Urban Landscape Management Research Articles

Examining the Change of Green View Index (GVI) at Street Eye-Level with GSV and YSV

Green spaces in cities make them look better and benefit the environment and people's well-being. Spending time in nature reduces stress, improves mental relaxation, and increases happiness. Green spaces also encourage people to be more active, which strengthens muscles, improves heart health, and reduces the risk of obesity. Tools like Google Street View (GSV) and Yandex Street View (YSV) simplify tracking and assessing these urban green areas. This gives planners up-to-date information to effectively plan and manage cityscapes. However, limitations exist. Information on street-level greenery assessment can be scarce, making planning challenging. This study used the Green View Index (GVI) to assess street greenery using GSV images. The study found GSV and YSV to be good tools for assessing and monitoring street-level greenery. GVI was also suggested as a possible way to objectively measure street-level greenness, which could be useful for urban landscape planning and management.

Exploring the potentials of urban crop farming and the question of environmental sustainability

As part of efforts to promote urban green spaces in increasingly urbanized cities of Africa, urban crop farming (UCF) has become a necessary pillar of urban environmental sustainability. Beyond the primary functions of food security and employment, UCF contributes to greening the urban environment and provides valuable options for urban regeneration within the broad components of environmental, social, and economic sustainability. We draw on interviews and focus group discussions in Tamale, a rapidly urbanizing Ghanaian metropolis, to examine the potential of UCF and the question of urban environmental sustainability. Our findings revealed the tremendous contributions of UCF to the provision of greenery, beautiful scenery, healthy spaces, socio-economic inclusion, and environmental restoration. We argue that reflecting and incorporating these findings in policy will be helpful for urban landscape planning and management.

Urban Landscape Management of Makassar City Based on Waterfront City Concept

Abstract Makassar City is one of the coastal cities in Indonesia with a 32 km long coastline. This extensive coastal stretch harbors numerous potential natural resources. Recognizing the coastal region’s potential, the government has been implementing the Waterfront City concept to develop and manage this area. Since 2003, the Makassar City government has actively undertaken revitalization and reclamation efforts in the coastal zone, aiming to establish various facilities including commercial areas, public parks, residential zones, and tourism infrastructure, all with the aim of achieving the status of a waterfront city. However, these ongoing development and reclamation activities are inevitably transforming the coastal landscape, bringing about both positive and negative changes. On the downside, there are adverse effects such as deteriorating water quality and diminishing mangrove areas. Conversely, there has been an increase in tourist arrivals, showcasing a positive aspect. This study aims to assess the suitability of land in the coastal areas and the visual appeal of Makassar City’s waterfront, providing recommendations for coastal landscape management. Based on the analysis of land suitability and the aesthetics of the coastal area of Makassar City, the urban areas generally possess land suitable for implementing the waterfront city concept, categorized into three zones: tourism, residential, and conservation, to optimize land functionality. Besides the quality of the beautiful coast has a fairly good value with a neat and clean conditions.

Unveiling the dynamics of urbanization and ecosystem services: insights from the Su-Xi-Chang Region, China

Assessing the impact of past and future urban land expansion on ecosystem services (ESs) is essential for the sustainable management of urban landscapes. Despite recent progress, it remains challenging to determine the influence mechanism of different urbanization stages and areas on ESs and their trade-offs/synergies. Here, we analyzed the responses of four ESs and their trade-offs/synergies to the spatial and temporal differentiation of urbanization in the Su-Xi-Chang region of China from 1990 to 2050. The results showed that the relationship between ESs and urbanization followed a U-shaped curve from 1990 to 2050. Between 1990 and 2020, urbanization weakened trade-offs and enhanced lose-lose situations, exhibiting an S-shaped curve. From 2020 to 2050, lose-lose situations are expected to diminish, and the curve is projected to display a downward trend. Our findings suggest the implementation of compact urban development, sustainable agricultural practices, reforestation, and the conversion of farmland to lakes.

The making of the Chinese urban landscape: Exploring a framework for analysis

Despite sociopolitical changes, urban landscape heritage has traditionally been valued in Chinese society. However, in the past two to three decades, intensifying pressures for urban redevelopment have created major challenges to urban landscape management. While the management of urban landscape change has focused on landscape-based conservation techniques, urban landscape characterization and assessment, and urban landscape planning, its theoretical and practical foundations remain to be clarified. In connection with the epistemological orientations of landscape in both China and the outside world, this article proposes a new conceptual framework comprising a triad of structural-correlative, morphogenetic-generative, and integrated perspectives for the study and management of urban landscape heritage in China.

Preparation of future development scenarios of urban landscapes in accordance with natural and socio-economic conditions (on the example of the cities of the Kura-Araz lowland)

Problems Statement and Purpose. More than 50% of the world's population lives in cities. In Azerbaijan, 53% of the population lives in cities. For this reason, almost all global problems originate from urban landscapes. Therefore, it is very important to study the development of cities and prepare the future scenario. Our goal is to study the cities located in the Kura-Araz plain, determine their annual growth rate and forecast future development trends. Data and Methods. In the article, the development of 17 cities located in the Kur-Araz plain in the central part of Azerbaijan during the historical period and its future forecast were analyzed. Modern methods were especially preferred during the research. Satellite images of cities were processed and the results were analyzed. Satellite images from 1975 and 2023 were used and deciphered in determining the boundaries of cities and studying their dynamics. The dynamics of changes in the areas of the cities were studied by determining the boundaries of the cities, and the dynamics of population growth was studied and analyzed. Statistical analyzes were used in the study of the population. Results and Discussion. The cities of Kura-Araz lowland cover 25% of the cities of the republic. These rivers are the main source of the formation of cities. However, as these coastal cities grew, the ecological problems of the Kura and Araz rivers increased and the water level decreased. Cities have grown in all directions and are still growing. For the first time in Azerbaijan, urban landscapes were studied based on GIS technologies and Remote Sensing methods. For the first time, the factors of natural conditions, the absolute height, inclination and exposure of the terrain were analyzed based on GIS technologies, and it was determined that 2/3 of the research area is located below sea level, and 1/3 is located in areas up to a maximum of 200 m absolute height. The inclination of the area continues up to a maximum of 5⁰. Cities have been classified in different directions. Conclusion. For the first time, issues of territorial management of urban landscapes were conducted and mapped on the basis of GIS technologies. At this time, it was determined that cities have grown more than 2 times during 1975-2023. However, this increase cannot be compared with the dynamics of population growth. Because during these years, the population growth has varied between 10-30%. Urban landscapes have grown mainly in riverside areas, along transport routes.

Enhancing ecological network establishment with explicit species information and spatially coordinated optimization for supporting urban landscape planning and management

While insightful, ecological networks (ENs) incorporated in landscape planning and management may not provide a sufficient reference for maintaining biodiversity without explicit species information and coordinated actions, particularly in urban agglomeration areas. To address this gap, we conducted a study in Southern Jiangsu to refine the habitat ranges of 25 target species within the current ecological spaces by integrating explicit species information and diversified environmental variables using the MaxEnt model. Subsequently, an eco-space network and a habitat network were established for the region with identified connectivity hotspots as strategic areas for optimizing ENs. To assess the potential impacts of divergent actions during implementation, we developed four decision-making criteria from global and local views to simulate multiple optimization scenarios. These scenarios were quantitatively evaluated based on connectivity performance using cohesive metrics derived from complex network theory. Our findings demonstrated that incorporating species distribution and their interactions with the environment into ENs establishment can strengthen biodiversity conservation planning schemes within a limited range of regional ecological spaces. Furthermore, it highlighted shortcomings such as lack of focus on landscape priorities, discrepancies in corridors, and underestimation of landscape fragmentation caused by solely relying on an eco-space network-based approach. During optimization efforts, our results revealed that adopting a criterion focused on maximizing the number of strategic areas while adhering to a total area threshold can lead to a more connected and effective habitat network strategy when coordinating individual cities from a global view. This study provides valuable insights into prioritized landscapes and offers practical contributions toward mitigating biodiversity loss and improving urban sustainability.

Reaching beyond GIS for comprehensive 3D visibility analysis

Visibility analyses are one of the fundamental geospatial processing tasks applied in various fields. Recent technological advancements have accelerated viewshed calculations and improved their accuracy thanks to the growing availability of high-resolution spatial data. However, limitations of standard GIS tools, primarily related to the inability to perform analyses in a fully three-dimensional environment and the restriction to only point-based object analyses, have hindered the development of visibility analyses methods that accurately replicate human perspectives. This article presents a novel approach that combines GIS with 3D graphic software and uses high resolution LIDAR data. The presented method not only addresses the limitations of traditional GIS methods but also opens up new possibilities for comprehensive 3D visibility analyses that can better represent real-world scenarios. The proposed methodology, which ensures compatibility of the results with GIS for further spatial analysis, has the potential to enhance decision-making processes in fields such as urban planning, landscape management and protection, environmental impact assessment, infrastructure planning and development. By presenting a case study involving a photovoltaic farm, this article demonstrates the practical applicability and benefits of the proposed method in real-world scenarios.

Beyond just green: Explaining and predicting restorative potential of urban landscapes using panorama-based metrics

Amidst the growing concerns about mental health issues among urban dwellers, there has been increased attention to the restorative potential (RP) of urban landscapes. However, research into the relevant landscape features tends to lack the integration of quantifiable methodologies, which are essential for practical implementation in urban planning and management. To address this gap, our study employed panorama-based metrics relying on computer vision to quantify the features of urban landscapes. We established an explanatory (generalized linear mixed model, GLMM) and a predictive (Random Forest) model to comprehensively elucidate the relationship between these landscape features and RP. The RP outcome was derived from an online survey of respondents (n = 1500) with diverse socio-demographic characteristics, where each respondent was randomly assigned panoramic images from a pool of a hundred landscape scenes taken across the city of Singapore. The GLMM regression identified sky, tree, water, and depth as the primary influences of RP. Furthermore, the Random Forest model demonstrated commendable predictive performance and was used to visually showcase the scenes within the testing dataset with corresponding RP outcomes. To illustrate the potential application of this predictive tool, we also performed spatial mapping for RP prediction, taking the Singapore Botanic Gardens as an example. The subsequent discussion underscored the simultaneous effect of tree, sky, and depth on RP from a quantitative perspective using LOWESS curves. By employing metrics and models that explain and predict the RP, this study contributes evidence-based insights that underscore the pivotal role of trees and openness (sky and depth) in enhancing the psychological benefits of urban landscapes and provides an effective predictive tool that contributes to urban landscape planning and management.

Community science enhances modelled bee distributions in a tropical Asian city

AbstractBees and the ecosystem services they provide are vital to urban ecosystems, but little is understood about their distributions, particularly in the Asian tropics. This is largely due to taxonomic impediments and limited inventorying, monitoring, and digitization of occurrence records. While expert collections (EC) are demonstrably insufficient by themselves as a data source to model and understand bee distributions, the boom of community science (CS) in urban areas provides an untapped opportunity to learn about bee distributions within our cities. We used CS observations in combination with EC observations to model the distribution of bees in Singapore, a small tropical city‐state in Southeast Asia. To address the restricted spatial context, we performed multiple bias corrections and show that species distribution models performed well when estimating the distribution of habitat specialists with distinct range limits detectable within Singapore. We successfully modelled 37 bee species, where model statistics improved for 23 species upon the incorporation of CS observations. Nine species had insufficient EC observations to obtain acceptable models, but could be modelled with the incorporation of CS observations. This is the first study to combine both EC and CS observations to map and model the occurrences of tropical Asian bee species for a highly urbanized region at such fine resolution. Our results suggest that urban landscapes with impervious surfaces and higher temperatures are less suitable for bee species, and such findings can be used to advise the management of urban landscapes to optimize the diversity of bee pollinators and other organisms.

Mapping development preferences on the perceived value of ecosystem services and land use conflict and compatibility in Greater Kuala Lumpur

Rapid and unplanned development can diminish the social values for ecosystem services associated with urban landscapes. Tropical Global South cities, such as Greater Kuala Lumpur (GKL), Malaysia, that are highly biodiverse, are particularly vulnerable to the fragmentation and loss of natural ecosystems. This study investigates the social values for ecosystem services in GKL, a rapidly urbanising metropolitan area in Southeast Asia and presents the novel application of the SolVES (Social Values for Ecosystem Services) tool to an urban area. A public participatory GIS (PPGIS) survey was conducted to assess residents’ development preferences and perceived distribution of social values. The study revealed two groups of respondents, using cluster analysis, each with unique development preferences - a group favouring both green and grey developments and another favouring green development but strongly opposing grey development. The two groups differed statistically in their sociodemographic characteristics, and also how they mapped different social values. Our spatial analysis of their preferences towards future urban expansion in GKL highlighted locations where there is potential for land-use conflict. For example, the favour-balanced-development group tended to value built areas over green spaces. These findings support the need to consider residents’ preferences and socioecological traits through greater public engagement in urban landscape management.

Impact of population growth and housing development on the riverine environment: Identifying environmental threat and solution in the Wanggu River, Indonesia

Economic growth in the nickel mining sector in Southeast Sulawesi Province, Indonesia, has accelerated development and population in Kendari City. The impact of increased immigration, transmigration, and urbanization increases the problem of deforestation to support the construction of people's homes in urban areas will result in damage to the ecosystem of the Wanggu River, Kendari City. This research uses geomorphology, demography, and ecology approaches to identify natural conditions with aerial photographs and satellite images (Google earth) simulated using ArcGis version 10.8. Then, it simulates the potential impact of flooding and pollution of the river environment due to the construction of people's houses around the riverside buffer. The study's findings reveal a discernible correlation between population growth and the heightened risk of ecological degradation within the river environment. The expansion of residential housing exerts significant stress on the river environment, resulting in the degradation of riparian areas and an increase in the river's pollution load. This deterioration in geomorphological, demographic, and ecological conditions within the river system has a direct and adverse impact on the overall health of the river ecosystem. Moreover, the results of the dynamics system simulation unequivocally indicate that river pollution is a persistent concern, with detrimental consequences extending to the mangrove area situated at the mouth of the Wanggu River, notably affecting pollution in Kendari Bay. The improvement of the built river area is useful for improving the landscape function of the river area, preventing erosion, and self-restoration of cities with rivers for ecological restoration, urban planning, and ecological management of urban landscapes in semi-arid areas with high rainfall intensity.

Multi-Temporal PSI Analysis and Burn Severity Combination to Determine Ground-Burned Hazard Zones

Forest fires are a seasonal phenomenon in Greece, reoccurring annually and causing adverse impacts on both human-made and natural environments. Our case study focuses on the devastating fire that took place in July 2018 in the second-housing area of Mati, East Attica. In this research, we propose a simple and effective approach that combines the deformation trend obtained from the Permanent Scatterer Interferometry (PSI) analysis with the burn severity assessment aiming to identify and classify potential ground-burn hazard zones. To maximize the number of measuring points, we employ a weighted full-graph PSI approach. Additionally, we calculate the burn severity by comparing Sentinel-2 satellite images captured before and after the event. The resulting datasets are reclassified on a scale from 1 to 5, and the proposed equation yields the final product. Numerous high and very high hazard zones have been identified using this methodology. The research findings reveal the proximity between these hazard zones and the stream network. Overall, the proposed method offers valuable insights for the post-fire monitoring and management of urban and peri-urban landscapes in the affected areas.

Assessing the impact of urban form and urbanization process on tropospheric nitrogen dioxide pollution in the Yangtze River Delta, China

Optimizing urban form through urban planning and management policies can improve air quality and transition to demand-side control. Nitrogen dioxide (NO2) in the urban atmosphere, mainly emitted by anthropogenic sources such as industry and vehicles, is a key precursor of fine particles and ozone pollution. Both NO2 and its secondary pollutants pose health risks for humans. Here we assess the interactions between urban forms and airborne NO2 pollution in different cities with various stages of urbanization in the Yangtze River Delta (YRD) in China, by using the machine learning and geographical regression model. The results reveal a strong correlation between urban fragmentation and tropospheric NO2 vertical column density (TVCD) in YRD cities in 2020, particularly those with lower or higher levels of urbanization. The correlation coefficients (R2) between NO2 TVCD and the largest patch index (a metric of urban fragmentation) in different cities are greater than 0.8. For cities at other urbanization stages, population and road density are strongly correlated with NO2 TVCD, with an R2 larger than 0.61. This study highlights the interdependence among urbanization, urban forms, and air pollution, emphasizing the importance of customized urban landscape management strategies for mitigating urban air pollution.

Development and evaluation of temperature-based deep learning models to estimate reference evapotranspiration

Efficient irrigation management of urban landscapes is critical in arid/semi-arid environments and depends on the reliable estimation of reference evapotranspiration (ETo). However, the available measured climatic data in urban areas are typically insufficient to use the standard Penman-Monteith for ETo estimation. Therefore, smart landscape irrigation controllers often use temperature-based ETo models for autonomous irrigation scheduling. This study focuses on developing deep learning temperature-based ETo models and comparing their performance with widely used empirical temperature-based models, including FAO Blaney & Criddle (BC), and Hargreaves & Samani (HS). We also developed a simple free and easy-to-access tool called DeepET for ETo estimation using the best-performing deep learning models developed in this study. Four artificial neural network (ANN) models were developed using raw weather data as inputs and the reconstructed signal obtained from the wavelet transform as inputs. In addition, long short-term memory (LSTM) recurrent neural network (NN) and one-dimensional convolution neural network (CNN) models were developed. A total of 101 active California Irrigation Management Information System (CIMIS) weather stations were selected for this study, with >725,000 data points expanding from 1985 to 2019. The performance of the models was evaluated against the standard CIMIS ETo. When evaluated at the independent sites, the temperature-based DL (Deep Learning) models showed 15–20% lower mean absolute error values than the calibrated HS model. No improvement in the performance of the ANN models was observed using reconstructed signals obtained from the wavelet transform. Our study suggests that DL models offer a promising alternative for more accurate estimations of ETo in urban areas using only temperature as input. The DeepET can be accessed from the Haghverdi Water Management Group website: http://www. ucrwater.com/software-and-tools.html.

Ecosystem Service Flow Perspective of Urban Green Land: Spatial Simulation and Driving Factors of Cooling Service Flow

The linking of ecosystem service flows (ESFs) with urban land management is still in its nascent stage. The spatial process modeling of ESFs plays a crucial role in establishing connections between urban land sustainability and human benefits. However, the spatial processes and driving mechanisms associated with urban cooling services (UCS) remain ambiguous. In this study, we selected the area within the 6th Ring Road of Beijing as the study area, where the population is highly concentrated and the urban greenery is relatively developed. We modeled the spatial processes of cooling service flow (UCSF) in this area and elucidated the contribution of landscape patterns to UCSF. Firstly, the cooling capacity, referred to as UCS, of the urban blue–green landscape, was estimated using the InVEST tool. Subsequently, the UCSF spatial process was simulated by employing a two-dimensional Gaussian function at the pixel level. In order to characterize the landscape features in the study area, eight landscape indices were selected, and Fragstats v4.2 was employed for their calculation. Finally, GeoDetector was utilized to explore the driving mechanisms of landscape patterns on UCSF. The predominant area for both UCS and UCSF lies between the 5th and 6th Ring Road in Beijing, exhibiting a declining trend from the 6th Ring Road toward the city center. The UCSF coverage area, which represents the beneficiary area, accounted for approximately 87.78% of the study area, with the largest increase occurring within the 2nd Ring Road. The Landscape Shape Index demonstrated the strongest individual contribution to UCSF, while its combined bivariate contribution was significant. Geometry exerted a greater influence on UCSF compared to landscape scale and spatial configuration. This study presents novel insights for assessing the omnidirectional flow of ESFs through the modeling of flow functions. The findings of this study can serve as a valuable reference for sustainable urban landscape management and planning.

Maintaining key ecosystem services under multiple development scenarios: A case study in Guangdong–Hong Kong–Macao greater bay Area, China

Effective land use management can better maintain ecosystem services, especially in urban agglomerations. However, rational urban scale systems and landscape patterns to maintain key ecosystem services (ESs) in highly urbanized areas remain poorly understood. Taking the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a study area, we quantified the spatio-temporal change of key ESs from 2000 to 2020 by the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model, and simulated land use change prior considering ES conservation priority areas under different multiple development scenarios in 2050 by adopting the future land use simulation (FLUS) model. The main findings were as follows: (1) From 2000 to 2020, natural habitat, water retention and carbon sequestration decreased by 5.5%, 7.9%, and 3.9%, respectively, while the soil conservation increased by 63.7%. (2) The proportion of different conservation priority areas ranged from 10.6% to 22.6%, which were mainly located in the mountainous region. (3) The urban land area would increase from 4286.00 km2 to 4802.25 km2 between 2020 and 2050 in the GBA, with a growth rate of 12.05%. Under the simulation scenarios, the new urban land was mainly distributed in megacities and supercities. (4) Under the integrative conservation scenario, the habitat quality index, water conservation, soil conservation and carbon sequestration would increase by 0.036, 7 × 104 t, 5.11 × 106 t and 0.93 × 106 t, respectively. To maintain the key ESs, we recommend optimizing the urban scale system, making it compact at the city scale and scattered at the regional scale, and strictly restricting the conversion of forestland and farmland adjacent to megacities into urban land. These findings were beneficial to achieve regional high-quality development and sustainable development via rational urban system and landscape management.

Real-time measurement of individual tree structure parameters based on augmented reality in an urban environment

The rapid and accurate acquisition of tree structural parameters is a challenging task in urban tree inventories. Here, we developed a mobile application based on augmented reality (AR) called ARTreeWatch to measure individual tree height (TH) and diameter at breast height (DBH) using an Android smartphone. For the experiments, we installed ARTreeWatch on two types of smartphones equipped with different cameras and inertial measurement units (IMUs) to capture the three-dimensional (3D) point clouds and measure the TH and DBH of 51 trees in three plots with different tree species compositions. When the two types of smartphone measurements were compared with traditional ground surveys, the root mean square error (RMSE) of the estimated DBH ranged from 1.04 cm to 1.21 cm, and the RMSE of the TH ranged from 1.29 m to 1.98 m. Meanwhile, half the labor costs and time were saved compared to traditional field surveys. ARTreeWatch is an efficient, accurate, and lower-cost solution for measuring the structural parameters of trees in urban environments, which may be useful to urban landscape managers and researchers.

An Integrated Approach to Sub-Surface Water Pathways for the Sustainable Development of the Architectural Landscape of Agro-Urban Areas

This paper presents the results of multidisciplinary research which addresses the issue of sustainability within the design of urban agricultural landscapes through the joint solution of architecture and hydro-geomorphology for the management, accessibility and use of urban agricultural landscapes. If the traditional separation between urban and productive land has now been overcome by the inclusion of agricultural areas within the cities, what is still under discussion is how to make its planning sustainable, especially in densely urbanized contexts. This research was developed with a methodology able to combine different types of data in order to satisfy needs relating to the availability of water for land supply and to make this landscape—both rural and urban—accessible to the city. Historical traces, interpretative insights, and hydro-geomorphological reading models of the territory were analysed. Their interweaving has made it possible to develop a prototype of a water and landscape infrastructure that combines a system for subsurface water, cycle–pedestrian paths and small-scale architecture features around the water tanks. The research has been tested in the city of Pozzuoli (NA) in Southern Italy, within the Monteruscello neighbourhood. The result led to a design solution of an integrated system which contributes to implementing the green transition within cities.

Impacts of urban green infrastructure on attentional functioning: insights from an fMRI study.

Multiple studies using various measures, technologies, and participant groups have found that exposure to urban green infrastructure can help alleviate the daily attentional fatigue that human experience. Although we have made significant progress in understanding the effects of exposure to urban green infrastructure on attention restoration, two important gaps in our knowledge remain. First, we do not fully understand the neural processes underlying attention restoration that exposure to urban green infrastructure elicits. Second, we are largely unaware of how typical patterns of urban green infrastructure, such as combinations of trees and bioswales, affect recovery from attentional fatigue. This knowledge is crucial to guide the design and management of urban landscapes that effectively facilitate attention restoration. To address these gaps in our knowledge, we conducted a controlled experiment in which 43 participants were randomly assigned to one of three video treatment categories: no green infrastructure (No GI), trees, or trees and bioswales. We assessed attentional functioning using functional Magnetic Resonance Imaging (fMRI) and the Sustained Attention Response Task (SART). Participants exposed to urban settings with trees exhibited improved top-down attentional functioning, as evidenced by both fMRI and SART results. Those exposed to urban settings with trees and bioswales demonstrated some attention-restorative neural activity, but without significant improvements in SART performance. Conversely, participants exposed to videos of urban environments without green infrastructure displayed increased neural vigilance, suggesting a lack of attention restoration, accompanied by reduced SART performance. These consistent findings offer empirical support for the Attention Restoration Theory, highlighting the effectiveness of tree exposure in enhancing attentional functioning. Future research should investigate the potential impact of bioswales on attention restoration.