Journal Description
Land
Land
is an international and cross-disciplinary, peer-reviewed, open access journal on land system science, landscape, soil–sediment–water systems, urban study, land–climate interactions, water–energy–land–food (WELF) nexus, biodiversity research and health nexus, land modelling and data processing, ecosystem services, and multifunctionality and sustainability etc., published monthly online by MDPI. The International Association for Landscape Ecology (IALE), European Land-use Institute (ELI), Landscape Institute (LI) and Urban Land Institute (ULI) are affiliated with Land, and their members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SSCI (Web of Science), PubAg, AGRIS, GeoRef, RePEc, and other databases.
- Journal Rank: JCR - Q2 (Environmental Studies) / CiteScore - Q2 (Nature and Landscape Conservation)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 14.8 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.9 (2022);
5-Year Impact Factor:
4.0 (2022)
Latest Articles
Exploring Drivers of Wildfires in Spain
Land 2024, 13(6), 762; https://doi.org/10.3390/land13060762 - 28 May 2024
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Wildfires play a dual role in ecosystems by providing ecological benefits while posing catastrophic events; they also inflict non-catastrophic damage and yield long-term effects on biodiversity, soil quality, and air quality, among other factors, including public health. This study analysed the key determinants
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Wildfires play a dual role in ecosystems by providing ecological benefits while posing catastrophic events; they also inflict non-catastrophic damage and yield long-term effects on biodiversity, soil quality, and air quality, among other factors, including public health. This study analysed the key determinants of wildland fires in Spain using openly available spatial data from 2008 to 2021, including fire perimeters, bioclimatic variables, topography, and socioeconomic datasets, at a resolution of 1 km2. Our methodology combined principal component analysis (PCA), linear regression analysis, and one-way analysis of variance (ANOVA). Our findings show that scrub/herbaceous vegetation (average 63 ± 1.45% SE) and forests (average 19 ± 0.76% SE) have been highly susceptible to wildfires. The population density exhibited a robust positive correlation with wildfire frequency (R2 = 0.88, p < 0.0001). Although the study provides insights into some fire-related climatic drivers over Spain, it includes only temperature and precipitation-based variables and does not explicitly consider fuel dynamics. Therefore, a more advanced methodology should be applied in the future to understand the local specifics of regional wildfire dynamics. Our study identified that scrub/herbaceous areas and forests near densely populated regions should be prioritised for wildfire management in Spain, particularly under changing climate conditions.
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Open AccessArticle
Enhancing Urban Land Use Identification Using Urban Morphology
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Chuan Lin, Guang Li, Zegen Zhou, Jia Li, Hongmei Wang and Yilun Liu
Land 2024, 13(6), 761; https://doi.org/10.3390/land13060761 - 28 May 2024
Abstract
Urban land use provides essential information about how land is utilized within cities, which is critical for land planning, urban renewal, and early warnings for natural disasters. Although existing studies have utilized multi-source perception data to acquire land use information quickly and at
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Urban land use provides essential information about how land is utilized within cities, which is critical for land planning, urban renewal, and early warnings for natural disasters. Although existing studies have utilized multi-source perception data to acquire land use information quickly and at low cost, and some have integrated urban morphological indicators to aid in land use identification, there is still a lack of systematic discussion in the literature regarding the potential of three-dimensional urban morphology to enhance identification effectiveness. Therefore, this paper aims to explore how urban three-dimensional morphology can be used to improve the identification of urban land use types. This study presents an innovative approach called the UMH–LUC model to enhance the accuracy of urban land use identification. The model first conducts a preliminary classification using points of interest (POI) data. It then improves the results with a dynamic reclassification based on floor area ratio (FAR) measurements and a variance reclassification using area and perimeter metrics. These methodologies leverage key urban morphological features to distinguish land use types more precisely. The model was validated in the Pearl River Delta urban agglomeration using random sampling, comparative analysis and case studies. Results demonstrate that the UMH–LUC model achieved an identification accuracy of 81.7% and a Kappa coefficient of 77.6%, representing an 11.9% improvement over a non-morphology-based approach. Moreover, the overall disagreement for UMH–LUC is 0.183, a reduction of 0.099 compared to LUC without urban morphology and 0.19 compared to EULUC-China. The model performed particularly well in identifying residential land, mixed-use areas and marginal lands. This confirms urban morphology’s value in supporting low-cost, efficient land use mapping with applications for sustainable planning and management.
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Open AccessArticle
Tenure Security Perception Patterns among Amazonian Communities in Peru: Gender and Ethnicity
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Zoila A. Cruz-Burga, María de los Ángeles La Torre-Cuadros, Iliana Monterroso and Anne M. Larson
Land 2024, 13(6), 760; https://doi.org/10.3390/land13060760 - 28 May 2024
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This study delves into perceptions of land and forest tenure (in)security among Indigenous and mestizo populations in the Peruvian Amazon. Despite all having collective lands, the selected communities vary in their formalisation processes. This research seeks to enhance comprehension of tenure security perceptions
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This study delves into perceptions of land and forest tenure (in)security among Indigenous and mestizo populations in the Peruvian Amazon. Despite all having collective lands, the selected communities vary in their formalisation processes. This research seeks to enhance comprehension of tenure security perceptions in the Peruvian Amazon by investigating sources of security and insecurity across key tenure components. A combination of descriptive, bivariate, and multivariate analyses is employed, based on fieldwork conducted between July 2015 and December 2017 in 22 Native and Peasant Communities in Loreto and Madre de Dios, utilising 1006 intra-household surveys, 52 in-depth interviews, and 44 focus group discussions. The results reveal similarities and differences in (in)security sources between titled and untitled communities. The study also explores the influence of gender and ethnicity on these perceptions, finding ethnicity-based variation in security perception over the past 20 years (1995–2015). Recognising these differences in perception is critical for assessing the robustness of exercising acquired collective rights.
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(This article belongs to the Special Issue Gender and Land)
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Korean Paradox of Public Support for the Research and Development Investment in the Sustainable Performance of the Regional Economy
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Yongrok Choi, Siyu Li and Hyoungsuk Lee
Land 2024, 13(6), 759; https://doi.org/10.3390/land13060759 - 28 May 2024
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The Swedish Paradox is a well-known phenomenon related to high research and development (R&D) investment with supposedly low aggregate economic performance owing to economic saturation. The Korean economy has not yet become an advanced economy; however, its R&D performance is negligible. Recently, also
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The Swedish Paradox is a well-known phenomenon related to high research and development (R&D) investment with supposedly low aggregate economic performance owing to economic saturation. The Korean economy has not yet become an advanced economy; however, its R&D performance is negligible. Recently, also the R&D share of the GNP has become much higher, and its contribution to the economic growth rate is rapidly decreasing, implying a negative relationship between R&D activities and economic performance. This study uses slacks-based data envelopment analysis to investigate investment performance at the local government level in Korea. Our findings reveal that the average score for R&D investment performance in Korea is 64%, indicating huge potential for an efficiency enhancement of 36%. Notably, among the 16 local governments examined, Seoul and its surrounding metropolitan areas showed the lowest R&D efficiency, while Gangwon and Gwangju exhibited superior performance. Since these two regions have promoted specific missions, such as the medical hub in Gangwon and the optical fiber strategic platform in Gwangju, precise and accurate differentiation appears necessary to avoid a lack of governance. To determine the workable mechanism of R&D support policies, we further divided R&D productivity into three categories by incorporating the Malmquist Index (MI). The paper productivity of R&D shows an increasing trend over the experimental period from 2016 to 2021. However, overall, the MI shows slightly deteriorating productivity with 0.978, owing to the aggravating effect of patents and commercialization of R&D. The success in the paper comes from the harmonized partnership between the strong push factor of the government and voluntary pull factor of the R&D support receiving universities. Thus, we suggest that the Korean government should not depend on the superficial effectiveness of R&D in the term but on public–private partnerships with stronger performance-oriented responsibility.
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(This article belongs to the Section Land Socio-Economic and Political Issues)
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Digital and Culture: Towards More Resilient Urban Community Governance
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Hongxun Xiang, Xia Heng, Boleng Zhai and Lichen Yang
Land 2024, 13(6), 758; https://doi.org/10.3390/land13060758 - 28 May 2024
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Urban communities are characterized by significant population size, high density, and strong mobility. While we might enjoy the dividends of rapid modernization, there are nonetheless variable and frequent public crises that occur. Modernization’s problems are gradually emerging, and the traditional risk prevention logic
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Urban communities are characterized by significant population size, high density, and strong mobility. While we might enjoy the dividends of rapid modernization, there are nonetheless variable and frequent public crises that occur. Modernization’s problems are gradually emerging, and the traditional risk prevention logic that relies on administrative “rigidity” has begun to be widely challenged. Traditional urban communities depend on institutional, structural, and spatial aspects to improve community resilience. Because big data has become popular, attention has begun to be paid to digital empowerment and community resilience. However, the emergence of problems such as “digital paradox” and “digital ethics” in the digital realm itself has prompted calls for cultural resilience to continue to rise. Therefore, urgently needed resolutions are required to questions regarding the resilience of traditional communities, the construction of digital and cultural resilience, the relationship between digital and cultural resilience, and the manner in which cultural resilience is coordinated to solve the problem of digital resilience. A quantitative analysis of 350 questionnaires from five urban communities found that these communities’ institutional, spatial, and structural dimensions are the driving factors for improving resilience. In contrast, the cultural and digital dimensions are constraints. Therefore, the question of how to coordinate the cultural and digital factors represented by traditional and modern societies in order to compensate for the shortcomings in resilience construction is that which future urban communities must consider. The authors of this study believe that digital empowerment is needed to open up the “first mile” of resilient communities, that cultural empowerment is required to break down the “blocks in the middle” of resilient communities, and that digital and cultural coupling is needed to link the “last mile” of resilient communities. One must use culture to compensate for the shortcomings of digital resilience and digital to pay for the failures of cultural resilience before one can move towards more resilient urban community governance.
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(This article belongs to the Topic Artificial intelligence, Risk resilience and Sustainable Development)
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Quantifying Urban Spatial Morphology Indicators on the Green Areas Cooling Effect: The Case of Changsha, China, a Subtropical City
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Jiang Li, Hao Wang, Xiaoxi Cai, Shaobo Liu, Wenbo Lai, Yating Chang, Jialing Qi, Gexuan Zhu, Chuyu Zhang and Yudan Liu
Land 2024, 13(6), 757; https://doi.org/10.3390/land13060757 - 28 May 2024
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Green city areas are crucial in mitigating the Urban Heat Island Effect (UHI). However, the cooling effect of green city areas can be influenced by the surrounding complex urban spatial environment. This study focuses on Changsha, a subtropical city in China, where 40
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Green city areas are crucial in mitigating the Urban Heat Island Effect (UHI). However, the cooling effect of green city areas can be influenced by the surrounding complex urban spatial environment. This study focuses on Changsha, a subtropical city in China, where 40 green city areas were screened and analyzed. The study aims to quantify the specific impact of urban spatial morphology on the cooling effect of green city areas. Through statistical correlation and regression analysis, this study focused on six urban spatial morphology indicators: building density (BD), building floor area ratio (BFR), building volume density (BVD), building evenness index (BEI), building average height (BH), and building height standard deviation (BSD). The results indicate that the cooling effect of green city areas could be influenced by urban spatial morphology. Factors such as BD, BFR, BH, and BSD were found to be significantly correlated with the cooling effect of green city areas, with BH showing the strongest influence. BD and BFR were negatively correlated, while BH and BSD were positively correlated. The range values of BD, BFR, BH, and BSD were determined to achieve the optimal conditions for the cooling effect of green city areas. Additionally, the relative position of the green city areas in the neighboring urban areas affects the cooling effect of the green city areas. The cooling effect is most pronounced in the urban area situated to the south of the green city areas. These findings provide a solid foundation for urban planning around green city spaces and offer scientifically sound evidence for mitigating the UHI.
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(This article belongs to the Topic SDGs 2030 in Buildings and Infrastructure)
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Between Struggle, Forgetfulness, and Placemaking: Meanings and Practices among Social Groups in a Metropolitan Urban Park
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Ana Rosenbluth, Teresa Ropert, Vicente Rivera, Matías Villalobos-Morgado, Yerko Molina and Ignacio C. Fernández
Land 2024, 13(6), 756; https://doi.org/10.3390/land13060756 - 28 May 2024
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Urban spatial segregation in Santiago de Chile, a prevalent feature of Latin American cities, underscores socioeconomic disparities and shapes the city’s socio-spatial dynamics. This segregation, driven by land prices and private ownership, has pushed disadvantaged groups to the periphery and limited their access
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Urban spatial segregation in Santiago de Chile, a prevalent feature of Latin American cities, underscores socioeconomic disparities and shapes the city’s socio-spatial dynamics. This segregation, driven by land prices and private ownership, has pushed disadvantaged groups to the periphery and limited their access to desirable areas reserved for wealthier segments of society. Quebrada Macul Park, situated within this segregated urban landscape, serves as an emblematic case that challenges and expands the classical definition of urban segregation. It exemplifies the complex negotiations over space utilization among social groups, defined by socioeconomic, generational, and interest-based differences. This study employs micro-segregation studies in a broad sense, both as a conceptual framework and as a methodological tool to analyze these dynamics. Through qualitative methodologies, including six in-depth interviews with diverse stakeholders (social and ecological activists, longtime residents, and park employees) and five participant observations, the research investigates the varied uses and meanings attributed to the park. The findings reveal that the park’s evolution from a space frequented by low-income dwellers to a diverse metropolitan park has sparked debates over its public versus private character, mirroring the power struggles among distinct social factions. The park serves as a profound identity marker for its historical inhabitants, who initially fought for the right to use it and today experience nostalgia due to its widespread popularity. Meanwhile, the struggle to establish the park as a public space challenges the city’s segregation dynamics and might promote social cohesion within urban natural environments.
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(This article belongs to the Special Issue Urban Micro-Segregation)
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Practicing Multilevel Governance: The Revision of the Piedmont Regional Territorial Plan
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Elena Todella, Francesca Abastante and Giancarlo Cotella
Land 2024, 13(6), 755; https://doi.org/10.3390/land13060755 - 28 May 2024
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The regional level plays a relevant role in spatial governance and planning in Europe, as it constitutes the most suitable scale to both program European Union funding and territorialize international development strategies. In this light, regional spatial planning instruments play a crucial role
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The regional level plays a relevant role in spatial governance and planning in Europe, as it constitutes the most suitable scale to both program European Union funding and territorialize international development strategies. In this light, regional spatial planning instruments play a crucial role in translating general objectives and recommendations (e.g., those included in the UN 2030 Agenda for Sustainable Development) in place-based implementation practices. This contribution reflects upon the implementation of a methodology aimed at engaging a multidisciplinary team of students in the revision of the Piedmont regional territorial plan (PTR), developed in close cooperation with the regional public administration. This problem-based learning activity supported the integration of supranational strategic objectives and funding streams with the regional territorial development priorities. In so doing, it represents a possible way to practice multilevel governance in concrete terms, employing the PTR as a meaningful catalyst.
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(This article belongs to the Special Issue Fostering Urban Regeneration Pathways via Urban and Architectural Design Projects)
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Evaluating Performance of Multiple Machine Learning Models for Drought Monitoring: A Case Study of Typical Grassland in Inner Mongolia
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Yuchi Wang, Jiahe Cui, Bailing Miao, Zhiyong Li, Yongli Wang, Chengzhen Jia and Cunzhu Liang
Land 2024, 13(6), 754; https://doi.org/10.3390/land13060754 - 28 May 2024
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Driven by continuously evolving precipitation shifts and temperature increases, the frequency and intensity of droughts have increased. There is an obvious need to accurately monitor drought. With the popularity of machine learning, many studies have attempted to use machine learning combined with multiple
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Driven by continuously evolving precipitation shifts and temperature increases, the frequency and intensity of droughts have increased. There is an obvious need to accurately monitor drought. With the popularity of machine learning, many studies have attempted to use machine learning combined with multiple indicators to construct comprehensive drought monitoring models. This study tests four machine learning model frameworks, including random forest (RF), convolutional neural network (CNN), support vector regression (SVR), and BP neural network (BP), which were used to construct four comprehensive drought monitoring models. The accuracy and drought monitoring ability of the four models when simulating a well-documented Inner Mongolian grassland site were compared. The results show that the random forest model is the best among the four models. The R2 range of the test set is 0.44–0.79, the RMSE range is 0.44–0.72, and the fitting accuracy relationship could be described as RF > CNN > SVR ≈ BP. Correlation analysis between the fitting results of the four models and SPEI found that the correlation coefficient of RF from June to September was higher than that of the other three models, though we noted the correlation coefficient of CNN in May was slightly higher than that of RF (CNN = 0.79; RF = 0.78). Our results demonstrate that comprehensive drought monitoring indices developed from RF models are accurate, have high drought monitoring ability, and can achieve the same monitoring effect as SPEI. This study can provide new technical support for comprehensive regional drought monitoring.
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(This article belongs to the Special Issue Land Degradation and Land Productivity Assessment Using Remote Sensing)
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A Dual-Layer Complex Network-Based Quantitative Flood Vulnerability Assessment Method of Transportation Systems
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Jiayu Ding, Yuewei Wang and Chaoyue Li
Land 2024, 13(6), 753; https://doi.org/10.3390/land13060753 - 28 May 2024
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Evaluating the vulnerability of urban transportation systems to flood disasters can provide scientific support for urban disaster prevention and mitigation. Current methods for assessing the flood vulnerability of urban roads often overlook the internal relationships within the complex spatial composition of road networks
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Evaluating the vulnerability of urban transportation systems to flood disasters can provide scientific support for urban disaster prevention and mitigation. Current methods for assessing the flood vulnerability of urban roads often overlook the internal relationships within the complex spatial composition of road networks and surface structures. In this study, based on the theory of complex networks, a dual-layer network assessment model is established for evaluating the flood vulnerability of urban transportation systems by coupling basic geographic data with road network vector data. Unlike traditional methods, this model considers the complex relationship between road network structures and ground surfaces, uncovering a correlation between road network structure and road flood vulnerability. By utilizing this model, the flood vulnerability of road networks in Shenzhen, as well as the city’s spatial flood vulnerability, are quantitatively assessed. Based on the quantitative results, we create maps illustrating the distribution of road and spatial flood vulnerability in Shenzhen. The study results reflect that roads highly vulnerable to flooding are mainly located in the central urban area of the southwest, with the flood vulnerability spatially concentrated primarily in the northern and western regions. Using data from government reports, news stories, and other sources over the past five years, we compile recorded instances of urban waterlogging. The quantitative results of the model are consistent with the distribution trend in recorded waterlogging points, indicating that the model’s outcomes are authentic and reliable.
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(This article belongs to the Topic Spatial Patterns of Disaster Risk Assessment via Remote Sensing)
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Introduction of the Approach for Reviving the Sub-Municipal Level as a Spatial Aspect of Decentralization in Serbia
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Marija Drobnjaković and Milena Panić
Land 2024, 13(6), 752; https://doi.org/10.3390/land13060752 - 28 May 2024
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Decentralization is a globally accepted concept of separation, the diversity of structures within the political system, the transfer of resources, activities, and powers in the decision-making process, and the division of tasks from the central government to lower authorities. It is implemented in
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Decentralization is a globally accepted concept of separation, the diversity of structures within the political system, the transfer of resources, activities, and powers in the decision-making process, and the division of tasks from the central government to lower authorities. It is implemented in both developed and developing countries, with different aims and consequences. In Serbia, the urban-centric development model and centralized governance caused rural settlements to become non-viable, and services and opportunities were deprived. This research has been undertaken in order to provide a deeper understanding of the territorial aspect of decentralization in Serbia and how it affects rural areas. It strives to offer a methodological framework for the identification of central settlements in rural areas of Serbia that will serve as a focal point for settlements networking in order to facilitate the spatial integration of rural areas and governance at the local level. This research encompasses (i) the identification of rural nodes as bearers of balanced governance and spatial development; (ii) the delimitation of their gravity sphere; and (iii) the determination of the relationship between settlement organization models and decentralization in Serbia. The research results indicate that identified rural nodes can be valuable to developing a holistic understanding of rural issues, supporting a bottom-up approach and regional disparities mitigation.
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(This article belongs to the Section Urban Contexts and Urban-Rural Interactions)
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Effects of Winery Wastewater to Soils on Mineral Properties and Soil Carbon
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Max Nightingale-McMahon, Brett Robinson, Brendon Malcolm, Tim Clough and David Whitehead
Land 2024, 13(6), 751; https://doi.org/10.3390/land13060751 - 28 May 2024
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Winery wastewater (WW) is a high-volume biowaste and, in the context of Marlborough and New Zealand wineries, there is a growing recognition of the need to improve current WW disposal systems to mitigate negative environmental impacts. The application of WW to land is
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Winery wastewater (WW) is a high-volume biowaste and, in the context of Marlborough and New Zealand wineries, there is a growing recognition of the need to improve current WW disposal systems to mitigate negative environmental impacts. The application of WW to land is a low-cost method of disposal, that could significantly reduce the environmental risk associated with WW directly entering surface and groundwater bodies. This study analysed elemental concentrations in WW and soils from three Marlborough vineyards across their annual vintage to determine the loading rates of nutrients into WW and the subsequent accumulation effects of WW irrigation on receiving soils. The findings showed loading rates of approximately 1.8 t ha−1 yr−1 of sodium within WW and a significant increase in soil sodium concentration and pH, attributed to sodium-based cleaning products. A loading rate of approximately 4 t ha−1 yr−1 of total organic carbon was also identified within WW, however, significant losses in soil carbon, nitrogen, magnesium and calcium concentrations were identified. Focusing efforts to retain key nutrients from WW within soils could provide benefits to New Zealand’s wine industry, facilitating increased biomass production in irrigation plots, thereby increasing biodiversity and potentially generating incentives for vineyard owners to contribute to increasing biomass carbon stocks and offset agricultural greenhouse gas emissions.
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An Assessment of Landscape Perception Using a Normalised Naturalness Index in the Greater Seoul Area
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Doeun Kim and Yonghoon Son
Land 2024, 13(6), 750; https://doi.org/10.3390/land13060750 - 28 May 2024
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This study analysed the greater Seoul area (GSA) in terms of naturalness, a representative indicator of natural scenic beauty, and created an assessment map, shifting from a traditional urban development perspective to a landscape perspective. It also developed a “normalised naturalness index” by
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This study analysed the greater Seoul area (GSA) in terms of naturalness, a representative indicator of natural scenic beauty, and created an assessment map, shifting from a traditional urban development perspective to a landscape perspective. It also developed a “normalised naturalness index” by combining the results of the expert metric score with the Hemeroby index, which was used as a naturalness assessment representative item. Then, it interpreted the naturalness status of the GSA landscape characteristics. As a result, the landscape of the GSA demonstrates the following five characteristics: First, the central business districts in the capital city of Seoul are densely developed areas with a very high degree of human intervention. Second, the satellite cities built to solve Seoul’s housing and logistics problems are rated as “a little less, but still heavily humanised” as a landscape characteristic. These areas are becoming increasingly humanised. Also, it is worth noting that the third characteristic, regarding moderate landscape areas, has a distinctly different meaning for areas outside of the city boundary, as well as those within the city boundary. Although these areas are in the same statistical category, they have two different meanings: one is the area where the average values converged on “moderate” by virtue of urban forests near the city centre, and the other is the area outside of Seoul that has a Hemeroby value of 0.5–0.6, which refers to open spaces such as agricultural lands, wetlands, or coastal areas. Fourth, suburban forests are reserved with legal restrictions to curb excessive urban sprawl, as well as parts of the demilitarised zone along the border areas of North and South Koreas. The last landscape characteristic is illustrated in the scenic area of the eastern woodlands. The normalised landscape naturalness index developed through this study provides an overall understanding of the environmental state of the GSA. Future research may build on the results of this study to refine methods for assessing public perceptions of naturalness.
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(This article belongs to the Special Issue Advances in Landscape Perception Based on New Approaches & Technologies)
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Determining the Climatic Drivers for Wine Production in the Côa Region (Portugal) Using a Machine Learning Approach
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Helder Fraga, Teresa R. Freitas, Marco Moriondo, Daniel Molitor and João A. Santos
Land 2024, 13(6), 749; https://doi.org/10.3390/land13060749 - 28 May 2024
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The Côa region in inner-northern Portugal heavily relies on viticulture, which is a cornerstone of its economy and cultural identity. Understanding the intricate relationship between climatic variables and wine production (WP) is crucial for adapting management practices to changing climatic conditions. This study
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The Côa region in inner-northern Portugal heavily relies on viticulture, which is a cornerstone of its economy and cultural identity. Understanding the intricate relationship between climatic variables and wine production (WP) is crucial for adapting management practices to changing climatic conditions. This study employs machine learning (ML), specifically random forest (RF) regression, to predict grapevine yields in the Côa region using high-resolution climate data for 2004–2020. SHAP (SHapley Additive exPlanations) values are used to potentially explain the non-linear relationships between climatic factors and WP. The results reveal a complex interplay between predictors and WP, with precipitation emerging as a key determinant. Higher precipitation levels in April positively impact WP by replenishing soil moisture ahead of flowering, while elevated precipitation and humidity levels in August have a negative effect, possibly due to late-season heavy rainfall damaging grapes or creating more favorable conditions for fungal pathogens. Moreover, warmer temperatures during the growing season and adequate solar radiation in winter months favor higher WP. However, excessive radiation during advanced growth stages can lead to negative effects, such as sunburn. This study underscores the importance of tailoring viticultural strategies to local climatic conditions and employing advanced analytical techniques such as SHAP values to interpret ML model predictions effectively. Furthermore, the research highlights the potential of ML models in climate change risk reduction associated with viticulture, specifically WP. By leveraging insights from ML and interpretability techniques, policymakers and stakeholders can develop adaptive strategies to safeguard viticultural livelihoods and stable WP in a changing climate, particularly in regions with a rich agrarian heritage, such as the Côa region.
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Evaluating the Cost-Effectiveness of Green Infrastructure for Mitigating Diffuse Agricultural Contaminant Losses
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Yvonne S. Matthews, Paula Holland, Fleur E. Matheson, Rupert J. Craggs and Chris C. Tanner
Land 2024, 13(6), 748; https://doi.org/10.3390/land13060748 - 27 May 2024
Abstract
New Zealand’s agricultural sector faces the challenge of maintaining productivity while minimizing impacts on freshwaters. This study evaluates the cost-effectiveness of various green infrastructure systems designed to reduce diffuse agricultural sediment and nutrient loads. Utilizing a quantitative economic and contaminant reduction modeling approach,
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New Zealand’s agricultural sector faces the challenge of maintaining productivity while minimizing impacts on freshwaters. This study evaluates the cost-effectiveness of various green infrastructure systems designed to reduce diffuse agricultural sediment and nutrient loads. Utilizing a quantitative economic and contaminant reduction modeling approach, we analyze the impacts of five interceptive mitigation systems: riparian grass filter strips, constructed wetlands, woodchip bioreactors, filamentous algal nutrient scrubbers, and detainment bunds. Our approach incorporates Monte Carlo simulations to address uncertainties in costs and performance, integrating hydrological flow paths and contaminant transport dynamics. Mitigation systems are assessed individually and in combination, using a greedy cyclical coordinate descent algorithm to find the optimal combination and scale of a system for a particular landscape. Applying the model to a typical flat pastoral dairy farming landscape, no single system can effectively address all contaminants. However, strategic combinations can align with specific freshwater management goals. In our illustrative catchment, the mean cost to remove the full anthropogenic load is NZD 1195/ha for total nitrogen, NZD 168 for total phosphorus, and NZD 134 for suspended solids, but results will vary considerably for other landscapes. This study underscores the importance of tailored deployment of green infrastructure to enhance water quality and support sustainable agricultural practices.
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(This article belongs to the Special Issue Innovations in Agricultural Green Infrastructure)
Open AccessArticle
Analysis of the Spatiotemporal Evolution of Carbon Budget and Carbon Compensation Zoning in the Core Area of the Yangtze River Delta Urban Agglomeration
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Yuxin Tang, Ran Wang, Hui Ci, Jinyuan Wei, Hui Yang, Jiakun Teng and Zhaojin Yan
Land 2024, 13(6), 747; https://doi.org/10.3390/land13060747 - 27 May 2024
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As a world-class urban agglomeration, the Yangtze River Delta urban agglomeration is significant for China’s carbon neutrality strategy when calculating the carbon budget and dividing carbon compensation zones. This paper focused on 129 county-level cities in the core area of the Yangtze River
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As a world-class urban agglomeration, the Yangtze River Delta urban agglomeration is significant for China’s carbon neutrality strategy when calculating the carbon budget and dividing carbon compensation zones. This paper focused on 129 county-level cities in the core area of the Yangtze River Delta urban agglomeration, calculating the carbon budget for 2000–2020 using night-time light data and analyzing the evolution of spatiotemporal patterns. On this basis, a carbon compensation zoning model was constructed using the K-means algorithm; 129 cities were divided into different carbon compensation zones after combining this model with the main functional zones. The results showed that (1) the carbon emissions increased, with overall stabilization after 2012. The distribution of high carbon emission areas evolved from a “core-periphery” pattern into a “Z-shaped” pattern. Ecological carbon sinks showed a continuous decline, with the southern sinks performing better than the northern ones. (2) The carbon budget of the study area showed a deficit, gradually widening and exhibiting an unbalanced spatial distribution characterized by a “high in the south and low in the north” pattern. (3) Eleven types of carbon compensation zones were designated after overlaying the main functional zones. Low-carbon development suggestions were proposed for each zone type.
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Spatial and Temporal Distribution Characteristics and Influential Mechanisms of China’s Industrial Landscape Based on Geodetector
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Mi Yan, Qingmiao Li and Yan Song
Land 2024, 13(6), 746; https://doi.org/10.3390/land13060746 - 26 May 2024
Abstract
The industrial landscape constitutes a crucial aspect of a region’s historical and cultural identity, serving as a valuable asset in the development of industrial tourism. Exploring the industrial landscape supports initiatives in industrial tourism, acts as a catalyst for community revitalization, and contributes
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The industrial landscape constitutes a crucial aspect of a region’s historical and cultural identity, serving as a valuable asset in the development of industrial tourism. Exploring the industrial landscape supports initiatives in industrial tourism, acts as a catalyst for community revitalization, and contributes to sustainable urban progress. The primary objective of this research was to investigate the spatial distribution characteristics and underlying determinants of China’s industrial landscape (CIL) to inform urban planning, cultural heritage preservation, and sustainable development initiatives. This study utilized analytical tools, such as the nearest neighbor index, geographic concentration index, and hot spot analysis, to comprehensively examine the spatial distribution of CIL. Additionally, Geodetector was employed to explore the correlating factors behind this distribution. The findings reveal the following: (1) CIL exhibited a pronounced agglomerative spatial pattern characterized by a high degree of concentration, significant disparities, and substantial spatial autocorrelation. (2) Over time, the agglomeration of CIL varied, intensifying initially and then diminishing, with the center of gravity of its distribution shifting eastward before subsequently moving westward in a directional trend resembling “northeast–southwest”. (3) There was a diverse array of industrial landscape types within China, with notable disparities in the prevalence of different categories. The manufacturing and transportation sectors boasted the highest number of heritage sites. (4) The distribution pattern of CIL was shaped by factors such as the level of economic development, socio-demographic conditions, transportation infrastructure, and cultural milieu. The interplay between these factors had a substantial impact on this distribution pattern.
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(This article belongs to the Special Issue Feature Papers for Land Planning and Landscape Architecture Section)
Open AccessArticle
Drought Sensitivity and Vulnerability of Rubber Plantation GPP—Insights from Flux Site-Based Simulation
by
Runqing Zhang, Xiaoyu E, Zhencheng Ma, Yinghe An, Qinggele Bao, Zhixiang Wu, Lan Wu and Zhongyi Sun
Land 2024, 13(6), 745; https://doi.org/10.3390/land13060745 - 26 May 2024
Abstract
Drought, an intricate natural phenomenon globally, significantly influences the gross primary productivity (GPP) and carbon sink potential of tropical forests. Present research on the drought response primarily focuses on natural forests, such as the Amazon rainforest, with relatively limited studies on tropical plantations.
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Drought, an intricate natural phenomenon globally, significantly influences the gross primary productivity (GPP) and carbon sink potential of tropical forests. Present research on the drought response primarily focuses on natural forests, such as the Amazon rainforest, with relatively limited studies on tropical plantations. Therefore, for a comprehensive understanding of global climate change, accurately evaluating and analyzing the sensitivity and vulnerability of rubber plantation GPP to various drought characteristics is crucial. The Standardized Precipitation Evapotranspiration Index (SPEI) was used in this research to quantify drought intensity. The Spatially Explicit Individual Based Dynamic Global Vegetation Model (SEIB-DGVM) was localized based on observation data from the Hainan Danzhou Tropical Agro-ecosystem National Observation and Research Station. Subsequently, the calibrated model was utilized to simulate the dynamic process of rubber plantation GPP under multi-gradient drought scenarios (2 extreme boundaries × 3 drought initiation seasons × 4 drought intensities × 12 drought durations × 12 SPEI time scales). The results show that the sensitivity and vulnerability of rubber plantation GPP exhibit significant differences under drought scenarios in different initiation seasons; GPP exhibits higher sensitivity to extreme, long-duration flash droughts in the early rainy season. Regarding vulnerability, the impact of extreme, long-duration flash droughts on GPP is most pronounced. This research lays the foundation for estimating the impact of droughts on the GPP of rubber plantations under future climate change scenarios, providing a scientific basis for enhancing regional ecological restoration and protection.
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(This article belongs to the Special Issue Key Hydrological Processes and Its Controlling Factors in Terrestrial Ecosystems)
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Open AccessArticle
A Simulated Assessment of Land Use and Carbon Storage Changes in the Yanqi Basin under Different Development Scenarios
by
Ying Jiang, Yilinuer Alifujiang, Pingping Feng, Ping Yang and Jianpeng Feng
Land 2024, 13(6), 744; https://doi.org/10.3390/land13060744 - 26 May 2024
Abstract
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The most extensive carbon reservoir system on Earth is found in the vegetation and soil in terrestrial ecosystems, which are essential to preserving the stability of ecosystems. Land use/cover change (LUCC) patterns in terrestrial ecosystems significantly impact carbon storage (CS). Therefore, it is
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The most extensive carbon reservoir system on Earth is found in the vegetation and soil in terrestrial ecosystems, which are essential to preserving the stability of ecosystems. Land use/cover change (LUCC) patterns in terrestrial ecosystems significantly impact carbon storage (CS). Therefore, it is imperative to investigate the relationship between LUCC and CS to coordinate regional ecological conservation and industrial development. In this study, the characteristics of spatial and temporal changes in land use and CS in the Yanqi Basin from 2000 to 2020 were revealed using the PLUS (patch-generating land use simulation) model and the CS module of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model. This study also predicted the spatial and temporal evolution of CS and the response mechanism of the Yanqi Basin from four scenarios—natural development scenario (NDS), ecological protection scenario (EPS), cropland protection scenario (CPS), and urban development scenario (UDS) for the years 2030, 2040, and 2050. This study shows the following: (1) Between 2000 and 2020, the Yanqi Basin witnessed an expansion in cropland and construction land, the order of the land use dynamic degree which is as follows: construction land > cropland > woodland > unused land > water > grassland. At the same time, the CS exhibited a trend of growth that was followed by a decline, a cumulative decrease of 3.61 Tg. (2) Between 2020 and 2050, woodland, grassland, and unused land decreased under the NDS and UDS. Meanwhile, grassland and woodland showed an expanding trend, and there was a decrease in cropland and construction land under the EPS; the CPS projected an increase in cropland to 3258.06 km2 by 2050. (3) CS under the UDS is always the lowest, and CS under the EPS is the highest; moreover, by 2050, CS under the EPS is projected to increase by 1.18 Tg compared with that under the UDS. The spatial distribution of CS shows a high value in the western part of the region and a low value in the eastern part of the region, which is more in line with the historical spatial distribution. (4) The development of land by human activities is one of the major factors leading to the change of CS. The direct cause of the decrease in CS is the transformation of large areas of cropland and woodland into construction land. Therefore, woodlands must be protected to improve CS and prevent ecological degradation. At the same time, future land use planning in the Yanqi Basin needs to limit the conversion rate of various types of land, control the construction land, optimize the urban pattern, improve the regional CS level, adhere to the concept of striving to achieve carbon neutrality, and realize the sustainable development of the region to provide scientific suggestions for carrying out macro-decision making regarding land use planning in arid areas.
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Open AccessArticle
Digital Footprint as a Public Participatory Tool: Identifying and Assessing Industrial Heritage Landscape through User-Generated Content on Social Media
by
Ji Li, Jinsheng Pan, Qixuan Dou, Fei Fu and Yaling Shi
Land 2024, 13(6), 743; https://doi.org/10.3390/land13060743 - 26 May 2024
Abstract
International heritage management approaches have developed into a more inclusive process wherein public participation is identified as a pivotal tool. Thus, determining how to assess public interests and include the public’s ideas in heritage protection has become a technical issue, but relevant research
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International heritage management approaches have developed into a more inclusive process wherein public participation is identified as a pivotal tool. Thus, determining how to assess public interests and include the public’s ideas in heritage protection has become a technical issue, but relevant research still remains limited. This paper aims to test the digital footprints of social media users as a public participatory tool, with the objectives of identifying industrial heritage landscape attributes and assessing associated values. Targeting the Sanxian industrial heritage landscape of Liangdancheng in China as a case study, in this research the data from user-generated content on social media platforms Ctrip, Weibo, and Meituan were collected and processed with ROST CM 6 and NVivo 12, and content analysis (CA) and importance-performance analysis (IPA) were conducted. Results revealed that the industrial heritage landscape of Liangdancheng encompasses various built, cultural, and natural environmental resources, including both tangible and intangible attributes such as architectural constructions, historic artifacts, cultural events, and plants. These attributes were assessed and categorized into four quadrants of importance–performance characteristics, wherein cultural environmental resources show relatively high performance but built environmental resources need further actions to improve their value perception and interpretation among the public. This research demonstrated that the digital footprints of social media users as a participatory tool can work well in terms of data accessibility, value identification, and public representation, advancing the theoretical framework of Chinese industrial heritage management and global practices.
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(This article belongs to the Special Issue Landscape Governance in the Age of Social Media (Second Edition))
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