Land, Volume 12, Issue 12 (December 2023) – 103 articles

Corn grain moisture (CGM) is critical to estimate grain maturity status and schedule harvest. Traditional methods for determining CGM range from manual scouting, destructive laboratory analyses, and weather-based dry down estimates. Such methods are either time consuming, expensive, spatially inaccurate, or subjective, therefore they are prone to errors or limitations. Realizing that precision harvest management could be critical for extracting the maximum crop value, this study evaluates the estimation of CGM at a pre-harvest stage using high-resolution (1.3 cm/pixel) multispectral imagery and machine learning techniques. Aerial imagery data were collected in the 2022 cropping season over 116 experimental corn planted plots. A total of 24 vegetation indices (VIs) were derived from imagery data along with reflectance (REF) information in the blue, green, red, red-edge, and near-infrared imaging spectrum that was initially evaluated for inter-correlations as well as subject to principal component analysis (PCA). VIs including the Green Normalized Difference Index (GNDVI), Green Chlorophyll Index (GCI), Infrared Percentage Vegetation Index (IPVI), Simple Ratio Index (SR), Normalized Difference Red-Edge Index (NDRE), and Visible Atmospherically Resistant Index (VARI) had the highest correlations with CGM (r: 0.68–0.80). Next, two state-of-the-art statistical and four machine learning (ML) models (Stepwise Linear Regression (SLR), Partial Least Squares Regression (PLSR), Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and K-nearest neighbor (KNN)), and their 120 derivates (six ML models × two input groups (REFs and REFs+VIs) × 10 train–test data split ratios (starting 50:50)) were formulated and evaluated for CGM estimation. The CGM estimation accuracy was impacted by the ML model and train-test data split ratio. However, the impact was not significant for the input groups. For validation over the train and entire dataset, RF performed the best at a 95:5 split ratio, and REFs+VIs as the input variables (r_train: 0.97, rRMSE_train: 1.17%, r_entire: 0.95, rRMSE_entire: 1.37%). However, when validated for the test dataset, an increase in the train–test split ratio decreased the performances of the other ML models where SVM performed the best at a 50:50 split ratio (r = 0.70, rRMSE = 2.58%) and with REFs+VIs as the input variables. The 95:5 train–test ratio showed the best performance across all the models, which may be a suitable ratio for relatively smaller or medium-sized datasets. RF was identified to be the most stable and consistent ML model (r: 0.95, rRMSE: 1.37%). Findings in the study indicate that the integration of aerial remote sensing and ML-based data-run techniques could be useful for reliably predicting CGM at the pre-harvest stage, and developing precision corn harvest scheduling and management strategies for the growers. Full article

With the recent increase in food demand, urban agriculture has gained attention as a way of increasing food self-sufficiency and providing recreational spaces in cities. In this study, the suitability of rooftop greenhouses (RGs), a type of urban agriculture, was analyzed by combining the analytical hierarchy process (AHP) and geographic information systems (GIS) in Seoul, the capital city of Korea. To achieve this, we derived location suitability factors through expert consultations and calculated the weights of each factor through AHP. After building the spatial data according to these factors, they were weighted and summed then scaled to a score of 0–100. The highest weight of the RG location factors was for benefit (0.1782), followed by officially assessed land prices (0.0913) and supermarket density (0.0802). The weights of supermarket density and accessibility were high because they are considered the main distribution channels. When analyzing the location of RGs by linking these results with the spatial data according to factor, we revealed that Gangseo-gu (a district of Seoul) had relatively high location suitability scores. This trend was determined to be caused by the rather low officially assessed land price, high supermarket density, and productive population. This result could prove useful when selecting the approximate locations of RGs in Seoul and for promoting food self-sufficiency in cities. Full article

The Chure Hills, already vulnerable due to their fragile nature, face increased landslide risk, prompting the need for reliable susceptibility assessment. This study uses Poisson regression modeling to assess landslide susceptibility in two highly susceptible districts of the Chure region. Variance inflation factor (VIF) tests were conducted to ensure robustness, indicating no multicollinearity among the variables. Subsequently, Poisson regression analysis identified eight significant variables, among which geology, lineament density, elevation, relief, slope, rainfall, solar radiance, and land cover types emerged as important factors associated with landslide count. The analysis revealed that higher lineament density and slope were associated with lower landslide counts, indicating potential stabilizing geological and topographical influences. The categorical variable, namely geology, revealed that middle Siwalik, upper Siwalik, and quaternary geological formations were associated with lower landslide counts than lower Siwalik. Land cover types, including areas under forest, shrubland, grassland, agricultural land, water bodies, and bare ground, had a substantial significant positive association with landslide count. The generated susceptibility map that exhibited a substantial portion (23.32% in Dang and 5.22% in Surkhet) of the study area fell within the very-high-susceptibility categories, indicating pronounced landslide susceptibility in the Dang and Surkhet districts of the Chure hills. This study offers valuable insights into landslide vulnerability in the Chure region, serving as a foundation for informed decision-making, disaster risk reduction strategies, and sustainable land-use and developmental policy planning. Full article

The metropolitan area serves as a vital catalyst for advancing the new urbanization strategy and remains a focal point of current academic research in China. This paper endeavors to explore the developmental mechanisms of China’s metropolitan areas, centering on the circulation of regional production factors within these urban conglomerations. Additionally, it introduces the hypothesis of various spatial governance models for these metropolitan areas. Drawing upon theoretical research, the paper substantiates the hypothesis regarding the development mechanisms and spatial governance model of metropolitan areas through several case studies. Finally, we present the principal research findings concerning the development mechanisms and spatial governance models of China’s metropolitan areas, along with issues in need of further examination. Full article

The spatial pattern of regional green space is an important dimension to describe and quantitatively express the characteristics of regional green spaces outside the built-up area of a city. With the expansion of urban and rural construction land, regional green space has been continuously encroached upon. This leads to a decline in regional ecological well-being and the loss of biodiversity. Based on the remote sensing data of Shanghai city from 2000 to 2020, we quantitatively studied the spatial morphological change characteristics of regional green space outside the built-up area of Shanghai city. Firstly, with the help of the GEE platform, the optimal decoding accuracy classification method was selected through machine learning (random forest, support vector machine, classification regression tree); then, based on the biophysical component (BCI) and CA binarization, the built-up area ranges for up to five time nodes were obtained; finally, through GIS spatial data analysis and processing technology, the regional green space dynamic data of Shanghai for five time nodes were extracted. Based on the above data, an analysis index system was constructed to quantitatively analyze the spatial morphology characteristics of the regional green space outside the built-up area of Shanghai. The results show that (1) the area of regional green space outside the built-up area of Shanghai had a fluctuating growth pattern of “decreasing and then increasing”. The arable land and water areas in Shanghai decreased, and the woodland area increased steadily, while the wetland and grassland areas showed a trend of first decreasing and then increasing. (2) The regional green patch fragmentation shows a fluctuating development trend of increasing, decreasing, and increasing. (3) The change in the spatial center of gravity of the regional green space in Shanghai had a high degree of consistency with the overall green space change. The center of gravity of the grasslands in the regional green space moved substantially to the northwest, while the center of gravity of the other types remained basically unchanged. This study reveals the spatial morphology characteristics of regional green spaces and provides a research method to study the dynamic changes in regional ecological resources. The results of this study can provide a scientific basis for the identification, protection, and development of regional ecological resources. Full article

Wildfires are a pervasive natural phenomenon in Mediterranean forest ecosystems, causing significant ecological imbalances that demand immediate restoration efforts. The intricacy of reinstating the ecological balance necessitates a proactive approach to identifying and assessing suitable restoration sites. The assessment and investigation of the most suitable restoration sites is of particular importance both for the relevant authorities and for planning and decision making by the state. This study proposes the development of a user-friendly model for evaluating and identifying the most suitable restoration sites immediately after a fire, using geoinformation technologies. For the purposes of demonstrating the method’s applicability, the 2016 fire of “Prinos”, Thasos, Greece, an area that has been repeatedly affected by forest fires, was chosen as a case study. The methodology evaluation was carried out by applying the weighted multicriteria decision analysis method (MCDAM) and was based on a number of variables. The analysis, processing and extraction of the results were performed using primarily remote sensing datasets in a geographical information system (GIS) environment. The methodology proposed herein includes the classification of the individual criteria and their synthesis based on different weighting factors. In the final results, the restoration suitability maps are presented in five suitability zones based on two different scenarios. Based on this study, the integration of geospatial and remote sensing data offers a valuable and cost-effective means for promptly assessing post-fire landscapes, with the aim of identifying suitable restoration sites. Full article

This research focuses on the governance of rural living environments in China from the perspective of “System-Life”. The objective of improving rural living environments is to construct a beautiful countryside, which is an important part of China’s rural revitalization strategy. Through a literature review, a field study, and quantitative analysis, this paper explores the tensions and interactions between local governments and social demand by investigating four elements of the village improvement program: the village’s appearance, sewage treatment, domestic garbage disposal, and the sanitation of toilets. We also examine the interactions between the main participants involved in the governance of rural living environments, including the primary-level governments, village committees, and the villagers themselves. It was found that there is a path toward constructing a benign interaction between “system” and “life”. In terms of “system”, the primary-level governments play a decisive role in the implementation of policies, offering a creative interpretation and flexible implementation of a policy. From the perspective of “life”, the village committee is the bridge between the primary-level governments and villagers. The villagers have their own understanding of policy and the logic of life. This probe leads us to suggest that primary-level governments need to respect the perceptions and priorities of villagers in order to improve the performance of this well-intentioned program. Full article

Contemporary urban planning models include urban trail paths. These are paths that create active transportation corridors within a city’s built environment, providing more sustainable travel, especially for short trips. The benefits of their use are plentiful, including improvements in commuters’ health, reductions in energy footprint, and socio-economic benefits for the entire society. In modern urban planning approaches such as the “15-minute city”, urban trail paths serve as connectors, facilitating access to amenities beyond the close-proximity concept of a “neighborhood”. They act as a way of connecting residents to other 15-minute cities/neighborhoods via safe routes, reducing extensive car use. Micromobility constitutes a novel approach to short trips with proven results. This paper explores the possibility of introducing micromobility as a means of connecting 15-minute cities/neighborhoods through urban trail paths. Through a literature review, an analysis is conducted of the opportunities arising from the introduction of micromobility, as well as on the factors influencing its sustained use in urban mobility and the public realm. Full article

Risks associated with severe wildfire are growing in forest landscapes due to interactions among climate change, fuel accumulation from fire suppression, an expanding wildland–urban interface, and additional factors. People, infrastructure, ecosystem services, and forest health all face varying degrees of risk. The spatial distributions of the many social and ecological factors that influence wildfire, its impacts, and management responses are an important landscape-level context for managing risks and fostering resilient lands and communities. Decision-support tools that integrate these varied distributions can provide a holistic and readily interpreted characterization of landscapes, helping fire management decision making be appropriate, efficient, and effective. Firescapes—landscape types defined in relation to fire, its drivers, and its effects as a socioecological system—fill this role, providing a way to organize and interpret spatial variation along multiple relevant dimensions. We describe a quantitative approach for classifying and mapping firescapes for decision support, using the southeastern United States as a case study. We worked with regional partners to compile relevant large-scale datasets and identify 73 variables for analysis. We used factor analysis to reduce the data to eight factors with intuitive interpretations relevant to fire dynamics, fire history, forest characteristics, climate, conservation and ecosystem service values, social and ecological landscape properties, and social vulnerabilities. We then used cluster analysis on the factors to generate quantitative landscape classes, which we interpreted as nine distinctive firescape classes. The firescapes provide a broad-scale socioecological information context for wildfire risk management and planning. The analytical approach can accommodate different data types at a variety of scales, incorporate new monitoring data as they are available, and can be used under data-driven scenarios to assess possible consequences of future change. The resulting firescape maps can provide decision support to forest managers, planners, and other stakeholders, informing appropriate strategies to manage fire and associated risks, build community and forest resilience to fire, and improve conservation outcomes. Full article

Ecological compensation for cultivated land is a prominent means to coordinate the protection and utilization of cultivated land ecosystems. This study assessed the ecological compensation for cultivated land, considering both the ecological footprint and value of ecosystem services. We used the ecological footprint model to calculate the ecological footprint and ecological carrying capacity of cultivated land, combined with the value of its ecosystem services, with a focus on estimating its ecological compensation standard, and we analyzed the temporal and spatial distribution characteristics of Northeast China. We found that the ecological footprint and ecological carrying capacity of cultivated land showed a fluctuating growth trend in Northeast China from 2000 to 2020, increasing by 288.83 × 10⁵ ha and 131.37 × 10⁵ ha, respectively. The spatial distribution of cultivated land’s ecological footprint and ecological carrying capacity showed growth from the southwest to the northeast. The value of its ecosystem services presented an overall trend of growth over the past 20 years, increasing by CNY 13.64 billion, or an increase of 12.47%. In terms of spatial distribution, the trends of the ecological compensation for cultivated land showed obvious differences. This study mainly focused on black soil cultivated land, and its results are helpful for governments in different countries solving similar problems in terms of the ecological compensation for cultivated land. This study will provide a valuable reference to measure the compensation standard scientifically and to provide policy recommendations for sustainable cultivated land’s protection and utilization. Full article

Arid regions are considered to be among the most ecologically fragile and highly sensitive to environmental change globally, and land use and land cover conditions in the region directly influence large-scale ecosystem processes. Currently, thanks to diverse remote sensing platforms, geographers have developed an array of land cover products. However, there are differences between these products due to variations in spatio-temporal resolutions. In this context, assessing the accuracy and consistency of different land cover products is crucial for rationalizing the selection of land cover products to study global or regional environmental changes. In this study, Xinjiang Uygur Autonomous Region (XUAR) is taken as the study area, and the consistency and performance (type area deviation, spatial consistency, accuracy assessment, and other indexes) of the five land cover products (GlobeLand30, FROM_GLC30, CLCD, GLC_FCS30, and ESRI) were compared and analyzed. The results of the study show that (1) the GlobeLand30 product has the highest overall accuracy in the study area, with an overall accuracy of 84.06%, followed by ESA with 75.57%, while CLCD has the lowest overall accuracy of 70.05%. (2) The consistency between GlobeLand30 and CLCD (area correlation coefficient of 0.99) was higher than that among the other products. (3) Among the five products, the highest consistency was found for water bodies and permanent snow and ice, followed by bare land. In contrast, the consistency of these five products for grassland and forest was relatively low. (4) The full-consistency area accounts for 49.01% of the total study area. They were mainly distributed in areas with relatively homogeneous land cover types, such as the north and south of the Tianshan Mountains, which are dominated by bare land and cropland. In contrast, areas of inconsistency make up only 0.03% and are mostly found in heterogeneous areas, like the transitional zones with mixed land cover types in the Altai Mountains and Tianshan Mountains, or in areas with complex terrain. In terms of meeting practical user needs, GlobeLand30 offers the best comprehensive performance. GLC_FCS30 is more suitable for studies related to forests, while FROM_GLC30 and ESRI demonstrate greater advantages in identifying permanent ice and snow, whereas the performance of CLCD is generally average. Full article

UNESCO-designated geoparks, intended for conservation, seek to drive economic development via geological heritage education and tourism. Since 2018, within the framework of the European project Atlantic Geoparks (Interreg Atlantic area program), the Valleys of Cantabria project has been promoted to declare a UNESCO Global Geopark (UGGp) in the Cantabria region (northern Spain). The Valles de Cantabria proposal, aligning with UNESCO objectives, evaluates the region’s geopark potential, emphasizing sustainable development and societal education. Covering 600 km² in eastern Cantabria, the territory involves 19 municipalities and has a population of 60,600. The geological context, ranging from the Triassic to the Quaternary periods, reflects the complex evolution of this territory, which has been influenced by tectonic forces, geomorphological processes, and sea-level changes. Detailed reviews and fieldwork performed by experts, including university researchers, have identified 66 sites of geological interest (SGI). The geosites, which have different geological–geomorphological significances, have been assessed according to their scientific value (including educational importance), potential of use (mainly geotouristic use), and vulnerability or risk of degradation. The geological heritage is directly related to the high biodiversity of the area. The challenges of this territory, such as depopulation and the low income of the inhabitants, can be improved with the declaration of a geopark, which would help to create new job opportunities related to geotourism and sustainable development. UNESCO recognition could catalyse scientific research, address socioeconomic challenges, and foster rural revitalization, strengthening the symbiotic relationship between geoconservation and local economic growth. Collaboration with other Atlantic geoparks has enabled the exchange of experiences that will hopefully deepen in the future. Consequently, the aim of this work is to explore the potential of this territory in terms of high-quality geological features and biological and cultural heritage, as well as to evaluate the socioeconomic context that makes the territory potentially suitable for promoting a UGGp. Full article

Megacity regions where human activities are intensive are key areas for CVD prevention and control in China. Optimizing land-use patterns has been widely recognized as an important public health intervention. Ecological space, agricultural space, and construction space are three basic management objects in China’s new land-use management system. Given that most existing studies focused on a single type of land use, this study treats them as a whole and not only explores the impact of each type, but also systematically investigates the effects of the interactions between any two types of land use and the whole land-use pattern. Specifically, this study first constructs a hierarchical index system, then uses spatial error models (SEM) to explore the global associations between each index and age-standardized CVD mortality rates (ASMRs) and uses the multiple geographical weighted regression model (MGWR) to explore the spatial heterogeneity of factor effects. The possible association between land-use patterns and CVD mortality is then explored, and recommendations for policy formulation are provided. The analysis results show that the overall pattern of moderately decentralized and organically combined land use can control CVD mortality to a certain extent, but the specific influence mechanisms show significant differences according to different land-use types, relationships, and location conditions. First, in terms of single-type land-use distribution, the concentration of ecological space has positive health benefits, while a too high concentration of agricultural space has negative effects. Second, the combination of different types of land use has a significant association with CVD, in which the mixed layout of ecological and agricultural space helps to suppress CVD, while ecological and construction space need to be appropriately regularized and should not be too interspersed. Third, the same index may have different effects in different regions, suggesting that policy makers need to tailor their policies to local conditions. Full article

The foundation of the city of Valencia was created by the Romans on an island formed by the River Turia, strategically located between Carthago Nova (Cartagena) and Tarraco (Tarragona), and is directly connected to the sea. This raises the question of how the elements of access to the city came about and how the river and its bridges might have affected its evolution. This article delves into the study of the origins of the city, with a time frame that extends into the 11th century, the time at which an event took place that confirms one of the major changes in the city’s urban morphology: when it stopped being an island. The intrinsic relationship that exists between bridges and main communication routes as fundamental elements to the access of an island is the driving force behind this article, which is based on research, until now undone, on the existence and construction of the first bridges in the city of Valencia and their influence on the city’s subsequent development. This paper will start by studying the founding and location of this city and will then analyze the communication routes existing at the time. It will also study the communication routes that were created later and how all of them were forced to cross a fluvial accident, the River Turia. For this purpose, the number of bridges built until the city ceased to be an island have been identified, and analyses of their typology, location and who was responsible for them has been carried out to study how they may have affected the normal flow and evolution of the riverbed and their possible influence on the city’s development. Full article

As the global temperature and rapid urbanization continue to rise, urban heat islands (UHIs) also continue to increase across the world. Following the heat equity concept, UHIs disproportionately impact disadvantaged or overburdened communities. Green infrastructure (GI) has been at the forefront of UHI mitigation efforts, including nature-based solutions like parks, pervious open spaces, wooded areas, green roofs, rain gardens, and shade trees. In this paper, we use a heat equity lens to analyze community perceptions of the intersection of climate change, UHI, and GI in Camden, New Jersey—a post-industrial city with a history of environmental injustices. Based on a mixed-methods analysis of survey responses (n = 107), 11 years of relevant X (formerly Twitter) posts (n = 367), and geospatial data, we present community perceptions of and connections between climate change, UHI, and GI and discuss major themes that emerged from the data: perceived heat inequity in Camden triggers negative emotions; a public knowledge gap exists regarding climate change-UHI-GI connections; and perceived inequitable distribution of GI and certain GI planning and maintenance practices may negatively impact UHI mitigation strategies. We argue these themes are useful to urban planners and relevant professionals while planning for heat equity and mitigating UHI effects in disadvantaged urban communities like Camden. Full article

Changes in land use and land cover (LULC) are caused by several factors, including climate change, socio-demographic dynamics, human pressures and urban sprawl. These factors alter the structure and functionality of ecosystems and their capacity to provide ecosystem goods and services to society. The study of LULC changes is important for understanding the dynamics of relationships between environmental, social and economic components and for analyzing the factors affecting natural capital. Including ecosystem services (ES) in spatial planning tools and sectoral policies is useful for improving governance. In this paper, the impact of LULC changes on ES provision has been estimated. To this end, we carried out a literature review (Step 1) to select the biophysical and economic coefficients of ES supply by land cover classes and collect them in a database (Step 2). We subsequently aggregated the economic and biophysical coefficients by macro classes (Step 3) and, using the benefit transfer approach, we estimated the change in the supply of ESs concerning permanence and transition phenomena in Italy from 1990 to 2018 (Step 4). The transition phenomena analysis also allowed us to evaluate the consequences of urbanization and urban green space governance on ES supply. Indeed, these urban green spaces can help reduce risks to people’s health and safety and mitigate the effects induced by climate change. In total, approximately 800 coefficients (biophysical and economic) of ESs supplied by Corine Land Cover classes were acquired. The results show a reduction in the annual supply of ecosystem services of EUR 927 million (2022) caused by LULC changes between 1990 and 2018. This research proposes a methodology to improve knowledge of ESs concerning anthropogenic impacts and to support land-use planning policies regarding Agenda 2030 for Sustainable Development Goals. Full article

Wildfire occurrences have increased and are projected to continue increasing globally. Strategic, evidence-based planning with diverse stakeholders, making use of diverse ecological and social data, is crucial for confronting and mitigating the associated risks. Prescribed fire, when planned and executed carefully, is a key management tool in this effort. Assessing where prescribed fire can be a particularly effective forest management tool can help prioritize efforts, reduce wildfire risk, and support fire-resilient lands and communities. We collaborated with expert stakeholders to develop a Bayesian network model that integrated a large variety of biophysical, socioecological, and socioeconomic spatial information for the Southeastern United States to quantify where risk is high and where prescribed fire would be efficient in mitigating risk. The model first estimated wildfire risk based on landscape-scale interactions among the likelihoods of fire occurrence and severity and the people and resources potentially exposed—accounting for socioeconomic vulnerabilities as well as key ecosystem services. The model then quantified the potential for risk reduction through prescribed fire, given the existing fuel load, climate, and other landscape conditions. The resulting expected risk estimates show high risk concentrated in the coastal plain and interior highland subregions of the Southern US, but there was considerable variation among risks to different ecosystem services and populations, including potential exposure to smoke emissions. The capacity to reduce risk through fuel reductions was spatially correlated with risk; where these diverged, the difference was largely explained by fuel load. We suggest that both risk and the capacity for risk reduction are important in identifying priorities for management interventions. The model serves as a decision support tool for stakeholders to coordinate large-landscape adaptive management initiatives in the Southern US. The model is flexible with regard to both empirical and expert-driven parameterizations and can be updated as new knowledge and data emerge. The resulting spatial information can help connect active management options to forest management goals and make management more efficient through targeted investments in priority landscapes. Full article

In the Lubumbashi charcoal production basin (LCPB) in Southeastern DR Congo, agricultural and charcoal production activities regularly give rise to fires that lead to considerable degradation of the miombo open forest. This study analyzes the drivers of the spatiotemporal distribution of active fires and burnt areas in the LCPB by processing MODIS and Landsat data. In addition, a kernel density analysis method (KDE) was used to estimate fire risk, while the effect of the road network and dwellings on vegetation fires was highlighted in areas between a 0 and 3000 m radius. The obtained results revealed that fires in the LCPB generally occur between April and November, mainly during the day, between 11 a.m. and 12 p.m. These fires are concentrated in the central and southwestern part of the LCPB, more specifically in the savannahs and near roads. From 2002 to 2022, an average of 11,237 active fires and an average of 6337 km² of burnt areas were recorded in the LCPB. Each year, these fires peak in August, and despite their steady decline, the few fires that have affected the forests have caused more devastation (more than 2790 km²/year) than those observed in the fields and savannah. These figures highlight the imperative need to put in place fire prevention and management measures in the LCPB, with particular emphasis on awareness, monitoring, and fire-fighting measures. Full article

The diamondback terrapin (Malaclemys terrapin), a brackish water turtle species native to the eastern United States, is under “special concern” in the state of New Jersey, due to decreasing habitat from development and changing climatic conditions. Diamondback terrapins reside in saline marshes and coastal wetlands and nest in sandy substrate, primarily beaches and dunes, in June and July. New Jersey is vulnerable to sea level rise, leaving diamondback terrapin habitats and nesting areas at risk of inundation under future climate scenarios, and, as the most densely populated state, subject to continual development pressures on potentially conservable land. Changing sea levels and climatic conditions will cause accretion and migration of marshes into open grassy land, yielding new potential terrapin habitats, though changing temperatures could affect the availability of male-producing nesting sites and impact potential nesting patterns. This study spatially modeled lost, gained, and changed habitat and nesting areas under sea level rise scenarios for 2050 and 2100 in New Jersey and quantified these by municipality to offer insights into potential conservable land that may mitigate these changes for the vulnerable species. The results indicate an overall decrease in potential habitat coupled with a decrease in both overall and male-producing nesting ranges. Full article

Applying the livelihood resilience theory to the relocation of coal mining villages, the present study explored the levels and the factors hindering livelihood resilience among farmers under different relocation models. This has important implications for enhancing the livelihood resilience of farmers during coal mining relocation and promoting rural revitalization in coal mining areas. Based on the livelihood resilience framework and the actual conditions of mining areas, we formulated an evaluation index system, employed the stratified mean square deviation method to determine weights, used the comprehensive index method to assess the livelihood resilience level, and investigated the obstacles to livelihood resilience among farmers under different relocation models using the random forest model. The results indicate the following: first, the overall livelihood resilience level in the coal mining relocation area of Huaibei City is low and is not significantly different among the four types, with the ranking being as follows: central village agglomeration type > township-centered village construction type > mining-village combination type > suburban community type. Significant differences exist in the indicators and dispersion levels of the resilience dimensions of buffering capacity, self-organization ability, and learning ability among farmers under different relocation models. Second, factors such as household deposits, labor force quantity, social networks, and participation in village collective meetings significantly affect the livelihood resilience level of farmers. However, the degree of influence varies under different relocation models. Third, improvements such as increasing employment opportunities, investing in education resources, and building social networks are necessary to improve farmers’ livelihoods under the four types of relocation models. Full article

As the global population rises, there is an ever-increasing demand for food, in terms of volume, quality and sustainable production. Protected Cropping Structures (PCS) provide controlled farming environments that support the optimum use of crop inputs for plant growth, faster production cycles, multiple growing seasons per annum and increased yield, while offering greater control of pests, disease and adverse weather. Globally, there has been a rapid increase in the adoption of PCS. However, there remains a concerning knowledge gap in the availability of accurate and up-to-date spatial information that defines the extent (location and area) of PCS. This data is fundamental for providing metrics that inform decision making around forward selling, labour, processing and infrastructure requirements, traceability, biosecurity and natural disaster preparedness and response. This project addresses this need, by developing a national map of PCS for Australia using remotely sensed imagery and deep learning analytics, ancillary data, field validation and industry engagement. The resulting map presents the location and extent of all commercial glasshouses, polyhouses, polytunnels, shadehouses and permanent nets with an area of >0.2 ha. The outcomes of the project revealed deep learning techniques can accurately map PCS with models achieving F-Scores > 0.9 and accelerate the mapping where suitable imagery is available. Location-based tools supported by web mapping applications were critical for the validation of PCS locations and for building industry awareness and engagement. The final national PCS map is publicly available through an online dashboard which summarises the area of PCS structures at a range of scales including state/territory, local government area and individual structure. The outcomes of this project have set a global standard on how this level of mapping can be achieved through a collaborative, multifaceted approach. Full article

The COVID-19 lockdown has deepened inequity among vulnerable groups, such as the elderly. Reducing inequity in access to essential service facilities is an effective way to improve community resilience in dealing with pandemics. In this research, three indexes were created to measure community resilience in accessing essential services. Specifically, we have considered the different walking capacity and different needs of the elderly and the general population. We selected Shanghai as the case for our research and analyzed the spatial patterns of both space-based and population-based essential service facilities. The Lorenz curve and the Gini coefficient were used to measure the spatial equity. And, we attempted to reveal the relationships between the population density and three indexes through bivariate Local Indicators of Spatial Association. The results suggest that the Diversity Index enjoys the highest equity, followed by the Demand Accessibility Index, and the equity of the Per Capita Quantity Index is the lowest. Furthermore, the accessibility of essential services in urban areas is excellent, while in some suburban areas it is low. Our findings contribute valuable scientific insights for policy makers to strengthen community resilience and address inequities for immediate or long-term measures. Full article

The Convention on Biological Diversity (CBD) has been a pivotal international instrument for global biodiversity conservation since 1992. The recent Kunming-Montreal Global Biodiversity Framework (GBF) aims to provide a pathway for the CBD for the present decade. However, the practicalities of land use and biodiversity conservation pose significant challenges. Drawing from diverse literature and reports, we identify nine implementation challenges for the GBF. These encompass harmonising conservation with sustainable development, integrating local values and indigenous knowledge, adopting a holistic landscape approach, and prioritising effective local governance. A shift from broad targets to explicit conservation metrics is vital. We propose strategies emphasising building institutional capacity for localised, participatory conservation and policy-making processes. This article offers suggestions for improving the GBF’s implementation and shaping future policy frameworks. Full article

To mitigate the urban heat island phenomenon at night, cool, fresh air can be introduced into the city to circulate and dissipate the heat absorbed during the day, thereby reducing high urban air temperatures. In other words, cold air flow (CAF) generated by mountainous and green areas should be introduced to as wide an area as possible within the city. To this end, it is necessary to first understand the characteristics of urban spatial factors that impact CAF, and to conduct concrete and quantitative analyses of how these urban spatial characteristics are contributing to air temperature reduction. In this study, the following are conducted: (1) an analysis of the relationship between cold air volume flux (CAVF) and the amount of air temperature reduction; (2) urban spatial categorization; (3) an analysis of the relationship between CAVF and the amount of air temperature reduction by urban spatial type; (4) a regression analysis between the amount of air temperature reduction and urban spatial characteristic factors that affect CAF; and finally, (5) the use of CAF to reduce urban air temperatures in urban planning and a design is proposed. Urban space was categorized into nine types using the results of the tertile analysis of CAVF and urban temperature reduction. It was determined that building height (BH) has a positive (+) influence on all urban spatial types, while building area ratio (BA) has a negative (−) effect. However, in the case of wall area index (WAI), the direction of influence varied depending on the development density; relatively low BA areas should focus on development that increases height to increase WAI, while relatively high BA areas should focus on development that reduces BA to reduce WAI by targeting development types closer to the tower type. And even in areas with similar development density, influence varies depending on the terrain elevation. Moreover, it is necessary to prepare improvement measures to increase the factors with CAF that positively influence air temperature reduction and decrease those with negative influence according to the characteristics of urban spatial types. Such results quantitatively and specifically confirmed the effects of spatial factors that affect CAF by urban spatial type on air temperature reduction. The results of this study can be used as useful information for the efficient use of CAF, a major element of urban ecosystem services. Full article

Effectively managing the diversity and complexity of human settlements is pivotal in tackling the sustainability challenges we face in the Anthropocene. Conceptualizing a city’s human settlement as a unified social–ecological system and investigating its system archetype and evolutionary pattern offer a promising approach to understanding sustainability challenges within specific spatio-temporal contexts. This study introduced a novel approach to assessing and characterizing human settlements using a spatio-temporal two-tier structure archetype analysis for human settlement systems. Applying inductive clustering to an integrated dataset, we identified five typical human settlement systems for 2019 and eight change patterns (2001–2019) in the Yangtze River Delta region. By linking inductively recognized human settlement systems into deductive categories of human-nature connectedness and associating inductive change patterns with deduced phases within the adaptive cycle, we defined five system spatial archetypes and three archetypical evolutionary patterns, revealing the typical interaction between them. This enabled us to understand sustainability challenges for each interaction, formulating seven tailored solutions to promote place-based development in human settlements. Generally, our approach showcases considerable potential in uncovering human settlement challenges, ultimately contributing to addressing these challenges at the local level within the broader context of global sustainability issues. Full article

Adverse environmental impacts in the watershed are driven by urbanization, which is reflected by land use and land cover (LULC) transitions, such as increased impervious surfaces, industrial land expansion, and green space reduction. Some adverse impacts on the water environment include urban flooding and water quality degradation. Our study area, the Rouge River Watershed, has been susceptible to accelerated urbanization and degradation of ecosystems. Employing the Land Change Modeler (LCM), we designed four alternative urban development scenarios for 2023. Subsequently, leveraging the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), we utilized two models—Nutrient Delivery Ratio (NDR) and Flood Risk Mitigation (UFRM)—to evaluate and compare the performance of these scenarios, as well as the situation in 2019, in terms of nutrient export and urban flooding. After simulating these scenarios, we determined that prioritizing the medium- and high-intensity development scenario to protect open space outperforms other scenarios in nutrient export. However, the four scenarios could not exhibit significant differences in urban flooding mitigation. Thus, we propose balanced and integrative strategies, such as planning green infrastructure and compact development, to foster ecological and economic growth, and enhance the Rouge River Watershed’s resilience against natural disasters for a sustainable future. Full article

In the post-pandemic era, the need for accessible urban green open spaces has increased. There is an urgent need to accurately identify large-scale unit-affiliated green spaces and focus on the potential for open sharing. Therefore, using POI data from the Gaode map of Shanghai obtained via web crawler, combined with remote sensing image data and the current green space data, the subjects of unit-affiliated green spaces in the main urban area and five new towns of Shanghai were identified in 2021. On this basis, in-depth explorations were carried out in terms of the type and number of subjects, the overall layout, and the grading of potential open sharing. A new application path for identifying subjects of unit-affiliated green spaces based on the POI data was established. The analysis of the potential openness of the subjects strongly supports the open sharing of unit-affiliated green spaces; the open sharing of unit-affiliated green spaces can compensate for the deficiencies in the fairness and efficiency of urban green spaces. Full article

It is widely recognized that urban resilience is one of the core goals of urban development. As an important part of a city, the resilience level of urban human settlements directly affects the development trend of urban resilience. However, at present, research results on the resilience of urban human settlements are very rare, are mainly concentrated in the central region of China, and rarely take into account the economically backward northeastern region. Therefore, in order to better improve the anti-risk ability of the urban human settlement environment system in three provinces of Northeast China, fully implement the strategic goal of “Comprehensive Revitalization of Northeast China”, and achieve high-quality urban development, this paper focuses on 34 prefecture-level cities in three provinces of Northeast China and proposes an urban human settlement resilience evaluation system with 36 indicators in five dimensions, namely, the natural system, human system, housing system, supporting system, and social system. Using the entropy weight method, the Dagum Gini coefficient, and a geographical probe model, the changes in the resilience level of each city from 2005 to 2020 were measured, and the urban living environment was assessed in terms of the adaptability and resilience of the development level in each subsystem based on the temporal and spatial evolution law and its influencing factors. The following conclusions were drawn: (1) The development level of urban human settlement resilience in the three provinces in Northeast China showed an N-shaped development trend from 2005 to 2020, but the regional differences were significant, and the overall spatial pattern was “high in the south and low in the north”. (2) In terms of the overall difference, the overall difference in urban human settlement resilience in the three northeastern provinces of China was small: the inter-regional difference was the main source of the difference, and the intra-regional difference was the secondary source. The regional differences were in the order of Heilongjiang Province > Liaoning Province > Jilin Province, indicating that Jilin Province had the smallest difference and that the resilience level of urban human settlements does not show a balanced development trend. In terms of the average Gini coefficient between regions, the order of difference was Liaoning Province–Heilongjiang Province > Jilin Province–Liaoning Province > Jilin Province–Heilongjiang Province, indicating that the difference between Liaoning Province and Heilongjiang Province was the most significant. (3) The “natural system”, “human system”, “living system”, “supporting system”, and “social system” had significant spatial and temporal heterogeneity and significantly affected the resilience level of urban human settlements in the three provinces in Northeast China. Among them, the “social system” has always been the main factor affecting the resilience level of urban human settlements. Full article

With regard to the aims of achieving the “Dual Carbon” goal and addressing the significant greenhouse gas emissions caused by urban expansion, there has been a growing emphasis on spatial research and the prediction of urban carbon emissions. This article examines land use data from 2000 to 2020 and combines Grid and the PLUS model to predict carbon emissions in 2030 through a multi-scenario simulation. The research findings indicate the following: (1) Between 2000 and 2020, construction land increased by 95.83%, with carbon emissions also increasing. (2) By 2030, for the NDS (natural development scenario), carbon emissions are expected to peak at 6012.87 × 10⁴ t. Regarding the ratio obtained through the EDS (economic development scenario), construction land is projected to grow to 3990.72 km², with expected emissions of 6863.29 × 10⁴ t. For the LCS (low-carbon scenario), the “carbon peak” is expected to be reached before 2030. (3) The intensity of carbon emissions decreases as the city size increases. (4) The shift of the center of carbon emission intensity and the center of construction land all indicate movement towards the southeast. Studying the trends of regional land use change and the patterns of land use carbon emissions is beneficial for optimizing the land use structure, thereby enabling us to achieve low-carbon emission reductions and sustainable urban development. Full article

In key moments of urban history, urban design is confronted with the emergence of new paradigmatic design models, such as the garden city and the radiant city. Recently, the Smart City seems to have gained centre stage in the public debate. However, despite its emblazoned technological features, the Smart City remains a hazy concept in the urban design domain to such an extent that almost any form can be built under the Smart City label. While this may sound libertarian and progressist, it is also concerning since different urban forms are associated with different societal outcomes. This paper aims to investigate the forms of Smart City districts through morphometric comparison. More specifically, it proposes a replicable methodology based on 18 metrics of urban form and statistical analysis to compare a Smart City district with other city areas with known design models of reference. Such a methodology is applied to three case studies on the French Riviera: Méridia, a Smart City district, Hôtel-des-Postes, a 19th-century traditional district, and Sophia Antipolis, a sprawling technopark. The results show that Méridia has a hybrid form that partly resembles Hôtel-des-Postes (higher densities, gridiron plan, and functional mix) and partly Sophia Antipolis (bulky buildings with large setbacks). However, the top–down approach used in the production of the physical space ultimately renders Méridia more similar to Sophia Antipolis than Hôtel-des-Postes. This study provides one of the first morphometric characterisations of a Smart City district, but also a replicable methodology that can further the morphological understanding of the Smart City phenomenon worldwide. Full article