xiaoxing’anling mineral belt in Heilongjiang Province as a case study, we integrated remote sensing, geographic information, statistical yearbooks, and field survey data, and applied an objective weighting method to quantitatively assess ecological changes from 2010 to 2020. The results indicate the following: (1) Ecological evolution exhibits significant spatiotemporal heterogeneity, with persistently high ecological pressure in the eastern region leading to continued environmental degradation. (2) Socioeconomic transformation driven by new energy development has weakened the overall development driver, though Yichun City remains a core driver due to its super-large mineral deposits. (3) Ecological impacts demonstrate a spatial spillover effect, extending to urban residential areas, while ecological response measures lag severely and are misaligned with pressure distribution—nature reserves have become high-value response zones rather than the actual mining sites. (4) The comprehensive ecological restoration index is on a downward trend. The measures currently adopted by society to improve the ecology of mining areas, such as using greener mining methods and increasing vegetation coverage, are unable to counteract the adverse effects of previous mining activities. This study identifies passive and lagging responses as the key bottlenecks impeding ecological recovery. We emphasize that future management strategies must shift from passive remediation to proactive intervention, and propose clear spatial and institutional directions for sustainable governance in mining areas. Full article

The sustainable development of cities urgently requires an understanding of the interaction between social equity and ecological quality, especially in the peri-urban areas that traditional environmental justice research has paid less attention to. Taking Outer London as an example in this study, the Comprehensive Social Equity Index (CSEI) and the Remote Sensing Ecological Index (RSEI) were constructed to explore the social–ecological coupling relationship and spatial heterogeneity. Four types of socio-ecological coupling were identified through the four-quadrant model, ordinary least squares (OLS), and multi-scale geographically weighted regression (MGWR). The results reveal the characteristics of nonlinear coupling: in addition to the dual disadvantages and advantages of society and ecology, there are also regional patterns where social conditions are advantageous, but ecology is degraded, and where society is weak, but ecology is rich. This indicates that there is a complex spatial dislocation relationship between society and ecology in the peri-urban. The research proposes a scale-sensitive governance strategy based on location, emphasizing the coordinated countermeasures of social reinvestment and ecological restoration, providing a new perspective for environmental justice and sustainable planning in the peri-urban areas of the UK. Full article

A systematic assessment of the impact and mechanisms of Land Consolidation policy on ecological environment can provide valuable insights for optimizing territorial spatial development and restoring ecological functions, both in China and globally. Utilizing 2015–2022 township-level panel data from Zhejiang Province, this study employs satellite remote sensing to construct an Ecological Vulnerability (EV) index. We empirically examine the impact of Whole Region Comprehensive Land Consolidation (WRCLC) on EV and its transmission channels by applying a multi-period Difference-in-Differences (DID) model and a mediating effect model. The results indicate that the implementation of WRCLC pilot policies significantly reduces EV, a finding that remains robust after parallel trend tests, placebo tests, and other robustness checks. The mediating effects within the “Element-Pattern-Effect” framework indicate that the transition of land elements toward ecological functions and the absence of significant land use conflicts at the pattern level are key mechanisms driving these outcomes. Furthermore, the study reveals that WRCLC exerts a significant negative spatial spillover effect on adjacent areas. It is therefore recommended to promote this policy, providing valuable insights for land consolidation initiatives in other Chinese provinces and developing countries worldwide. Full article

With the rapid advancement of the Hainan Free Trade Port (HFTP), substantial changes in land use and ecological systems have emerged. The study analyzes the spatiotemporal dynamics of ecological quality in Hainan Province from 2017 to 2024 and projects its potential evolution through 2030 under different development scenarios. A comprehensive framework integrating the Remote Sensing Ecological Index (RSEI) and Land Use/Cover Change (LUCC) simulations was employed. Multi-source datasets, including remote sensing imagery, geographic, meteorological, and socio-economic data, were combined with the Markov–FLUS model to simulate future land-use patterns. The results indicate extensive urban expansion and a notable increase in construction land, accompanied by a continuous decline in RSEI values, particularly under the business-as-usual scenario. In contrast, policy-guided simulations suggest more sustainable land allocation and gradual improvement in ecological quality. The findings demonstrate that integrating scenario-based simulation with ecological index modeling provides an effective approach for supporting ecological conservation and sustainable urban planning in tropical island regions experiencing rapid economic transformation. Full article

This research presents a comprehensive analysis of the spatial extent and temporal change in benthic habitats within the Puck Lagoon in the southern Baltic Sea, utilizing integrated machine learning classification and multi-sourced remote sensing. Object-based image analysis was integrated with Random Forest, Support Vector Machine, and K-Nearest Neighbors algorithms for benthic habitat classification based on airborne bathymetric LiDAR (ALB), multibeam echosounder (MBES), satellite bathymetry, and high-resolution aerial photography. Ground-truth data collected by 2023 field surveys were supplemented with long temporal datasets (2010–2023) for seagrass meadow analysis. Boruta feature selection showed that geomorphometric variables (aspect, slope, and terrain ruggedness index) and optical features (ALB intensity and spectral bands) were the most significant discriminators in each classification case. Binary classification models were more effective (93.3% accuracy in the presence/absence of Zostera marina) compared to advanced multi-class models (43.3% for EUNIS Level 4/5), which identified the inherent equilibrium between ecological complexity and map validity. Change detection between contemporary and 1957 habitat data revealed extensive Zostera marina loss, with 84.1–99.0% cover reduction across modeling frameworks. Seagrass coverage declined from 61.15% of the study area to just 9.70% or 0.63%, depending on the model. Seasonal mismatch may inflate loss estimates by 5–15%, but even adjusted values (70–94%) indicate severe ecosystem degradation. Spatial exchange components exhibited patterns of habitat change, whereas net losses in total were many orders of magnitude larger than any redistribution in space. These findings recorded the most severe seagrass habitat destruction ever described within Baltic Sea ecosystems and emphasize the imperative for conservation action at the landscape level. The methodology framework provides a reproducible model for analogous change detection analysis in shallow nearshore habitats, creating critical baselines to inform restoration planning and biodiversity conservation activities. It also demonstrated both the capabilities and limitations of automatic techniques for habitat monitoring. Full article

This study focuses on the assessment of the ecological vulnerability of lands in the western regions of Kazakhstan (WKR) using the MEDALUS (Mediterranean Desertification and Land Use) model in combination with satellite remote sensing data. Particular attention is given to the influence of climatic factors, soil properties, vegetation condition, and anthropogenic pressure. As part of the analysis, key indicators were calculated, including the Soil Quality Index (SQI), Vegetation Quality Index (VQI), Climate Quality Index (CQI), and Management Quality Index (MQI). Based on these parameters, an Environmental Sensitivity Area (ESA) index was developed, allowing the classification of the territory into five vulnerability classes ranging from low to critical sensitivity. The results indicate that 52.7% of the territory of the WKR falls within the high-risk zone for land degradation. The most pronounced changes were observed in the southern oblasts of the region, particularly in Mangystau oblast (MAN), where 98.7% of the land is classified as degraded and 74.3% of the territory falls under the category of extremely high ecological vulnerability. In addition, a steady decline in precipitation levels has been identified, contributing to the intensification of aridization processes across the region. Correlation analysis showed that the strongest relationships with the final ESA index were observed for the Vegetation Quality Index (VQI) and Climate Quality Index (CQI), both with correlation coefficients of r = 0.93 and an average coefficient of determination R² = 0.87. The Soil Quality Index (SQI) also demonstrated a strong correlation (r = 0.86). In contrast, the Management Quality Index (MQI) exhibited a generally weak correlation, except in the MAN oblast, where within the Very Low Quality (VLQ) class areas, it showed a moderate correlation (r = 0.68, p < 0.0001). The results highlight the critical role of natural factors—particularly vegetation condition, climate, and soil quality—in shaping the ecological vulnerability of the region. Findings emphasize the need for a comprehensive, multi-criteria approach in developing strategies for sustainable land management under conditions of ongoing climate change. Full article

This study systematically investigates settlement sites that record living patterns of ancient humans, aiming to reveal the interactive mechanisms of human–environment relationships. The core issues of landscape archeology research are the surface spatial structure, human spatial cognition, and social practice activities. This article takes the Han Dynasty settlement site in Sanyangzhuang, Neihuang County, Anyang City, Henan Province, as a typical case. It comprehensively uses ArcGIS 10.8 spatial analysis and remote sensing image interpretation techniques to construct spatial distribution models of elevation, slope, and aspect in the study area, and analyzes the process of the Yellow River’s ancient course changes. A regional historical geographic information system was constructed by integrating multiple data sources, including archeological excavation reports, excavated artifacts, and historical documents. At the same time, the sequences of temperature and dry–wet index changes in the study area during the Qin and Han dynasties were quantitatively reconstructed, and a climate evolution map for this period was created based on ancient climate proxy indicators. Drawing on three dimensions of settlement morphology, architectural spatial organization, and agricultural technology systems, this paper provides a deep analysis of the site’s spatial cognitive logic and the ecological wisdom it embodies. The results show the following: (1) The Sanyangzhuang Han Dynasty settlement site reflects the efficient utilization strategy and environmental adaptation mechanism of ancient settlements for land resources, presenting typical scattered characteristics. Its formation mechanism is closely related to the evolution of social systems in the Western Han Dynasty. (2) In terms of site selection, settlements consider practicality and ceremony, which can not only meet basic living needs, but also divide internal functional zones based on the meaning implied by the orientation of the constellations. (3) The widespread use of iron farming tools has promoted the innovation of cultivation techniques, and the implementation of the substitution method has formed an ecological regulation system to cope with seasonal climate change while ensuring agricultural yield. The above results comprehensively reflect three types of ecological wisdom: “ecological adaptation wisdom of integrating homestead and farmland”, “spatial cognitive wisdom of analogy, heaven, law, and earth”, and “agricultural technology wisdom adapted to the times”. This study not only deepens our understanding of the cultural value of the Han Dynasty settlement site in Sanyangzhuang, but also provides a new theoretical perspective, an important paradigm reference, and a methodological reference for the study of ancient settlement ecological wisdom. Full article

The river source region of the Yellow River Basin is a critical ecological barrier in China, yet it is characterized by extreme environmental vulnerability. Human activities, particularly intensive mining, can severely disrupt the landscape ecosystem and alter its spatial patterns. The aim of this study is to conduct a comprehensive landscape ecological risk assessment, analyzing the spatial differentiation and driving factors of these risks to ensure regional ecological security. Employing high-resolution remote sensing technology, a comprehensive assessment of landscape ecological risk in the river source region of the Yellow River Basin was conducted based on the 2020 mining development status. The landscape ecological risk index (ERI_k) was applied to evaluate risk distribution patterns, while the Geodetector model implemented in R was utilized to identify and analyze key driving factors. The results were as follows: (1) The study area exhibited an elevated landscape ecological risk. (2) Anthropogenic disturbances, such as urban construction, residential activities, and mining, combined with a widespread cropland distribution, degraded alpine grasslands, and high landscape fragility, were identified as major contributors to the elevated landscape ecological risk in the study area. (3) Habitat quality and population density remain the most significant factors driving the spatial differentiation of landscape ecological risk, and their interaction strongly governs the spatial distribution of such risk. In contrast, mining development intensity is not a dominant factor influencing the spatial heterogeneity of landscape ecological risk at the regional scale in the study area. This assessment reveals the extent of ecological risk associated with mining and other human activities and its key drivers. Full article

Understanding landscape fragmentation is crucial to explore comprehensive land-use–land-cover (LULC) change within fast-growing urbanisation. While LULC change is a global concern, limited research explores landscape fragmentation along river and road infrastructure in high-density riverine contexts. This study addresses this gap through understanding dynamic landscape fragmentation patterns to track LULC in the Ciliwung River, Indonesia, from 1990 to 2020. The research employed remote sensing, GIS, R programming with Landsat data, Normalised Difference Vegetation Index (NDVI) values, buffering, and landscape metrics. The findings show minimal fragmentation was concentrated downstream near Jakarta, while significant fragmentation, manifesting as green loss, occurred in the midstream. Buffer analysis showed high green loss in the upstream segment both near the river and roads, particularly within a 0–400 m buffer. However, landscape metrics identified changes in the midstream close to the river buffer (0–200 m) indicating that riparian green spaces in this area persist as relatively large but ecologically unconnected “chunks”. The stability of these remaining patches makes them a crucial asset for targeted restoration. These findings contribute to a deeper understanding of how river and road networks influence the change, highlighting the integral role of remote sensing and GIS in monitoring LULC change for natural preservation. Full article

The interactive coupling mechanism between ecosystem service value (ESV) and urbanization has emerged as a critical research focus in ecological security and sustainable development. This study quantifies the ESV of prefecture-level cities by leveraging remote sensing data and socioeconomic statistics from the Yangtze River Delta (YRD) region spanning 2006—2020. It constructs a multidimensional evaluation index system for urbanization. We systematically assess both systems’ spatiotemporal evolution and interactions by employing entropy weighting, comprehensive indexing, and coupling coordination models. Furthermore, Geo-detectors and Geographical and Temporal Weighted Regression (GTWR) models are applied to identify driving factors influencing their coordinated development. Key findings include (1) the total amount of ESV in the YRD exhibits a fluctuating decline, primarily due to a steady increase in urbanization levels; (2) the coordination degree between ESV and urbanization demonstrates phased growth, transitioning to a “basic coordination” stage post-2009; (3) spatially, coordination patterns follow a “core–periphery” hierarchy, marked by radial diffusion and gradient disparities, with most cities being of the ESV-guidance type; (4) GTWR analysis reveals spatiotemporal heterogeneity in driving factors, ranked by intensity as Normalized Difference Vegetation Index (NDVI) > Economic density (ECON) > Degree of openness (OPEN) > Scientific and technological level (TECH) > Industrial structure upgrading index (ISUI) > Government investment efforts (GOV). This study advances methodological frameworks for analyzing ecosystem–urbanization interactions in metropolitan regions, while offering empirical support for ecological planning, dynamic redline adjustments, and territorial spatial optimization in the YRD, particularly within the Ecological Green Integrated Development Demonstration Zone. Full article