Search Results (350)

Mangrove ecosystems provide numerous ecological services and serve as vital habitats for a wide range of flora and fauna. Thus, accurate mapping and monitoring of relevant land covers in mangrove ecosystems are crucial for effective conservation and management efforts. In this study, we proposed a novel approach for mangrove ecosystem mapping using a Hybrid Selective Kernel-based Convolutional Neural Network (HSK-CNN) framework and multi-temporal Sentinel-2 imagery. A time series of the Normalized Difference Vegetation Index (NDVI) products derived from Sentinel-2 imagery was produced to capture the temporal behavior of land cover types in the dynamic ecosystem of the study area. The proposed algorithm integrated Selective Kernel-based feature extraction techniques to facilitate the effective learning and classification of multiple land cover types within the dynamic mangrove ecosystems. The model demonstrated a high Overall Accuracy (OA) of 94% in classifying eight land cover classes, including mangrove, tidal zone, water, mudflat, urban, and vegetation. The HSK-CNN demonstrated superior performance compared to other algorithms, including random forest (OA = 85%), XGBoost (OA = 87%), Three-Dimensional (3D)-DenseNet (OA = 90%), Two-Dimensional (2D)-CNN (OA = 91%), Multi-Layer Perceptron (MLP)-Mixer (OA = 92%), and Swin Transformer (OA = 93%). Additionally, it was observed that the structure of the network, such as the types of convolutional layers and patch sizes, affected the classification accuracy using the proposed model and, thus, the optimum scenarios and values of these parameters should be determined to obtain the highest possible classification accuracy. Overall, it was observed that the produced map could offer valuable insights into the distribution of different land cover types in the mangrove ecosystem, facilitating informed decision-making for conservation and sustainable management efforts. Full article

This study employs the Historic Urban Landscape (HUL) framework to explore the integration of landscape plants as green heritage with Lanna urban identity in Chiang Mai Old City, Thailand. The research focuses on 38 Lanna temples, investigating the characteristics and roles of plant materials in these sacred spaces. Through comprehensive ground surveys, GIS mapping, and structured interviews with monks, temple caretakers, and long-term residents, the study documents the types, locations, and uses of native and exotic plants. The findings emphasize the cultural, aesthetic, and ecological significance of heritage trees, such as the Bodhi trees and the Yang tree. These trees are pivotal in maintaining cultural continuity, supporting traditional rituals, and enhancing biodiversity. The study also reveals that while ornamental and edible plants are actively used in rituals and community practices, medicinal and applicable plants are preserved more for their historical value than practical use. This research underscores the necessity of sustainable landscape management, community engagement, and the preservation of ethnobotanical knowledge to mitigate the impacts of urbanization. By integrating green heritage into urban planning, the study provides valuable insights for enhancing the cultural and environmental landscape of Chiang Mai. Full article

The present study reflects on spontaneous nature’s agency to reclaim abandoned urban areas in Italian urban brownfields, providing a focused analysis of the Metropolitan Area of Milan. These spaces are the products of phenomena, such as deindustrialization, demilitarization, and uncontrolled urban expansion, which have produced a compromised heritage and challenges to regeneration. Such abandonment sometimes produces new forms of urban nature, which suggests a possible path for ecological regeneration and coexistence, as affirmed by the multidisciplinary literature. The related informal urban biodiversity grows regardless of future planning provisions, triggering unexpected transformations of the urban environment and producing socio-ecological value, as demonstrated by citizens’ recognition of these places. The present study maps informal urban biodiversity in the Milan territory, identifying the presence of large contaminated sites, relevant urban voids, vacant lots, and former agricultural spaces. This study also reflects on possible paths for urban planning and policies to integrate informal urban biodiversity within the urban ecological structure by analyzing the main features and challenges of the corresponding regeneration processes. Full article

Urban Green Infrastructures (UGIs) have gained increasing relevance in the field of climate adaptive design because of their capacity to provide regulating ecosystem services apt to respond to the impacts of global warming with short-term strategies. The effectiveness of UGIs in reducing climate risks depends on both the state of natural resources and the understanding of urban ecosystem processes over time. The implementation of analytic methods to better understand urban ecosystem dynamics, as well as the local effective potential of ESs, is crucial for addressing climate impacts in cities. The advances in remote sensing methodologies for mapping and monitoring urban ecosystems represent a key opportunity to deepen the ecological features of existing urban green areas as a potential planning asset to respond to climate impacts. Indeed, remote sensing technologies implement a new data-driven planning approach that enables models and simulations of different project scenarios by supporting planning decisions and reducing the risk of failures. According to these assumptions, this paper discusses the results of a literature review aimed at providing the current state of the art in applying remote sensing technologies for mapping and monitoring ecosystem services, focusing on operational opportunities in urban environments. It examines how remote sensing can depict ESs and ensure data quality and reliability for UGI design. The emphasis is on the potential of ESs to mitigate and adapt to heat wave risks which will be more frequent in the next decade, particularly in cities, as highlighted by the IPCC Report 2023. Therefore, UGIs are strategic tools for addressing heat wave impacts, necessitating a shift from empirical approaches to analytical, data-driven planning methods. Full article

This study presents the development and application of a prototype decision support system (DSS) for tree selection specifically for Punjab, India, a region facing challenges of low forest cover and an increasing demand for sustainable land use practices. The DSS developed using the R Shiny framework integrates ecological, social, and agro-commercial criteria to facilitate scientific knowledge decision making in tree plantation. The modules in this DSS include a tree selection tool based on comprehensive species attributes, a GIS-based tree suitability map module utilizing an Analytical Hierarchical Process (AHP), and a silviculture practice information module sourced from authoritative databases. Combining sophisticated statistical and spatial analysis, such as NMDS and AHP-GIS, this DSS mitigates data redundancy in SDM while incorporating extensive bibliographic research in dataset processing. The study highlights the necessity of fundamental niche-based suitability in comparison to realized niche suitability. It emphasizes on the importance of addressing ecosystem services, agro-commercial aspects, and enhancing silvicultural knowledge. Additionally, the study underscores the significance of local stakeholder engagement in tree selection, particularly involving farmers and other growers, to ensure community involvement and support. The DSS supports agroforestry initiatives and finds applications in urban tree management and governmental programs, emphasizing the use of scientific literature at each step, in contrast to relying solely on local knowledge. Full article

As urbanization accelerates, solid waste management has become one of the key issues in urban governance. Accurate and efficient waste sorting is a crucial step in enhancing waste processing efficiency, promoting resource recycling, and achieving sustainable development. However, there are still many challenges inherent in today’s garbage detection methods. These challenges include the high computational cost of detection, the complexity of the detection background, and the difficulty in accurately evaluating the spatial relationship between rectangular detection frames during the inspection process. Therefore, this study improves the latest YOLOv8s object detection model, introducing a garbage detection model that balances light weight and detection performance. Firstly, this study introduces a newly designed structure, the CG-HGNetV2 network, to optimize the backbone network of YOLOv8s. This novel framework leverages local features, surrounding context, and global context to enhance the accuracy of semantic segmentation. It efficiently extracts features through a hierarchical approach, significantly reducing the computational cost of the model. Additionally, this study introduces an innovative network called MSE-AKConv, which integrates an attention module into the network architecture. The irregular convolution operations facilitate efficient feature extraction, enhancing the ability to extract valid information from complex backgrounds. In addition, this study introduces a new method to replace CIoU (complete intersection over union). On the basis of calculating IoU (intersection over union), it also considers the outer boundary of the two rectangles. By calculating the minimum distance between the boundaries, this method handles cases where boundaries are close but not overlapping, offering a more detailed similarity assessment than that provided by traditional IoU. In this study, the model was trained and evaluated using a publicly available dataset. Specifically, the model has improved the precision (P), recall rate (R), and mAP@50 (mean average precision at 50) by 4.80%, 0.10%, and 1.30%, while reducing model parameters by 6.55% and computational demand by 0.03%. This study not only provides an efficient automated solution for waste detection, but also opens up new avenues for ecological environmental protection. Full article

Wetland ecosystems are vital for ecological security. However, rapid industrialization and urbanization have led to regional degradation, particularly in areas like the Qin-mang River Basin, a pivotal site in China’s ecological security strategy. Urgent measures are required to safeguard the health of its wetland ecosystems. This study employs the hierarchical analysis method-neural network-driver-pressure-state-response (AHP-SOM-DPSR) model to evaluate the ecological health of wetland ecosystems in the Qin-mang River Basin over a thirty-year period, from 1992 to 2022. Initially, the Drive-Pressure-State-Response (DPSR) model establishes a comprehensive indicator system encompassing 19 indicators spanning driving forces, pressures, states, and responses. Subsequently, a hybrid approach combining Analytic Hierarchy Process (AHP) and Self-Organizing Map (SOM) determines indicator weights to evaluate spatiotemporal ecosystem changes over the past three decades. Additionally, spatial autocorrelation theory analyzes ecosystem health in the study area. Finally, Pearson correlation coefficient analysis examines the driving factors influencing ecosystem health and their impacts. Results indicate: (1) Ecosystem health has deteriorated gradually from 1992 to 2022, underscoring the imperative for enhanced wetland management in the Qin-mang River Basin. (2) High spatial autocorrelation areas, primarily in the central-southern and northern regions, highlight priority zones for wetland ecosystem management. (3) Urbanization levels, average temperature, and total population significantly impact wetland ecosystem health in the Qin-mang River Basin. These findings offer valuable scientific insights for guiding ecological management and conservation efforts in the region. Full article

Rural areas provide ecosystem services (ESs) to urban metropolitan regions. These services are threatened by the constant pressure of urbanisation and new interest in rural development. This has heightened the conflict between environmental concerns and developmental needs, thereby presenting significant land management and rural planning challenges. Employing a quantitative measurement and optimisation framework, we investigate six representative ES variables to assess planning strategies that can address this contradiction. We used a suburban rural area around Nanjing, China, as our study area. We collected spatial data from 2005 to 2020 at two scales (village level and 500 m grid) to map ESs, quantify interactions (trade-offs and synergies among ES bundles), and identify the social, ecological, and landscape drivers of rural change. Based on this, rural planning strategies for optimising ESs at different scales have been proposed. Our findings include (1) spatial heterogeneity in the distribution of ESs, (2) the identification of seven synergistic and eight trade-off pairs among ESs, (3) a spatial scale effect in suburban rural areas, and (4) the spatial trade-offs/synergies of ESs exhibiting a ‘Matthew effect’. The identification of key trade-offs and synergistic ES pairs and the categorisation of ES bundles form the basis for a multi-scale hierarchical management approach for ESs in the region. By examining the commonalities and variations in drivers across diverse scales, we established connections and focal points for spatial planning. We use these findings to propose spatial planning and landscape policy recommendations for rural suburban areas on multiple scales. This study aims to provide a comprehensive and detailed spatial optimisation strategy for rural areas that can help contribute to their revitalisation. Full article

Urban sprawl leads to the degradation of aquatic environments and, consequently, to the destruction of biodiversity. With the aim of highlighting the distribution profile of benthic macroinvertebrates in the city of Yaoundé and its surroundings according to the level of degradation, this study was carried out in seven rivers. A total of 144 taxa of benthic macroinvertebrates, belonging to 74 families, 15 orders, five classes, and three phyla, were collected from seven rivers in urban, peri-urban, and forest environments on Yaoundé and its surroundings. The self-organizing map (SOM) analysis tool was used to group the collected taxa from all stations into three clusters or affinity cores. The indicator value analysis (IndVal) method was employed to determine, based on their ecological preferences, which organisms were most likely to belong to each group. Out of the 144 collected taxa, only 44 were indicated to represent the three different groups. Thus, three communities were defined: the Hydropsyche community, with Hydropsyche sp. as the predominant taxon in Group III, characterizing well-oxygenated and low-mineralized stations; the Hydrocyrius community, where the species Hydrocyrius sp. predominates in Group I, describing stations with low oxygenation and moderate mineralization; and the Lumbriculidae community, where Lumbriculidae is the taxon associated with environments with high mineralization and critical oxygenation. These two methods contribute to the biomonitoring of tropical aquatic environments, firstly by grouping organisms by affinity and then identifying those that reflect the environment conditions. This facilitates the detection of changes in the quality of hydrosystems and guides management and conservation efforts. Full article

Soil erosion represents a complex ecological issue that is present on a global level, with negative consequences for environmental quality, the conservation and availability of natural resources, population safety, and material security, both in rural and urban areas. To mitigate the harmful effects of soil erosion, a soil erosion map can be created. Broadly applied in the Balkan Peninsula region (Serbia, Bosnia and Herzegovina, Croatia, Slovenia, Montenegro, North Macedonia, Romania, Bulgaria, and Greece), the Erosion Potential Method (EPM) is an empirical erosion model that is widely applied in the process of creating soil erosion maps. In this study, an innovation in the process of the identification and mapping of erosion processes was made, creating a coefficient of the types and extent of erosion and slumps (φ), representing one of the most sensitive parameters in the EPM. The process of creating the coefficient (φ) consisted of applying remote sensing methods and satellite images from a Landsat mission. The research area for which the satellite images were obtained and thematic maps of erosion processes (coefficient φ) were created is the area of the Federation of Bosnia and Herzegovina and the Brčko District (situated in Bosnia and Herzegovina). The Google Earth Engine (GEE) platform was employed to process and retrieve Landsat 7 Enhanced Thematic Mapper plus (ETM+) and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) satellite imagery over a period of ten years (from 1 January 2010 to 31 December 2020). The mapping and identification of erosion processes were performed based on the Bare Soil Index (BSI) and by applying the equation for fractional bare soil cover. The spatial–temporal distribution of fractional bare soil cover enabled the definition of coefficient (φ) values in the field. An accuracy assessment was conducted based on 190 reference samples from the field using a confusion matrix, overall accuracy (OA), user accuracy (UA), producer accuracy (PA), and the Kappa statistic. Using the confusion matrix, an OA of 85.79% was obtained, while UA ranged from 33% to 100%, and PA ranged from 50% to 100%. Applying the Kappa statistic, an accuracy of 0.82 was obtained, indicating a high level of accuracy. The availability of a time series of multispectral satellite images for each month is a crucial element in monitoring the occurrence of erosion processes of various types (surface, mixed, and deep) in the field. Additionally, it contributes significantly to decision-making, strategies, and plans in the domain of erosion control work, the development of plans for identifying erosion-prone areas, plans for defense against torrential floods, and the creation of soil erosion maps at local, regional, and national levels. Full article

The Korean Demilitarized Zone (DMZ) is an area where human disturbance has been strictly restrained for about seven decades since 1953. As a result, compared with rural and urban areas in Korea with similar ecological conditions, the landscape structure of the Korean DMZ today shows a big difference in that it has a riparian forest and lacks any of the artificial landscape elements, such as agricultural and residential areas. The vegetation maps made in the 1950s and those made in recent years of a model site that extends throughout the DMZ, the Civilian Control Zone (CCZ), and adjacent rural areas show that successional changes in the DMZ and CCZ areas are remarkable, while changes in the rural areas are not clear. Rice fields have been replaced by riparian forests, whereas young forests in areas previously subjected to excessive use and pine forests have been replaced by broad-leaved forests. Among the three landscape elements that changed, it was found that riparian zones, where natural disturbance is usually frequent, could mitigate the impacts of human disturbance and restore the original features of nature sooner than any other elements. The results of analyses on landscape change that focused on rice fields before the Korean War also showed similar results: most of these fields had turned into riparian vegetation. Stand ordination of riparian vegetation investigated in the CCZ, rural areas, and urban areas showed clear differences in species composition and diversity among regions. In this study, we confirmed the passive restoration of the Korean DMZ and CCZ through natural regeneration processes as a result of restricted human disturbance over a period of about seven decades. Full article

The study of Land Use and Landscape Patterns (LULPs) changes and their ecological quality effects in Haikou city under the background of the Hainan Free Trade Port Plan (HFTPP) helps to promote coordinated development between cities and the environment. To date, most research on ecological quality has focused on areas with extremely fragile ecology and/or is related to LULP analysis. There are few studies in the literature focusing on the impact of high-intensity human activities caused by relevant policies on urban LULPs. The purpose of this research was to design a framework that monitors urban ecological security by considering the effect of the developing free trade port. The proposed framework was constructed by integrating multi-temporal Sentinel-2 remote sensing images, night light remote sensing data, digital elevation model (DEM) data, and spectral index features such as the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), bare soil index (BSI), and normalized intertidal mangrove index (NIMI), as well as analytical approaches such as the land use transfer matrix, land use dynamic degree, land use degree and transfer matrix, land use gravity center measurement, and landscape pattern index. The framework takes advantage of the Google Earth Engine (GEE) cloud platform and was applied to a highly developed Haikou city, the capital of Hainan province. Maps of brightness (SBI), greenness (GVI), and humidity (WET) were created annually from 2016 to 2021, enabling detailed ecological environment quality evaluation and analysis. The advantages of this study are (1) reliable land cover results obtained automatically and quickly; (2) the strong objectivity of the quantitative research on landscape patterns and land use; and (3) deep integration with free trade port policies. Through the research on the ecological quality problems caused by the change in LULP in the study area, the research results show that, from 2016 to 2021, the spatial distribution of land use and landscape pattern in Haikou city had been constantly changing; the area of construction land has decreased, with most of it having been converted into forest land and farmland; the gravity center of the building land has moved to the northwest; the degree of landscape fragmentation has decreased and the heterogeneity of landscape distribution has increased; the free trade port policies have promoted Haikou’s economic development and ecological civilization construction; and finally, Haikou’s ecological environmental quality has improved significantly. Full article

The expansion of urban centers and peri-urban zones significantly impacts both the natural world and human well-being, leading to issues such as increased air pollution, the formation of urban heat islands, and challenges in water management. The concept of multifunctional greening serves as a cornerstone, emphasizing the interconnectedness of ecological, social, and health-related factors. This study aimed to identify potential locations for three specific types of blue-green infrastructure (BGI): bioswales, infiltration trenches, and green bus stops. Leveraging geospatial datasets, Geographic Information System (GIS) technology, and remote sensing methodologies, this study conducted a comprehensive analysis and modeling of spatial information. Initial cartographic representations were developed to identify specific locations within Olsztyn, a city in Poland, deemed appropriate for the implementation of the designated blue-green infrastructure (BGI) components. Following this, these models were combined with two additional models created by the researchers: a surface urban heat island (SUHI) model and a demographic model that outlined the age structure of the city’s population. This synergistic approach resulted in the development of a detailed map, which identified potential locations for the implementation of blue-green infrastructure. This was achieved by utilizing vector data acquired with a precision of 1 m. The high level of detail on the map allows for an extremely accurate representation of geographical features and infrastructure layouts, which are essential for precise planning and implementation. This infrastructure is identified as a key strategy for strengthening ecosystem resilience, improving urban livability, and promoting public health and well-being. Full article

Wild edible plants, botanically defined as phytoalimurgical species, have historically been a useful source of food to cope with recurrent famines and poor farming conditions. If properly identified, harvested, transformed and promoted, alimurgical plants could further enhance the wellbeing of rural and urban communities and the multifunctional productivity of agriculture. The research aimed to survey alimurgical species in a wetland, map their location, detect their spatial richness, and develop a monitoring plan for ongoing vegetation succession. The study area is the King’s Lagoon, a wetland that has recently undergone a radical restoration of its natural layout. A satellite image was used to create a land cover map and interpret the relationship between plant species and land cover. The survey provided a snapshot of the wetland’s current ecosystem status and used botanical analysis and ecological indices to investigate biodiversity levels. The alpha, beta and gamma levels of biodiversity were explored and interpreted through the statistical processing of a comprehensive dataset of species occurrence and abundance, together with the calculation of Shannon’s, Simpson’s and Jaccard’s indices. It was observed that biodiversity in the wetland is developing gradually following restoration and is expected to increase over time as successional stages take hold. Biodiversity is more pronounced along the banks of the canals and watercourses connecting the basins and open ponds, while it is less pronounced in areas where the soil has been disturbed by previous excavations. Salicornia spp., Beta vulgaris subsp. maritima and Suaeda vera were identified as the most common and interesting species found in the study area. The potential for cultivation of some of the halophyte species that were monitored was also highlighted, with particular reference to the selection of the most commercially interesting species, the best species associations and intercropping practices in a wetland context, which must always prioritize the conservation of wild biodiversity. The spring surveys should be repeated in the coming years in order to accurately trace the dynamics of the ecological succession of this particular ecosystem, once it has returned to its natural development. Full article

The present research aimed to measure the degree of connectivity and create a map of the ecological connectivity that highlights the real or potential presence of green, ecological, or ecotourism circuits integrating the green infrastructure of San Juan de Lurigancho and the Mangomarca hills using graph theory applications implemented in the Graphab 2.8 software. Mangomarca and Huiracocha Park were selected for this study. In terms of the methodology, a simple approach based on landscape metrics, which are easy to interpret, was proposed to measure the connectivity of the mosaic of patches in the designated area. The IndiFrag software was used to obtain landscape metrics for the structural connectivity analysis. The Graphab software was employed for the functional connectivity analysis. Both tools proved effective in identifying vegetation gaps or the intensity of the greenery. Landsat 8 images from 8 July 2021 and 4 October 2021 were selected for this research due to the lower amount of cloud cover. Concerning the structural connectivity, the TMCl (patch size), NobCl (number of patches), and PerimCl (perimeter) metrics were effective in distinguishing the mosaic of urban landscape patches from the hill landscape. These indices confirm that the urban landscape patches have a higher number of fragments but are smaller in size compared to the hill landscape. Regarding the functional connectivity, it is evident that the patches are connected at lower-cost distances, averaging 7 cost units (210 m) during the wet season and 23 cost units (410 m) during the less humid season. However, these distances are too extensive and do not form ecological corridors. A survey of the population’s perception of the maximum separation distances between patches of vegetation cover that could still be considered a green corridor was included. The results indicate that a third of the sample (36%) prefer to walk down a hallway with a maximum separation distance of 10 m, while almost two-thirds (68%) would prefer a maximum separation distance of 50 m. Therefore, city planning should consider actions to reduce these distances and enable ecological connectivity in the area. It is recommended to continue researching the functional connectivity and determining the green corridors in the city to establish monitoring guidelines for the ecological connectivity of the city. Full article