Rural areas around developed metropolitan areas continue to attract capital inflows, promoting rural spatial commodification. Taking Shanghai as a case study, this paper analyzes the characteristics of the spatial distribution pattern and the influencing factors of rural spatial commodification (RSC) through kernel density analysis, multiple regression models, and spatial autocorrelation analysis. This study explores four types of RSC at the township scale outside the center of Shanghai: agricultural product-oriented commodification, farm housing commodification, tourism-oriented commodification, and construction land commodification. The results show the following: (1) The four types of RSC show positive spatial correlation, a clear pattern of agglomeration, and an obvious core–edge pattern, with high-density areas distributed in rural areas with specific advantages around metropolitan areas. The distribution of RSC also demonstrates an obvious polarization, forming an uneven distribution pattern. (2) Socio-economic factors, agriculture, transportation location, urbanization, and industrialization are key factors driving RSC. (3) Different types of RSC should be effectively guided at the policy and planning levels according to regional conditions and development stages to enhance the spatial organization of rural regions and achieve the effective revitalization of the countryside surrounding the metropolis.
{"title":"Characterization of Rural Spatial Commodification Patterns around Metropolitan Areas and Analysis of Influential Factors: Case Study in Shanghai","authors":"Yifan Fang, Jing Qiao, Hong Geng","doi":"10.3390/land13081121","DOIUrl":"https://doi.org/10.3390/land13081121","url":null,"abstract":"Rural areas around developed metropolitan areas continue to attract capital inflows, promoting rural spatial commodification. Taking Shanghai as a case study, this paper analyzes the characteristics of the spatial distribution pattern and the influencing factors of rural spatial commodification (RSC) through kernel density analysis, multiple regression models, and spatial autocorrelation analysis. This study explores four types of RSC at the township scale outside the center of Shanghai: agricultural product-oriented commodification, farm housing commodification, tourism-oriented commodification, and construction land commodification. The results show the following: (1) The four types of RSC show positive spatial correlation, a clear pattern of agglomeration, and an obvious core–edge pattern, with high-density areas distributed in rural areas with specific advantages around metropolitan areas. The distribution of RSC also demonstrates an obvious polarization, forming an uneven distribution pattern. (2) Socio-economic factors, agriculture, transportation location, urbanization, and industrialization are key factors driving RSC. (3) Different types of RSC should be effectively guided at the policy and planning levels according to regional conditions and development stages to enhance the spatial organization of rural regions and achieve the effective revitalization of the countryside surrounding the metropolis.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Linlin Wang, Zixin Zhou, Yi Chen, Liangen Zeng, Linlin Dai
Digital inclusive finance (DIF) is a strategic tool that fosters the green transformation of the industrial economy. Based on the data from the 11 provinces and municipalities in the Yangtze River Economic Belt of China between 2012 and 2021, This paper utilizes the Tobit, intermediary effect, and threshold effect models to empirically study the impact of DIF on the industrial land carbon emission intensity (ILCEI). This paper reaches the following conclusions: (1) The ILCEI in the region revealed a downward trend during the study period. There are substantial differences in carbon ILCEI; higher upstream and lower downstream. The average ILCEI in the lower reach provinces is 0.5829 ton/m2 during the research period, while that in the upper reach region is 1.0104 ton/m2. (2) DIF has a significantly inhibitory effect on the ILCEI; this effect has nonlinear characteristics. The impact of DIF on ILCEI exhibits a marginally diminishing trend as the industrial land economic agglomeration degree improves. (3) Regarding the transmission mechanism, the level of industrial R&D investment plays a primary intermediary role in the impact of DIF on ILCEI. (4) Concerning control variables, foreign investment dependence and trade contribute significantly to inhibiting ILCEI. Lastly, this paper proposes a series of measures to promote DIF to fully utilize the emission reduction effect. The research outcomes have substantial implications for the sustainable development of industrial land.
{"title":"How Does Digital Inclusive Finance Policy Affect the Carbon Emission Intensity of Industrial Land in the Yangtze River Economic Belt of China? Evidence from Intermediary and Threshold Effects","authors":"Linlin Wang, Zixin Zhou, Yi Chen, Liangen Zeng, Linlin Dai","doi":"10.3390/land13081127","DOIUrl":"https://doi.org/10.3390/land13081127","url":null,"abstract":"Digital inclusive finance (DIF) is a strategic tool that fosters the green transformation of the industrial economy. Based on the data from the 11 provinces and municipalities in the Yangtze River Economic Belt of China between 2012 and 2021, This paper utilizes the Tobit, intermediary effect, and threshold effect models to empirically study the impact of DIF on the industrial land carbon emission intensity (ILCEI). This paper reaches the following conclusions: (1) The ILCEI in the region revealed a downward trend during the study period. There are substantial differences in carbon ILCEI; higher upstream and lower downstream. The average ILCEI in the lower reach provinces is 0.5829 ton/m2 during the research period, while that in the upper reach region is 1.0104 ton/m2. (2) DIF has a significantly inhibitory effect on the ILCEI; this effect has nonlinear characteristics. The impact of DIF on ILCEI exhibits a marginally diminishing trend as the industrial land economic agglomeration degree improves. (3) Regarding the transmission mechanism, the level of industrial R&D investment plays a primary intermediary role in the impact of DIF on ILCEI. (4) Concerning control variables, foreign investment dependence and trade contribute significantly to inhibiting ILCEI. Lastly, this paper proposes a series of measures to promote DIF to fully utilize the emission reduction effect. The research outcomes have substantial implications for the sustainable development of industrial land.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alessio Patriarca, Eros Caputi, Lorenzo Gatti, E. Marcheggiani, F. Recanatesi, Carlo Maria Rossi, M. Ripa
Small landscape features (i.e., trees outside forest, small woody features) and linear vegetation such as hedgerows, riparian vegetation, and green lanes are vital ecological structures in agroecosystems, enhancing the biodiversity, landscape diversity, and protecting water bodies. Therefore, their monitoring is fundamental to assessing a specific territory’s arrangement and verifying the effectiveness of strategies and financial measures activated at the local or European scale. The size of these elements and territorial distribution make their identification extremely complex without specific survey campaigns; in particular, remote monitoring requires data of considerable resolution and, therefore, is very costly. This paper proposes a methodology to map these features using a combination of open-source or low-cost high-resolution orthophotos (RGB), which are typically available to local administrators and are object-oriented classification methods. Additionally, multispectral satellite images from the Sentinel-2 platform were utilized to further characterize the identified elements. The produced map, compared with the other existing layers, provided better results than other maps at the European scale. Therefore, the developed method is highly effective for the remote and wide-scale assessment of SWFs, making it a crucial tool for defining and monitoring development policies in rural environments.
{"title":"Wide-Scale Identification of Small Woody Features of Landscape from Remote Sensing","authors":"Alessio Patriarca, Eros Caputi, Lorenzo Gatti, E. Marcheggiani, F. Recanatesi, Carlo Maria Rossi, M. Ripa","doi":"10.3390/land13081128","DOIUrl":"https://doi.org/10.3390/land13081128","url":null,"abstract":"Small landscape features (i.e., trees outside forest, small woody features) and linear vegetation such as hedgerows, riparian vegetation, and green lanes are vital ecological structures in agroecosystems, enhancing the biodiversity, landscape diversity, and protecting water bodies. Therefore, their monitoring is fundamental to assessing a specific territory’s arrangement and verifying the effectiveness of strategies and financial measures activated at the local or European scale. The size of these elements and territorial distribution make their identification extremely complex without specific survey campaigns; in particular, remote monitoring requires data of considerable resolution and, therefore, is very costly. This paper proposes a methodology to map these features using a combination of open-source or low-cost high-resolution orthophotos (RGB), which are typically available to local administrators and are object-oriented classification methods. Additionally, multispectral satellite images from the Sentinel-2 platform were utilized to further characterize the identified elements. The produced map, compared with the other existing layers, provided better results than other maps at the European scale. Therefore, the developed method is highly effective for the remote and wide-scale assessment of SWFs, making it a crucial tool for defining and monitoring development policies in rural environments.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Manqing Yao, Deshun Zhang, Yingying Chen, Yujia Liu, M. Elsadek
In recent decades, the increasing frequency of urban fires, driven by urban functional enhancements and climate change, has posed a growing threat to metropolitan sustainability. This study investigates the temporal and spatial characteristics of fire incidents in Shanghai from 2019 to 2023. Using satellite fire point data and official government records, kernel density analysis and wavelet analysis were employed to analyze the time series and spatial distribution of fire data. Subsequently, eleven primary factors influencing urban fire occurrence were identified, encompassing probability, regional characteristics, and hazard sources. A combined methodology of subjective and objective weights with game theory was used to generate a fire risk assessment at a 1 × 1 km2 grid scale. Furthermore, the spatial distribution characteristics of the assessments were analyzed. The results reveal that the downtown area exhibits the highest intensity of urban fires in terms of spatial domain, with a decreasing intensity towards the suburbs. Temporally, fire frequency demonstrates significant periodicity at an 18a time scale, while clear seasonal fluctuations and periodicity are observed at a 16-22a time scale, with higher occurrences in spring and winter. The study identifies typical aggregation patterns of urban fires, with high-risk centers in downtown Shanghai. Considering the impact of climate change and human activities, high-risk areas may gradually expand to adjacent urban suburbs, presenting a concerning future scenario. By examining the dual attributes of “combustibles and fireproof space” within urban greening systems, this research offers recommendations for the future strategies of disaster prevention and mitigation of green systems in Shanghai.
{"title":"Urban Fire Risk Dynamics and Mitigation Strategies in Shanghai: Integrating Spatial Analysis and Game Theory","authors":"Manqing Yao, Deshun Zhang, Yingying Chen, Yujia Liu, M. Elsadek","doi":"10.3390/land13081125","DOIUrl":"https://doi.org/10.3390/land13081125","url":null,"abstract":"In recent decades, the increasing frequency of urban fires, driven by urban functional enhancements and climate change, has posed a growing threat to metropolitan sustainability. This study investigates the temporal and spatial characteristics of fire incidents in Shanghai from 2019 to 2023. Using satellite fire point data and official government records, kernel density analysis and wavelet analysis were employed to analyze the time series and spatial distribution of fire data. Subsequently, eleven primary factors influencing urban fire occurrence were identified, encompassing probability, regional characteristics, and hazard sources. A combined methodology of subjective and objective weights with game theory was used to generate a fire risk assessment at a 1 × 1 km2 grid scale. Furthermore, the spatial distribution characteristics of the assessments were analyzed. The results reveal that the downtown area exhibits the highest intensity of urban fires in terms of spatial domain, with a decreasing intensity towards the suburbs. Temporally, fire frequency demonstrates significant periodicity at an 18a time scale, while clear seasonal fluctuations and periodicity are observed at a 16-22a time scale, with higher occurrences in spring and winter. The study identifies typical aggregation patterns of urban fires, with high-risk centers in downtown Shanghai. Considering the impact of climate change and human activities, high-risk areas may gradually expand to adjacent urban suburbs, presenting a concerning future scenario. By examining the dual attributes of “combustibles and fireproof space” within urban greening systems, this research offers recommendations for the future strategies of disaster prevention and mitigation of green systems in Shanghai.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Studying changes in land use per capita is critical for understanding the interactions between humans and ecosystems, and for modeling the impacts of land use changes on climate systems. However, many uncertainties in historical estimates significantly hinder climate modeling. This study estimated the per capita cropland area in traditional agricultural regions of China over the past millennium using historical-document-based and modern statistical cropland and population data. The findings showed that changes in the per capita cropland area in the provinces of the middle and lower reaches of the Yellow River could be characterized into three stages: slow decrease, rapid increase, and fluctuating decrease, whereas, in the provinces of the middle and lower reaches of the Yangtze River, there was a continuous decrease. Spatially, the per capita cropland area was higher in the middle and lower reaches of the Yellow River and lower in the middle and lower reaches of the Yangtze River during the study period. The per capita cropland areas showed clear differences in the HYDE dataset and our study; the corresponding values of our study were 2.1–8.0, 1.7–8.2, and 1.6–8.8 times higher than those from the HYDE dataset for the early Song, Yuan, and Ming dynasties, respectively.
{"title":"Per Capita Cropland Estimations for Traditional Agricultural Areas of China over Past Millennium","authors":"Meijiao Li, Fanneng He, Fan Yang, Ruifei Hao","doi":"10.3390/land13081122","DOIUrl":"https://doi.org/10.3390/land13081122","url":null,"abstract":"Studying changes in land use per capita is critical for understanding the interactions between humans and ecosystems, and for modeling the impacts of land use changes on climate systems. However, many uncertainties in historical estimates significantly hinder climate modeling. This study estimated the per capita cropland area in traditional agricultural regions of China over the past millennium using historical-document-based and modern statistical cropland and population data. The findings showed that changes in the per capita cropland area in the provinces of the middle and lower reaches of the Yellow River could be characterized into three stages: slow decrease, rapid increase, and fluctuating decrease, whereas, in the provinces of the middle and lower reaches of the Yangtze River, there was a continuous decrease. Spatially, the per capita cropland area was higher in the middle and lower reaches of the Yellow River and lower in the middle and lower reaches of the Yangtze River during the study period. The per capita cropland areas showed clear differences in the HYDE dataset and our study; the corresponding values of our study were 2.1–8.0, 1.7–8.2, and 1.6–8.8 times higher than those from the HYDE dataset for the early Song, Yuan, and Ming dynasties, respectively.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sara Favargiotti, Giulia Zantedeschi, Angelica Pianegonda, Matteo Brunelli, Michele Urbani
Logistics, distribution models, and landscapes of food production strongly influence the space of our cities and territories. In addition to the network of large-scale retail distribution that is diffused in urban and non-urban areas, with this contribution, we study the presence of new forms of the local and sustainable distribution of food (such as Alternative Food Networks, and community-supported agriculture). Studying and understanding how these distribution models can support and be integrated within a landscape planning and design approach is explored through the Analytic Hierarchy Process (AHP), a multi-criteria decision analysis method. Through the specific focus of a Food Hub localization, the aim is to demonstrate how distribution models can not only support but also integrate into landscape planning and design. The fundamental objectives for structuring and locating a Food Hub can be organized under three strategic objectives: pursuing the benefit of people, the planet, and profit. The choice of one distribution method over others, or what is the best location and condition for distribution centers, is the question we have tested with the collaboration of “L’Ortazzo” Association. The case study is a solidarity purchasing group located in the upper Valsugana valley area (Trentino Region, Italy), a supra-municipality reality involving about a hundred families that, currently, do not have a physical distribution center.
{"title":"Designing Food Hubs for Territories of Proximity: Assessing the Spatial, Ecological, and Cultural Potentials of Places through Multi-Criteria Decision Support Systems","authors":"Sara Favargiotti, Giulia Zantedeschi, Angelica Pianegonda, Matteo Brunelli, Michele Urbani","doi":"10.3390/land13081131","DOIUrl":"https://doi.org/10.3390/land13081131","url":null,"abstract":"Logistics, distribution models, and landscapes of food production strongly influence the space of our cities and territories. In addition to the network of large-scale retail distribution that is diffused in urban and non-urban areas, with this contribution, we study the presence of new forms of the local and sustainable distribution of food (such as Alternative Food Networks, and community-supported agriculture). Studying and understanding how these distribution models can support and be integrated within a landscape planning and design approach is explored through the Analytic Hierarchy Process (AHP), a multi-criteria decision analysis method. Through the specific focus of a Food Hub localization, the aim is to demonstrate how distribution models can not only support but also integrate into landscape planning and design. The fundamental objectives for structuring and locating a Food Hub can be organized under three strategic objectives: pursuing the benefit of people, the planet, and profit. The choice of one distribution method over others, or what is the best location and condition for distribution centers, is the question we have tested with the collaboration of “L’Ortazzo” Association. The case study is a solidarity purchasing group located in the upper Valsugana valley area (Trentino Region, Italy), a supra-municipality reality involving about a hundred families that, currently, do not have a physical distribution center.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The present study reflects on spontaneous nature’s agency to reclaim abandoned urban areas in Italian urban brownfields, providing a focused analysis of the Metropolitan Area of Milan. These spaces are the products of phenomena, such as deindustrialization, demilitarization, and uncontrolled urban expansion, which have produced a compromised heritage and challenges to regeneration. Such abandonment sometimes produces new forms of urban nature, which suggests a possible path for ecological regeneration and coexistence, as affirmed by the multidisciplinary literature. The related informal urban biodiversity grows regardless of future planning provisions, triggering unexpected transformations of the urban environment and producing socio-ecological value, as demonstrated by citizens’ recognition of these places. The present study maps informal urban biodiversity in the Milan territory, identifying the presence of large contaminated sites, relevant urban voids, vacant lots, and former agricultural spaces. This study also reflects on possible paths for urban planning and policies to integrate informal urban biodiversity within the urban ecological structure by analyzing the main features and challenges of the corresponding regeneration processes.
{"title":"Informal Urban Biodiversity in the Milan Metropolitan Area: The Role of Spontaneous Nature in the Leftover Regeneration Process","authors":"Lucia Ludovici, Maria Chiara Pastore","doi":"10.3390/land13081123","DOIUrl":"https://doi.org/10.3390/land13081123","url":null,"abstract":"The present study reflects on spontaneous nature’s agency to reclaim abandoned urban areas in Italian urban brownfields, providing a focused analysis of the Metropolitan Area of Milan. These spaces are the products of phenomena, such as deindustrialization, demilitarization, and uncontrolled urban expansion, which have produced a compromised heritage and challenges to regeneration. Such abandonment sometimes produces new forms of urban nature, which suggests a possible path for ecological regeneration and coexistence, as affirmed by the multidisciplinary literature. The related informal urban biodiversity grows regardless of future planning provisions, triggering unexpected transformations of the urban environment and producing socio-ecological value, as demonstrated by citizens’ recognition of these places. The present study maps informal urban biodiversity in the Milan territory, identifying the presence of large contaminated sites, relevant urban voids, vacant lots, and former agricultural spaces. This study also reflects on possible paths for urban planning and policies to integrate informal urban biodiversity within the urban ecological structure by analyzing the main features and challenges of the corresponding regeneration processes.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Environmental and design factors determine the stormwater management capacity of green roofs; however, the design and environmental factors that impact their hydrological performance in subtropical humid regions are poorly understood. In particular, meteorological factors have received little attention. Meteorological factors vary greatly at different stages of a rainfall event (e.g., during the rainfall and outflow). Therefore, the impact of meteorological factors at different stages on hydrological performance should be considered separately to obtain a more accurate picture of their effects on hydrological performance. In this study, experimental green roofs were established based on four substrate types and two depths. For the first time, this study systematically explored the effects of design factors for the substrate (type and depth) and multi-stage environmental factors on the hydrological performance of green roofs. Environmental factors, including meteorological factors, from three critical stages (before and during a rainfall event and during the outflow), and rainfall characteristics (e.g., rainfall depth and rainfall duration) were incorporated to determine the variation in hydrological performance. The effects of multi-stage environmental factors on retention and peak reduction were analyzed, with a ranking of each factor’s relative importance. Environmental factors played a leading role in determining hydrological performance. However, the impact of multi-stage environmental factors was not as important as that of rainfall depth and antecedent volumetric water content. Differences in hydrological performance were compared across combinations of design factors. No significant differences were observed across substrate types and depths. However, potential interactive effects might exist, though these were not significant compared to environmental factors (e.g., rainfall depth and rainfall duration). These results confirmed that the meteorological factors in the different event-related stages significantly impacted the hydrological performance. Quantifying the effects of design and environmental factors is critical for hydrological performance evaluation. The results provided a broader perspective on understanding influence mechanisms of hydrological performance and highlighted the impact of microclimates on hydrological performance.
{"title":"Effects of Design Factors and Multi-Stage Environmental Factors on Hydrological Performance of Subtropical Green Roofs","authors":"Zhongtang Liao, Jialin Liu, Yufei Li","doi":"10.3390/land13081129","DOIUrl":"https://doi.org/10.3390/land13081129","url":null,"abstract":"Environmental and design factors determine the stormwater management capacity of green roofs; however, the design and environmental factors that impact their hydrological performance in subtropical humid regions are poorly understood. In particular, meteorological factors have received little attention. Meteorological factors vary greatly at different stages of a rainfall event (e.g., during the rainfall and outflow). Therefore, the impact of meteorological factors at different stages on hydrological performance should be considered separately to obtain a more accurate picture of their effects on hydrological performance. In this study, experimental green roofs were established based on four substrate types and two depths. For the first time, this study systematically explored the effects of design factors for the substrate (type and depth) and multi-stage environmental factors on the hydrological performance of green roofs. Environmental factors, including meteorological factors, from three critical stages (before and during a rainfall event and during the outflow), and rainfall characteristics (e.g., rainfall depth and rainfall duration) were incorporated to determine the variation in hydrological performance. The effects of multi-stage environmental factors on retention and peak reduction were analyzed, with a ranking of each factor’s relative importance. Environmental factors played a leading role in determining hydrological performance. However, the impact of multi-stage environmental factors was not as important as that of rainfall depth and antecedent volumetric water content. Differences in hydrological performance were compared across combinations of design factors. No significant differences were observed across substrate types and depths. However, potential interactive effects might exist, though these were not significant compared to environmental factors (e.g., rainfall depth and rainfall duration). These results confirmed that the meteorological factors in the different event-related stages significantly impacted the hydrological performance. Quantifying the effects of design and environmental factors is critical for hydrological performance evaluation. The results provided a broader perspective on understanding influence mechanisms of hydrological performance and highlighted the impact of microclimates on hydrological performance.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Analysis of the driving mechanisms of wetland change can help identify spatial differences in the mechanisms affecting various elements, enabling a more scientific approach to the conservation and utilization of wetlands. This study investigated the impacts of natural and anthropogenic factors on the spatiotemporal evolution of the Altay and Greater and Lesser Khingan Mountains areas using Landsat satellite image data from 1980 to 2018 and fieldwork data from 2019 to 2020. A transfer matrix, correlation analysis, and dynamic characteristics were applied to calculate and analyze the transformation types and areas of wetland resources across all consecutive periods. Finally, the dominant factors influencing the spatiotemporal evolution of the wetland were explored and revealed using the drought index (Standardized Precipitation Index, SPEI) and statistical almanacs. The results showed: (1) From 1980 to 2018, the wetlands area in the Altay Mountains exhibited a decreasing trend, whereas the wetlands area in the Greater and Lesser Khingan Mountains showed an increasing trend. The primary type of wetland transfer in the Altay Mountains was grassland, whereas in the Greater and Lesser Khingan Mountains regions, the primary types of wetland transfer were grassland and forestland. The wetlands area transferred out of the Altay Mountain region was larger than the area of wetland types transferred into during 2010–2018, whereas the wetland areas of the Greater and Lesser Khingan Mountain areas showed the opposite trend. (2) From 1980 to 2018, the wetland ecosystem types in the Altay Mountains exhibited the highest dynamic and conversion degrees of the channels. Similarly, the mountain areas of the Greater Khingan Mountains showed the highest dynamic and conversion degrees of marshes and channels among the wetland types. In addition, the mountainous areas of the Lesser Khingan Mountains showed the highest dynamic and conversion degrees for reservoirs and rivers. (3) Natural driving factor analysis revealed that the SPEI values in the Altay Mountains and the Greater and Lesser Khingan Mountains areas exhibited an increasing trend, indicating that the climate has been warm and humid over the past 30 years and that the expansion of cropland and human-made wetland areas has been significantly influenced by human activities. Therefore, the wetland areas of the Greater and Lesser Khingan Mountains in the northeast are strongly influenced by human activities, whereas the wetland in the Altay Mountains in the northwest is strongly influenced by the climate.
{"title":"Characteristics of Changes in Typical Mountain Wetlands in the Middle and High Latitudes of China over the Past 30 Years","authors":"Nana Luo, Rui Yu, B. Wen","doi":"10.3390/land13081124","DOIUrl":"https://doi.org/10.3390/land13081124","url":null,"abstract":"Analysis of the driving mechanisms of wetland change can help identify spatial differences in the mechanisms affecting various elements, enabling a more scientific approach to the conservation and utilization of wetlands. This study investigated the impacts of natural and anthropogenic factors on the spatiotemporal evolution of the Altay and Greater and Lesser Khingan Mountains areas using Landsat satellite image data from 1980 to 2018 and fieldwork data from 2019 to 2020. A transfer matrix, correlation analysis, and dynamic characteristics were applied to calculate and analyze the transformation types and areas of wetland resources across all consecutive periods. Finally, the dominant factors influencing the spatiotemporal evolution of the wetland were explored and revealed using the drought index (Standardized Precipitation Index, SPEI) and statistical almanacs. The results showed: (1) From 1980 to 2018, the wetlands area in the Altay Mountains exhibited a decreasing trend, whereas the wetlands area in the Greater and Lesser Khingan Mountains showed an increasing trend. The primary type of wetland transfer in the Altay Mountains was grassland, whereas in the Greater and Lesser Khingan Mountains regions, the primary types of wetland transfer were grassland and forestland. The wetlands area transferred out of the Altay Mountain region was larger than the area of wetland types transferred into during 2010–2018, whereas the wetland areas of the Greater and Lesser Khingan Mountain areas showed the opposite trend. (2) From 1980 to 2018, the wetland ecosystem types in the Altay Mountains exhibited the highest dynamic and conversion degrees of the channels. Similarly, the mountain areas of the Greater Khingan Mountains showed the highest dynamic and conversion degrees of marshes and channels among the wetland types. In addition, the mountainous areas of the Lesser Khingan Mountains showed the highest dynamic and conversion degrees for reservoirs and rivers. (3) Natural driving factor analysis revealed that the SPEI values in the Altay Mountains and the Greater and Lesser Khingan Mountains areas exhibited an increasing trend, indicating that the climate has been warm and humid over the past 30 years and that the expansion of cropland and human-made wetland areas has been significantly influenced by human activities. Therefore, the wetland areas of the Greater and Lesser Khingan Mountains in the northeast are strongly influenced by human activities, whereas the wetland in the Altay Mountains in the northwest is strongly influenced by the climate.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accessibility is closely related to residents’ well-being and quality of life and is a potential indicator of social equity. This study aims to present a methodology for assessing the combined equity of living service amenities (LSAs) based on accessibility. This study focuses on fourteen types of LSAs in six dimensions and improves the three-step floating catchment area (3SFCA) model by considering the behavioral demand characteristics of different age groups. Taking the main built-up area of Xi’an as an example, the modified 3SFCA model is applied to assess the accessibility of LSAs, and the supply–demand index is used to measure the supply and demand level of the horizontal dimension. Furthermore, random forest regression was used to screen the key socioeconomic indicators affecting the accessibility of LSAs, and then the binary spatial correlation local index was used to reveal the spatial distribution characteristics between LSA accessibility and key socioeconomic indicators in the vertical dimension. Finally, the comprehensive equity of LSAs is evaluated by space superposition. The results showed that there was a serious imbalance between the supply and demand of LSAs in Xi’an’s main built-up area, with polarized oversupply and weak supply areas, especially for accessibility to low-grade LSAs. Accessibility is relatively low for children and young and middle-aged groups, and intergenerational inequalities were particularly pronounced among them. The lower-income group was generally at a disadvantage in accessing the high-demand amenities, and those who resided in affordable housing in the periphery of the city were more likely to face social exclusion. This study emphasizes the importance of distributing urban resources equitably among different social groups, which can help decision makers achieve a balance between horizontal equity and vertical equity in the allocation of urban LSAs and promote spatial equity and sustainable social development.
{"title":"Horizontal and Vertical Spatial Equity Analysis Based on Accessibility to Living Service Amenities: A Case Study of Xi’an, China","authors":"Tongtong Li, Xinrui Fang, Jiaqi Zhu, Qianliu Peng, Wenyu Zhao, Xin Fu","doi":"10.3390/land13081113","DOIUrl":"https://doi.org/10.3390/land13081113","url":null,"abstract":"Accessibility is closely related to residents’ well-being and quality of life and is a potential indicator of social equity. This study aims to present a methodology for assessing the combined equity of living service amenities (LSAs) based on accessibility. This study focuses on fourteen types of LSAs in six dimensions and improves the three-step floating catchment area (3SFCA) model by considering the behavioral demand characteristics of different age groups. Taking the main built-up area of Xi’an as an example, the modified 3SFCA model is applied to assess the accessibility of LSAs, and the supply–demand index is used to measure the supply and demand level of the horizontal dimension. Furthermore, random forest regression was used to screen the key socioeconomic indicators affecting the accessibility of LSAs, and then the binary spatial correlation local index was used to reveal the spatial distribution characteristics between LSA accessibility and key socioeconomic indicators in the vertical dimension. Finally, the comprehensive equity of LSAs is evaluated by space superposition. The results showed that there was a serious imbalance between the supply and demand of LSAs in Xi’an’s main built-up area, with polarized oversupply and weak supply areas, especially for accessibility to low-grade LSAs. Accessibility is relatively low for children and young and middle-aged groups, and intergenerational inequalities were particularly pronounced among them. The lower-income group was generally at a disadvantage in accessing the high-demand amenities, and those who resided in affordable housing in the periphery of the city were more likely to face social exclusion. This study emphasizes the importance of distributing urban resources equitably among different social groups, which can help decision makers achieve a balance between horizontal equity and vertical equity in the allocation of urban LSAs and promote spatial equity and sustainable social development.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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