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People's reduced connection with nature has led to many health problems. In the NBS framework, urban wildscapes (UWSs) are considered an important solution. They can contribute to improving the health of residents and ecosystems within the city. However, overly wild green spaces may also be offensive to residents. It is necessary to understand the public's acceptance of UWSs. Current studies on the acceptance of UWSs have used vague terms to generalize the "wildness degree". In this study, we attempted to quantify the degree of wildness using plant height and plant abundance in Japan and analyzed the results through mediated effect analysis. We discovered the following: 1. Japanese residents have low acceptance of UWSs in vacant lots. 2. The use of "height" and "abundance" may be a more objective way to quantify wildness. 3. The negative effects of abundance can be minimized. The negative effect of height cannot be controlled. This study addresses a gap in the study of Asian cities and proposes a novel approach to quantifying "wildness." It improves the health benefits of UWSs. Furthermore, it can offer guidance on the management and construction of urban green spaces. [ABSTRACT FROM AUTHOR]

Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an 'Urban Laboratory' as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project 'El Campo de Cebada' in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities. [ABSTRACT FROM AUTHOR]

Current information on urban land use and surface cover is derived from the land classification of cities, facilitating accurate future urban planning. Key insights are driven by multi-year remote sensing data. These data, when analyzed, produce high-resolution changes on the Earth's surface. In this context, publicly accessible Urban Atlas data are employed for the high-precision and high-resolution classification and monitoring of terrestrial surfaces. These datasets, which are useful for preserving natural resources, guiding spatial developments, and mitigating pollution, are crucial for monitoring changes and managing cities. This research aims to analyze and contrast land use and land cover (LULC) changes in Gaziantep (Turkey) between 2010 and 2018 using Urban Atlas data, and to investigate correlations between the city's statistical data and LULC changes. Gaziantep's urban dynamics were analyzed using Urban Atlas datasets from 2010 to 2015 and 2012 to 2018, the latter part of Copernicus, the European Earth Observation Programme. To understand the impact of LULC changes on urban landscapes, people, and the environment, official environmental and demographic statistics spanning four years were sourced and studied. The findings reveal a trend of agricultural and vacant lands evolving into residential and industrial zones, with such changes likely to increase in the near future, given the growth of building zones. While some land classes have shown consistent area values annually, residential and industrial zones have expanded in response to housing and employment demands. The most significant alterations have occurred in the last three years. Shifts in urban configurations align closely with migratory patterns, reflecting notable variations in factors like population, consumption, and pollution. [ABSTRACT FROM AUTHOR]

The large-scale identification of urban vacant land (UVL) and informal green spaces (IGSs) using conventional identification methods is challenged by the high cost of time and resources as well as inconsistent outcomes. Moreover, the spatial–temporal changes of UVL and IGSs have received limited academic attention. We introduce a methodological framework for the large-scale automatic identification of UVL and IGSs in Hangzhou, China, based on semantic segmentation. We construct and release a large-scale dataset for UVL identification, containing five different UVL categories, and one of them is IGS, with 3096 patches for training and 128 patches for evaluation. We then train five different semantic segmentation networks using the dataset and utilise Segformer to predict UVL and IGSs within the whole urban area of Hangzhou. The presented segmentation model has a hierarchically structured Transformer encoder and a multilayer perceptron decoder, which incorporates local and global information to obtain effective feature representations. Extensive experiments have been conducted to evaluate the segmentation performance of the applied Segformer. Experimental results show the good identification performance of Segformer for UVL and IGSs. Results also verify that the proposed identification framework can be effectively used to analyse the spatial–temporal changes of UVL and IGSs in Hangzhou. [ABSTRACT FROM AUTHOR]

Vacant land in residual urban areas is a crucial resource to tackle the current climate and housing crises. In this study, we present the development of a geodatabase to determine the occurrence of vacant land in the urban core of Oklahoma City, USA (OKC), and assess its potential for infill housing. As a starting point, we define urban vacant land through a literature review. We present a description of the case study's social and urbanistic context by highlighting its relevance to this study. We explain the methodology for the development of the geodatabase to quantify residual urban land in OKC's urban core. We examine the spatial distribution and recurring characteristics of vacant parcels using QGIS, Python scripting for Rhinoceros 3D, and aerial imagery. We find that small parcels have higher vacancy rates than average-sized parcels and there is a correlation between higher vacancy rates and proximity to downtown and brownfields. Finally, we discuss the implications of the findings by assessing the urban vacant land potential for residential development and its contribution to OKC's housing provision. Under all the proposed scenarios, the considered developable vacant land in the urban core could entirely fulfill the need for new housing units for the entire city. [ABSTRACT FROM AUTHOR]

Urban vacancies have been a concern for neighborhood distress and economic decline and have gained more recent attention as potential green infrastructure is known to benefit communities in diverse ways. To investigate this, this study looked into the relationship between land cover, natural environment, and urban vacancies in Austin, Texas. Additionally, we investigated the spatial patterns of green infrastructure and urban vacancies by different income groups to see if low income communities would potentially lack the benefits of green infrastructure. To measure green infrastructure, we used different land covers such as forests and shrublands, as well as natural environments such as tree canopies and vegetation richness, using remote sensing data. Urban vacancy information was retrieved from the USPS vacant addresses and parcel land uses. Through a series of multivariate analyses examining green infrastructure variables one by one, the study results indicate that green infrastructure interacts with residential and business vacancies differently. Additionally, low-income communities lack green infrastructure compared with the rest of the city and are exposed to more urban vacancies in their neighborhoods. Further study is required to understand the dynamics of vacancies in underserved communities and examine how existing vacant land can benefit the communities as ecological resources. [ABSTRACT FROM AUTHOR]

Many cities worldwide have large amounts of industrial vacant land (IVL) due to development and transformation, posing a growing problem. However, the large-scale identification of IVL is hindered by obstacles such as high cost, high variability, and closed-source data. Moreover, it is difficult to distinguish industrial vacant land from operational industrial land based solely upon image features. To address these issues, we propose a method for the large-scale automatic identification of IVL. The framework uses deep learning to train remote-sensing images of potential industrial vacant land to generate a semantic segmentation model and further use population density and surface temperature data to filter model predictions. The feasibility of the proposed methodology was validated through a case study in Tangshan City, Hebei Province, China. The study indicates two major conclusions: (1) The proposed IVL identification framework can efficiently generate industrial vacant land mapping. (2) HRNet exhibits the highest accuracy and strongest robustness after training compared with other semantic segmentation backbone networks, ensuring high-quality performance and stability, as evidenced by a model accuracy of 97.84%. Based on the above advantages, the identification framework provides a reference method for various countries and regions to identify industrial vacant land on a large scale, which is of great significance for advancing the research and transformation of industrial vacant land worldwide. [ABSTRACT FROM AUTHOR]

Urban vacant land availability offers revitalisation opportunities in the form of improving ecological functions. However, less is known about the available planning tools with which to mobilise this effort. Hence, this systematic review adopts ecological perspectives to explore planning tools to revitalise urban vacant land. The search strategy employs Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to track original research on vacant urban land from selected electronic databases. The search revealed thirty-six studies focusing on substance-oriented planning tools (indicator systems, Geographic Information System (GIS), models/simulations, field surveys, and experiments) and process-oriented tools (questionnaire surveys, the Delphi method, focus groups, and interviews). This review suggests that future studies adopt hybrid planning tools that combine the essence of substance- and process-oriented tools. Furthermore, as a framework, it recommends taking a stepwise approach at various planning stages to revive vacant land. Additional studies from the perspective of growing cities are necessary to provide insights into urban vacant land revitalisation planning, considering the competing objectives of economic prosperity and green space preservation. [ABSTRACT FROM AUTHOR]

This paper investigates whether perceptions of neighborhood physical disorder—measured by vacant lots, vacant buildings, and overgrown vegetation—influence perceptions of crime and perceptions of the frequency or magnitude of crime events. We use ordinal logistic regression to analyze individual-level and contextual-level variables derived from a survey of 401 randomly selected residents in seven New Orleans neighborhoods. Findings show that as perceptions of physical disorder increase, so does the likelihood of perceiving violent crime as more of a neighborhood problem than property crime. As residents perceive greater physical disorder, their perception of crime level decreases. Finally, residents who perceive greater physical disorder are more likely to perceive crime levels to be stable to increasing over the previous five years. The category of "physical disorder" is inherently subjective, and future research should distinguish between social disorder and physical disorder in the evaluation of perceptions of crime. Our major contribution is to empirically demonstrate that the influence of physical disorder on crime perceptions depends upon the crime type and temporal scale under investigation. [ABSTRACT FROM AUTHOR]

Over the last two decades, globally coastal areas have urbanized rapidly due to various socioeconomic and demographic driving forces. However, urban expansion in towns and cities of the developing world has been characterized by entangled structures and trends exacerbating numerous negative consequences such as pollution, ecological degradation, loss of agricultural land and green areas, and deprived settlements. Substantially, spatial simulation of urban growth and their consequences on coastal areas particularly in Egypt is still very rare. Geospatial modelling coastal urban growth is crucial and has enormous potential for coastal land use transformation and urban sustainability. The key aim of this study was to analyze spatiotemporal changes (2010–2020) and simulate future dynamics (2030 to 2050) of land use/land cover (LULC) in Alexandria Governorate, Egypt. Artificial Neural Network–Multiple Layer Perceptron (ANN-MLP) and Markov Chain techniques were employed within the GIS platform to assess processes of land transitions and predict urban growth trends, patterns and dimensions. The forecasting process was based on three maps of LULC derived from classified Landsat images of 2000, 2010 and 2020. In addition, topographical, demographic, accessibility, proximity factors were generated and developed in the form of raster spatial parameters of urbanization driving forces. The findings revealed that the observed expansion of the built-up area during one decade (2010–2020) was 12,477.51 ha, with a decline in agricultural area (7440.39 ha) and bare land (4904.91 ha). The projected change was forecasted to be 71,544 ha by 2030 and 81,983 ha in 2040 with a total of 35,998 ha increase in the built-up area and residential expansion by 2050. Despite this expected pattern of rapid changes, urban growth will be shaped by the key drivers of proximity to coastline and agricultural land transformation. The analysis indicates that the vertical urban growth will be most likely dominant along the coastal zone due to the lack of vacant lands, whereas the horizontal urban expansion will primarily take place towards the east-northeastern and south-southeastern directions of the city. The present work provides a holistic framework for establishing initial coastal land use plans not only for planners and urban administrators in Alexandria but also for policymakers and coastal municipalities in developing nations. [ABSTRACT FROM AUTHOR]

Urban agriculture is an important neighborhood revitalization strategy in the U.S. Rust Belt, where deindustrialization has left blighted and vacant land in the urban core. Immigrants and refugees represent a growing and important stakeholder group in urban agriculture, including in community gardens across the Rust Belt Midwest. Community gardens provide a host of social and economic benefits to urban landscapes, including increased access to culturally appropriate food and medicinal plants for refugee and immigrant growers. Our work in Lansing, Michigan was part of a collaboration with the Greater Lansing Food Bank's Garden Project (GLFGP) to describe the refugee and immigrant community gardening experience in three urban gardens with high refugee and immigrant enrollment. Our research describes the ways garden management facilitates inclusion for refugee and immigrant gardeners and how particular factors of inclusion in turn contribute to social capital, an important outcome that plays a critical role in refugee and immigrant subjective wellbeing. [ABSTRACT FROM AUTHOR]

Increasing the availability of greenspaces in built-up areas (GSB) is one of the main challenges to improving sustainability and livability in urban landscapes. Concurrently, the availability of brownfields and permeable spaces offers the chance to increase sustainability through the implementation of Nature-Based Solutions. This work aims to evaluate how land use/cover changes influenced the availability of permeable spaces in Italian built-up areas over the last three decades. These spaces were classified according to population density, vegetation type, and average size, to better characterize recent dynamics (2008–2016) and offer remarks and tips concerning ongoing soil sealing dynamics. According to the findings, despite an overall increase of 41.5% in built-up areas with respect to their 1990 extension, permeable spaces increased only by 25.2% during the same time-span, moving from 49.8% coverage in 1990 to 44.7% today, in relation to the whole national built-up area. Moreover, our in-depth analysis for the 2008–2016 period shows that forested spaces increased by 0.4%, while permeable unforested ones decreased by 0.7%, especially in thinly and intermediately populated areas. Overall, the scarcity of these spaces should be carefully considered when assigning residual vacant lots to new buildings and grey infrastructure, especially in densely populated areas. The proposed methodology provides reliable estimates and represents a starting point to develop advanced monitoring tools supporting sustainable urban policies. [ABSTRACT FROM AUTHOR]

Climate change and rapid urbanization are two global processes that have significantly aggravated natural disasters, such as drought and flooding. Urbanization without resilient and sustainable planning and execution could lead to undesirable changes in landscapes and stormwater regulation capacity. These changes have exacerbated the effects of extreme climatic events with disastrous consequences in many cities worldwide. Unfortunately, the major storm in Zhengzhou, China on 20 July 2021 was one of these examples. This event provided a rare opportunity to study the key roles of green infrastructures (GI) in mitigating flooding risks in a major urban center after a devasting flood event. Using the data from high-resolution images collected via two satellites, a comprehensive study of the Jialu System in Greater Zhengzhou was conducted to systematically compare how far the river water had reached before and after the 20 July 2021 major storm in order to identify the main weak links in the city's GI and stormwater management system. A flood inundation intensity index (FI) in the Upper (UJLR), Middle (MJLR), and Lower (LJLR) Regions of the Jialu River System was generated. Bivariate Moran's I, a correlation coefficient between FI and landscape characteristics, was calculated and used to identify problem areas for future improvements. Our results showed that the MJLR had the severest flooding impacts. LJLR had the biggest change in how far the river water reached after flooding, ranging from 4.59 m to 706.28 m. In UJLR, the percentages of mine, crop land, and green space had the highest global bivariate Moran's I correlation coefficients. In MJLR, the percentages of vacant land, impervious surfaces, and water body had the highest global bivariate Moran's I correlation coefficients. In LJLR, the percentages of vacant land, water body, and crop land had the highest global bivariate Moran's I correlation coefficients. The total percentages of both high landscape characteristics indices-high flood inundation intensity indices and low landscape characteristics indices-high flood inundation intensity indices areas are 12.96%, 13.47%, and 13.80% in UJLR, MJLR, and LJLR, respectively. These land cover composition types identified for each region can be treated as areas of primary focus. However, GeoDector Model (GDM) analyses showed that our eight variables of landscape characteristics were not independent. Hence, a more comprehensive approach integrating all eight variables is still necessary in future flood mitigation efforts. [ABSTRACT FROM AUTHOR]

As cities are facing environmental and societal challenges, including climate change, rapid urbanization, and the COVID-19 pandemic, scholars and policymakers have recognized the potential of small-scale urban green infrastructures (UGI), such as rain gardens and street trees, to support important ecosystem services (ES) during periods of crisis and change. While there has been considerable research on the design, planning, engineering, and ecology of small-scale UGI, the governance modes of such spaces to support ES and manage ecosystem disservices (EDS) have received significantly less research attention. In this article, we provide a systematic review to evaluate how different modes of governance support different ES in small-scale green infrastructure. We evaluated governance in six types of small-scale green infrastructure: small parks, community gardens, vacant lands, rain gardens, green roofs, and street trees. Our review examines the different characteristics of four new governance approaches, including adaptive, network, mosaic, and transformative to understand their bottom-up nature and applicability in governing ES/disservices of small-scale UGI. Each governance mode can be effective for managing the ES of certain small-scale UGI, given their associations with principles such as resilience thinking, connectivity, and active citizenship. Our synthesis highlights knowledge gaps at the intersection between governance arrangements and ES in small-scale UGI. We conclude with a call for further research on the environmental and contextual factors that moderate the linkages between governance modes and ES/EDS in different types of UGI. [ABSTRACT FROM AUTHOR]

Urban Agriculture (UA) is the widespread practice of food production within available city space using non-commercial, commercial and hybrid production technologies. The economic viability of UA remains a concern among UA practitioners. To investigate UA's viability; land, labour and distribution cost are analyzed, and margin and benefit–cost ratio (BCR) under vacant lot, rooftop/backyard and discretionary labour UA are calculated. We present a straightforward approach to gauge the economic viability of UA taking examples from 40 distinct locations of two divergent development contexts of Adelaide, South Australia and Kathmandu Valley, Nepal. UA seems potentially viable by selecting high-value crops in Adelaide but showed little chance of viability under low-value crop scenarios in both contexts. The high cost of land is shown to be the primary driver of cost for UA. Labour cost appears to be a critical difference between the two cities, being an important constraint for the economic viability in Adelaide, where the wage rate is high. To improve economic viability, the respective governments and planners should consider better ways to avail subsidised land through policy intervention and volunteer or subsidised labour arrangement mechanisms. Home food gardens accessing available land and labour as a discretionary/spare time activity with zero distribution cost may represent the best way to produce food without exceeding market costs in cities. [ABSTRACT FROM AUTHOR]

In recent years, socioeconomic transformation and social modernisation in the Gulf Cooperation Council (GCC) states have led to tremendous changes in lifestyle and, subsequently, expansion of urban settlements. This accelerated growth is pronounced not only across vegetated coasts, plains, and mountains, but also in desert cities. Nevertheless, spatial simulation and prediction of desert urban patterns has received little attention, including in Oman. While most urban settlements in Oman are located in desert environments, research exploring and monitoring this type of urban growth is rare in the scientific literature. This research focuses on analysing and predicting land use–land cover (LULC) changes across the desert city of Ibri in Oman. A methodology was employed involving integrating the multilayer perceptron (MLP) and Markov chain (MC) techniques to forecast spatiotemporal LULC dynamics and map urban growth patterns. The inputs were three Landsat images from 2010 and 2020, and a series of covariate layers based on transforms of elevation, slope, population settlements, urban centres, and points of interest that proxy the driving forces of change. The findings indicated that the observed LULC changes were predominantly rapid across the city during 2010 to 2020, transforming desert, bare land, and vegetation into built-up areas. The forecast showed that area of land conversion from desert to urban would be 5666 ha during the next two decades and 7751 ha by 2050. Similarly, vacant land is expected to contribute large areas to urban expansion (2370 ha by 2040, and 3266 ha by 2050), although desert cities confront numerous environmental challenges, including water scarcity, shrinking vegetation cover, and being converted into residential land. Massive urban expansion has consequences for biodiversity and natural ecosystems—particularly in green areas, which are expected to decline by approximately 107 ha by 2040 (i.e., 10%) and 166 ha by 2050. The outcomes of this research provide fundamental guidance for decision-makers and planners in Oman and elsewhere to effectively monitor and manage desert urban dynamics and sustainable desert cities. [ABSTRACT FROM AUTHOR]

Children are often the most disadvantaged cohort during miserable situations of natural disaster, economic crisis, and environmental degradation. Meanwhile, children's play is increasingly controlled, costly, and standardized with engineered structures and surfaces rather than infused with natural processes and organic materials. Access to nature-based playscapes in underserved neighborhoods is extremely limited, impacted by disparities of race, class, and gender. In these contexts, neglected vacant lots and streets and related interstitial spaces can be redesigned as playscapes that support active, engaged, meaningful, and socially interactive play. Our study addresses the ample opportunity to re-engage kids and city nature in underserved neighborhoods in Philadelphia and Pennsylvania. Methodologically, we balance systemic GIS spatial data approaches with informal and experiential—or tacit—site-based analyses. This mixed-methods approach helps identify local patterns of insecurity, children's circulation, and natural resource possibilities. Finally, a play network with eight playscape themes is revealed as an emergent pattern that we termed green play infrastructure. These themes provide examples of activities and opportunities for future programs that fit their surrounding context. The mixed-methods approach fills a gap in children's play literature and illustrates how green play infrastructure can serve as a key strategy in improving children's lives in disadvantaged neighborhoods. [ABSTRACT FROM AUTHOR]

Rapid urbanization influences green infrastructure (GI) development in cities. The government plans to optimize GI in urban areas, which requires understanding GI spatiotemporal trends in urban areas and driving forces influencing their pattern. Traditional GIS-based methods, used to determine the greening potential of vacant land in urban areas, are incapable of predicting future scenarios based on the past trend. Therefore, we propose a heterogeneous ensemble technique to determine the spatial pattern of GI development in Jinan, China, based on driving biophysical and socioeconomic factors. Data-driven artificial neural networks (ANN) and random forests (RF) are selected as base learners, while support vector machine (SVM) is used as a meta classifier. Results showed that the stacking model ANN-RF-SVM achieved the best test accuracy (AUC 0.941) compared to the individual ANN, RF, and SVM algorithms. Land surface temperature, distance to water bodies, population density, and rainfall are found to be the most influencing factors regarding vacant land conversion to GI in Jinan. [ABSTRACT FROM AUTHOR]

The world's electricity generation has increased with renewable energy technologies such as solar (solar power plant), wind energy (wind turbines), heat energy, and even ocean waves. Iran is in the best condition to receive solar radiation due to its proximity to the equator (25.2969° N). In 2020, Iran was able to supply only 900 MW (about 480 solar power plants and 420 MW home solar power plants) of its electricity demand from solar energy, which is very low compared to the global average. Yazd, Fars, and Kerman provinces are in the top ranks of Iran, with the production of approximately 68, 58, and 47 MW using solar energy, respectively. Iran also has a large area of vacant land for the construction of solar power plants. In this article, the amount of electricity generation using solar energy in Iran is studied. In addition, the construction of a 10 MW power plant in the city of Sirjan is economically and technically analyzed. The results show that with US$16.14 million, a solar power plant can be built in the Sirjan region, and the initial capital will be returned in about four years. The results obtained using Homer software show that the highest maximum power generation is in July. [ABSTRACT FROM AUTHOR]

Copper slag is generated when copper and nickel ores are recovered from their parent ores using a pyrometallurgical process, and these ores usually contain other elements which include iron, cobalt, silica, and alumina. Slag is a major problem in the metallurgical industries as it is dumped into heaps which have accumulated into millions of tons over the years. Moreover, they pose a danger to the environment as they occupy vacant land (space problems). Over the past few years, studies have been conducted to investigate the copper slag-producing outlets to learn their behavior, as well as properties of slag, to have the knowledge of how to better reuse and recycle copper slag. This review article provides the environmental and socioeconomic impacts of slag, as well as a characterization of copper slag, with the aim of reusing and recycling the slag to benefit the environment and economy. Recycling methods are considered an attractive technological pathway for reducing waste and greenhouse gas emissions, as well as promoting the concept of circular economy through the utilization of waste. These metal elements have value depending on their characteristics; hence, copper slag is considered as a secondary source of valuable metals. Some of the pyrometallurgical and hydrometallurgical processes to consider are physical separation, magnetic separation, flotation, leaching, and direct reduction roasting of iron (DRI). Some of the possible metals that can be recovered from the copper slag include Cu, Fe, Ni, Co, and Ag (precious metals). [ABSTRACT FROM AUTHOR]