Search Results (60)

In this work, we evaluated the silvicultural and ecological parameters of Populus bolleana Lauche trees growing in conditions of anthropogenic pollution, using the example of one of the largest megacities of the Donetsk ridge, the city of Donetsk. The objectives of this study included determining the level of anthropogenic load of the territory; conducting dendrological studies to assess morphometric and allometric parameters, age structure, and condition of P. bolleana stands under the influence of environmental factors; as well as completing biomechanical studies to assess and predict the mechanical stability of stands. A total of 1109 plants growing in areas with increased anthropogenic load and in the control areas were studied. The model territories of the study were located in the city of Donetsk on Fallen Communards Avenue (length of field routes: 2.6 km) and Ilyicha Avenue (length of field routes: 9.7 km). Control plantings grew on the territory of the Donetsk botanical garden and residential (dormitory) districts of the city. The age structure of P. bolleana plantations remained uniform throughout the city for 50–55 years due to the fact that the landscaping was under a single state program. In the steppe zone in the south of the East European Plain, with a high level of anthropogenic load and severe natural climatic factors, the critical age of P. bolleana (55 years) was determined. The condition of plantations and their morphometric indices correlate with the level of anthropogenic load of the city (H, Dbase, DBH). Under control conditions, the plants are in good condition with signs of weakening (2 points). Under conditions of increased anthropogenic load, the plants are in a severely weakened condition (3 points). A total of 25% of the plants in the sample are in critical condition (4–5 points). The main damages to the crowns and trunks of plants include core rot, mechanical damage to bark and tissues, the development of core rot through the affected skeletal branch, crown thinning, and drying. P. bolleana trees are valued for their crown area and ability to retain dust particles from the air. The analysis of experimentally obtained data on the crown area showed that in the initial phases of ontogenesis, the average deviation in the crown area of plants does not depend on the place of growth. Due to artificial narrowing and sanitary pruning of the crown, as well as skeletal branches dying along the busiest highways, the values do not exceed 22–23 m² on average, with an allometric coefficient of 0.35–0.37. When comparing this coefficient in the control areas, the crown area in areas with a high level of anthropogenic load is 36 ± 11% lower. For trees growing under the conditions of the anthropogenic load of an industrial city and having reached the critical age, mechanical resistance varied depending on the study area and load level. At sites with a high level of pollution of the territory, a significant decrease in indicators was revealed in comparison with the control (mcr—71%, EI—75%, RRB—43%). Having analyzed all the obtained data, we can conclude that, until the age of 50–55 years, P. bolleana retains good viability, mechanical resistance, and general allometric ratios, upon which the stability of the whole plant depends. Even with modern approaches and tendencies toward landscaping with exotic introductions, it is necessary to keep P. bolleana as the main species in dendrobanocenoses. Full article

Wildlife-vehicle collisions (WVCs) threaten biodiversity, particularly in the Gulf of Mexico, where road expansion increases habitat fragmentation. This research analyzes WVC patterns in southeastern Mexico, estimating collision rates across road types and assessing environmental factors influencing roadkill frequency. Field monitoring in 2016 and 2023 recorded vertebrate roadkills along roads in Campeche, Chiapas, and Tabasco. Principal Component Analysis (PCA) and Generalized Additive Models (GAM) evaluated landscape influences on WVC occurrences. A total of 354 roadkill incidents involving 73 species of vertebrates were recorded, with mammals accounting for the highest mortality rate. Hotspots were identified along Federal Highway 259 and State Highways Balancán, Frontera-Jonuta, and Salto de Agua. Road type showed no significant effect. Land cover influenced WVCs, with cultivated forests, grasslands, and savannas showing the highest incidences. PCA identified temperature and elevation as key environmental drivers, while GAM suggested elevation had a weak but notable effect. These findings highlight the risks of road expansion in biodiversity-rich areas, where habitat fragmentation and increasing traffic intensify WVCs. Without targeted mitigation strategies, such as wildlife corridors, underpasses, and road signs, expanding infrastructure could further threaten wildlife populations by increasing roadkill rates and fragmenting habitats, particularly in ecologically sensitive landscapes like wetlands, forests, and coastal areas. Full article

The conservation of biodiversity and the balance between ecological and societal needs are critical but often contested global issues. Wildlife-vehicle collision (WVC) on vital infrastructure, especially linear infrastructure, remains a persistent challenge from policy to practice and poses a serious life-threatening implication to humans and other non-human lives. Addressing this issue effectively requires solutions that provide win-win outcomes from both ecological and societal perspectives. This study critically analyzes a decade of roadkill incidents along Nepal’s longest East-West national highway, which passes through a biologically diverse national park in the western Terai Arc Landscape Area (TAL). Findings are drawn from field-based primary data collection of the period 2012–2022, secondary literature review, key informant interviews, and spatial analysis. The study reveals significant variations in roadkill incidence across areas and years. Despite Bardia National Park being larger and having a higher wildlife density, Banke National Park recorded higher roadkill rates. This is attributed to insufficient mitigation measures and law enforcement, more straight highway segments, and the absence of buffer zones between the core park and adjacent forest areas—only a road separates them. Wild boars (Sus scrofa) and spotted deer (Axis axis), the primary prey of Bengal tigers (Panthera tigris tigris), were the most frequently road-killed species. This may contribute to human-tiger conflicts, as observed in the study areas. Seasonal trends showed that reptiles were at higher risk during the wet season and mammals during winter. Hotspots were often located near checkpoints and water bodies, highlighting the need for targeted mitigation efforts such as wildlife crossings and provisioning wildlife requirements such as water, grassland, and shelter away from the regular traffic roads. Roadkill frequency was also influenced by forest cover and time of day, with more incidents occurring at dawn and dusk when most of the herbivores become more active in search of food, shelter, water, and their herds. The findings underscore the importance of road characteristics, animal behavior, and landscape features in roadkill occurrences. Effective mitigation strategies include wildlife crossings, speed limits, warning signs, and public education campaigns. Further research is needed to understand the factors in driving variations between parks and to assess the effectiveness of mitigation measures. Full article

Ecoacoustics examines the interactions between soundscapes, ecological processes, and anthropogenic disturbance. Acoustic communication is crucial for wildlife, making noise pollution a key factor in shaping biodiversity, though its effects are also modulated by habitat characteristics. In this work, we assess the influence of highway noise and vegetation structure on the soundscape and avian distribution of the Moriano oxbow lake (Bereguardo, PV, Italy), a Site of Community Importance in the Ticino Valley Regional Park. A two-week monitoring campaign (April 2022) used eight recorders arranged in a grid to analyze soundscape dynamics through eight ecoacoustic indices (ACI, ADI, AEI, BI, NDSI, H, DSC, ZCR). Vegetation surveys quantified tree diversity and structural parameters such as basal area, height, stem density, biomass, and leaf cover. Correlation analyses revealed that Quercus robur abundance and tree diversity significantly influenced the acoustic environment, while bird richness correlated positively with vegetation biomass and Quercus robur presence. Highway proximity was a key structuring factor, with indices (ADI, H, NDSI, ACI) increasing with distance. These findings underscore the dual role of noise and vegetation in shaping soundscapes and highlight the importance of incorporating habitat features into ecoacoustic assessments to better understand biodiversity patterns in anthropized landscapes. Full article

Moving away from a static concept for the landscape that surrounds us, in this research article, we approach the visual landscape as a dynamic concept. Moreover, we attempt to provide an interconnection between the domains of landscape and cartography by designing maps that are particularly suitable for characterizing the visible landscape and are potentially meaningful for overall landscape evaluation. Thus, the present work mainly focuses on the consecutive computation of vistas along highways, incorporating actual landscape composition—as the landscape is perceived from an egocentric perspective by observers moving along highway routes in peri-urban landscapes. To this end, we developed an integrated method and a Python (version 2.7.16) tool, named “RouteLAND”, for implementing an algorithmic geoprocessing procedure; through this geoprocessing tool, sequences of composite dynamic geospatial analyses and geometric calculations are automatically implemented. The final outputs are interactive web maps, whereby the segments of highway routes are characterized according to the dominant element of the visible landscape by employing (spatial) aggregation techniques. The developed geoprocessing tool and the generated interactive map provide a cartographic exploratory tool for summarizing the landscape character of highways in any peri-urban landscape, while hypothetically moving in a vehicle. In addition, RouteLAND can potentially aid in the assessment of existing or future highways’ scenic level and in the sustainable design of new highways based on the minimization of intrusive artificial structures’ vistas; in this sense, RouteLAND can serve as a valuable tool for landscape evaluation and sustainable spatial planning and development. Full article

Trails and tracks are the detectable signs of passage of wildlife and off-highway vehicles in natural landscapes. They record valuable information on the presence and movement of animals and humans. However, published works aimed at mapping trails and tracks with remote sensing are nearly absent from the peer-reviewed literature. Here, we demonstrate the capacity of high-density LiDAR (light detection and ranging) and convolutional neural networks to map undifferentiated trails and tracks automatically across a diverse study area in the Canadian boreal forest. We compared maps developed with LiDAR from a drone platform (10 cm digital terrain model) with those from a piloted-aircraft platform (50 cm digital terrain model). We found no significant difference in the accuracy of the two maps. In fact, the piloted-aircraft map (F1 score of 77 ± 9%) performed nominally better than the drone map (F1 score of 74 ± 6%) and demonstrated a better balance among error types. Our maps reveal a 2829 km network of trails and tracks across the 59 km² study area. These features are especially abundant in peatlands, where the density of detected trails and tracks was 68 km/km². We found a particular tendency for wildlife and off-highway vehicles to adopt linear industrial disturbances like seismic lines into their movement networks. While linear disturbances covered just 7% of our study area, they contained 27% of all detected trails and tracks. This type of funnelling effect alters the movement patterns of humans and wildlife across the landscape and impedes the recovery of disturbed areas. While our work is a case study, the methods developed have broader applicability, showcasing the potential to map trails and tracks across large areas using remote sensing and convolutional neural networks. This capability can benefit diverse research and management communities. Full article

Due to the high volume of traffic on European highways and the increased percentage of traffic accidents and fatalities, traffic safety is imperative in the planning and design of highways. While highway safety design construction standards have been extensively researched, insufficient attention has been given to the influence of the surrounding landscape on traffic safety and to drivers’ awareness about the danger of the same. Thus, the aim of the research was to assess drivers’ perceptions of various factors impacting highway traffic safety (climatic impacts from the surrounding landscape, landscape vegetation that follows the roadway, and animals) beyond specific engineering features (roadway surface, traffic signs, highway junction points). A survey of 138 drivers was conducted to assess driver awareness of traffic safety on the research section of a highway in Serbia. This highway is part of the Serbian highway that is a key connection within the European road network, forming an integral part of several major routes. The survey revealed that drivers, regardless of gender or experience, primarily associate traffic safety with well-built roads and good visibility during driving. While the impacts of climatic elements from the surrounding landscape were acknowledged, drivers do not strongly attribute any danger to traffic safety from these factors due to their lack of visibility. This is reflected in the notable number of traffic accidents, impacted by these factors, on the studied highway (e.g., 12% of the total number of accidents during 2022). Vegetation and animals did not play a significant role in the respondents’ answers, which should not be the case; however, their absence in the highway landscape and along the roadway led to a lack of observed quality by drivers. This underscores the need for the scientific community and policymakers to delve deeper into these issues with a broader perspective, and to elevate highway safety standards accordingly. Full article

The green vision rate of rural highway greening landscape is a key factor affecting the driver’s visual load. Based on this, this paper uses the eye tracking method to study the visual characteristics of drivers in different green vision environments on rural highways in Xianning County. Based on the HSV color space model, this paper obtains four sections of rural highway with a green vision rate of 10~20%, green vision rate of 20~30%, green vision rate of 30~40%, and green vision rate of 40~50%. Through the real car test, the pupil area, fixation time, saccade time, saccade angle, saccade speed, and other visual indicators of the driver’s green vision rate in each section were obtained. The visual load quantization model was combined with factor analysis to explore the influence degree of the green vision rate in each section on the driver’s visual load. The results show that the visual load of the driver in the four segments with different green vision rate is as follows: Z10~20% > Z20~30% > Z30~40% > Z40~50%. When the green vision rate is 10~20%, the driver’s fixation time becomes longer, the pupil area becomes larger, the visual load is the highest, and the driving is unstable. When the green vision rate is 40% to 50%, the driver’s fixation time and pupil area reach the minimum, the visual load is the lowest, and the driving stability is the highest. The research results can provide theoretical support for the design of rural highway landscape green vision rate and help to promote the theoretical research of traffic safety. Full article

The need to enrich the semantic completeness of OpenStreetMap (OSM) data is crucial for its effective use in geographic information systems and urban studies. Addressing this challenge, our research introduces a novel hierarchical feature augmentation approach to developing machine learning classifiers by the features retrieved from various levels of road network connectivity. This method systematically augments the feature space by incorporating measure values of connected road features, thereby integrating extensive contextual information from the network hierarchy. In our evaluation, conducted across diverse urban landscapes in six cities in Italy and Türkiye, we tested two geometry-, six centrality-, and eight semantic-based features to predict road functional classes stored as a highway = * key in OSM. The findings indicate a marginal impact of geometric features and city identifiers on classification performance. Utilizing centrality attributes alongside semantic features in a direct, non-hierarchical manner results in an F1 score of 80%. However, integrating these features in our network-based hierarchical feature augmentation process remarkably increases the F1 score up to 85%. The success of our approach underlines the importance of network-based feature engineering in capturing the complex dependencies of geographic data, considering a more accurate and contextually aware OSM classification framework. Full article

Ecological sensitivity is an essential indicator for measuring the degree of ecological fragility of a region, and traditional highway routing ignores the ecological benefits of regional nature, which causes irreversible impacts on the natural environment. Based on the AHP method, this paper carries out a comprehensive assessment of the ecological sensitivity of the K0+000~K56+438 section of the Guanzhuang Tourist Highway in the Zhangjiajie Wuling Mountain Area from 2000 to 2020, and it utilizes the spatial autocorrelation analysis method to reveal the pattern of its spatial and temporal changes in ecological sensitivity. The following results were obtained. (1) The ecological condition of the study area is gradually improving, and the areas with higher sensitivity are mainly distributed in the northeast and southwest of the study area. (2) The ecological sensitivity of the study area has strong spatial autocorrelation, but the autocorrelation has been reduced in recent years, and the distribution of the ecological sensitivity has been gradually discretized. (3) There are problems of high ecological risk and construction difficulty in the traditional highway route selection scheme of the A line. The optimized route selection scheme, the K line, can effectively avoid highly sensitive areas by adjusting the route and bridge settings. Finally, the article proposes engineering construction suitability and ecological restoration strategies for different road sections regarding vegetation cover, landscape risk, and geological hazards. This study establishes a set of comprehensive technical chains for tourism highway routing in ecologically fragile areas based on the spatial and temporal evolution of sensitivity, which provides new ideas for traditional highway routing and is of great significance for maintaining the balance and stability of ecosystems within the road area. Full article

Traditional orchards are distinctive features of cultural landscapes in Central Europe. Despite their high level of ecological importance, they are in decline, and comprehensive spatial data over broad extents, which could enable a trend analysis, are lacking. We analysed traditional orchard maps from 1952 to 1967 and a map from 2010, generated via aerial image interpretation, for the state of Hesse (ca. 21,115 km²), which has the second largest share of traditional orchards in Germany. We aimed to (1) quantify long-term orchard dynamics, (2) compare orchard characteristics in terms of topographical, ecological, and socioeconomic factors, and (3) identify key drivers of orchard loss. We found that the number and area of orchards have clearly decreased across Hesse, with varying local and regional patterns. Further, historically old orchards tended to have a larger area, higher shape complexity, and were located closer to settlements, highways, and neighbouring orchards. In contrast, newly established orchards were often found at higher elevations and on steeper slopes. Finally, the three historical orchard hotspots also experienced the most notable losses driven by different factors, namely the expansion of Artificial Surfaces, Residential Buildings, and Agricultural Land. We highlight the importance of such multitemporal spatial data for a wide range of ecological applications, and we encourage the use of novel technologies to support geospatial analyses in the future. Full article

After the loss and fragmentation of habitat, vehicle collisions are one of the main threats to the long-term survival of wild koalas. Koala road strike data were analysed for a section of the Peak Downs Highway between Nebo and Spencer’s Gap, west of Mackay, Queensland, Australia. The analysis was carried out on 345 records (October 2014 to November 2023), and results suggested the spatial distribution of koala road strike followed a random pattern along this section of the highway, assuming a Poisson point pattern on a linear network. An analysis of the candidate predictors of koala vehicle collisions, including habitat and road variables, found that the amount of high-quality koala habitat (as defined by the local koalas’ tree species preference) present and the driver visibility were the only significant predictors. The relative homogeneity of landuse and vegetation across this landscape may mean that koalas do not concentrate at specific crossing points. More research, including detailed habitat mapping, is needed into this population, which currently lacks government and conservation attention, to inform mitigation efforts and reduce mortality rates for this potentially nationally significant population. Full article

The intersectional relationship in bridge health monitoring refers to the mapping function that correlates bridge responses across different locations. This relationship is pivotal for estimating structural responses, which are then instrumental in assessing a bridge’s service status and identifying potential damage. The current research landscape is heavily focused on high-frequency responses, especially those associated with single-mode vibration. When it comes to low-frequency responses triggered by multi-mode vehicle loading, a prevalent strategy is to regard these low-frequency responses as “quasi-static” and subsequently apply time-series prediction techniques to simulate the intersectional relationship. However, these methods are contingent upon data regarding external loading, such as traffic conditions and air temperatures. This necessitates the collection of long-term monitoring data to account for fluctuations in traffic and temperature, a task that can be quite daunting in real-world engineering contexts. To address this challenge, our study shifts the analytical perspective from a static analysis to a dynamic analysis. By delving into the physical features of bridge responses of the vehicle–bridge interaction (VBI) system, we identify that the intersectional relationship should be inherently time-independent. The perceived time lag in quasi-static responses is, in essence, a result of low-frequency vibrations that are aligned with driving force modes. We specifically derive the intersectional relationship for low-frequency bridge responses within the VBI system and determine it to be a time-invariant transfer matrix associated with multiple mode shapes. Drawing on these physical insights, we adopt a time-independent machine learning method, the backpropagation–artificial neural network (BP-ANN), to simulate the intersectional relationship. To train the network, monitoring data from various cross-sections were input, with the responses at a particular section designated as the output. The trained network is now capable of estimating responses even in scenarios where time-related traffic conditions and temperatures deviate from those present in the training data set. To substantiate the time-independent nature of the derived intersectional relationship, finite element models were developed. The proposed method was further validated through the in-field monitoring of a continuous highway bridge. We anticipate that this method will be highly effective in estimating low-frequency responses under a variety of unknown traffic and air temperature conditions, offering significant convenience for practical engineering applications. Full article

Amidst rapid urbanization and escalating environmental degradation in China’s urban areas due to climate change, traditional drainage systems struggle to cope with rainfall, resulting in frequent flood disasters. In response, rain gardens have emerged as ecologically practical stormwater management solutions that integrate urban flood control with landscape design. Leveraging the dual benefits of rainwater purification and aesthetic enhancement provided by vegetation, herbaceous plant-based rain gardens have assumed a pivotal role in green infrastructure. However, dedicated research on the application of herbaceous plants in rain garden design is limited, especially within China’s water-stressed context. This study employs a literature review and case analysis to explore this critical issue. Initially, it delineates the concept of the sponge city introduced by the Chinese government. Subsequently, it reviews concepts and methods of plant biodiversity design in urban settings and rain gardens and elucidates the structure and function of rain gardens. Four Chinese rain gardens in different urban environments (old industrial areas, university campuses, urban villages, and urban highway green belts) were selected to examine the selection and arrangement of herbaceous plants while identifying deficiencies in their designs. Finally, feasibility suggestions are provided for the design of herbaceous plant diversity in Chinese rain gardens. This study’s findings can provide a reference for the planting design of herbaceous plants in rain gardens for other countries and regions with similar climates and environmental conditions. Full article

Currently, the use of modern technologies, such as UAVs, allows for a detailed analysis of the protection of Sites of Cultural Interest (BICs) in Spain. Cala Castle in Huelva is selected for this study, which is one of the most important medieval fortifications in the mountainous region and was rehabilitated between 2003 and 2011. After a decade of its architectural rehabilitation, the use of this new UAV technology will allow the creation of a database of the property and its surroundings, made up of a series of 3D models and photogrammetric studies of the territory. This analysis allows us two complementary readings to the original study: on the one hand, to characterize the natural and landscape context of Cala Castle, and on the other, to identify the pre-existence of a series of historic buildings, which have historically articulated this region. The 3D models obtained provide relevant graphic information. The current state of the BIC allows this space to be considered for reactivation as a social space at the regional level. The visuals of the regional environment allow us to identify that the most recent growth has been articulated longitudinally along the N-630 highway, this infrastructure being the backbone of the nucleus. As a pilot test, the beginning of this graphic and visual database (3D) at a regional level will provide a valuable tool for the conservation and registration of built heritage, given that it seeks to incorporate other fortifications that make up Banda Gallega with the aim of defining a sustainable development strategy at county level. Full article