Davide Marino, Antonio Barone, Angelo Marucci, Silvia Pili, M. Palmieri
Changes in land use and land cover (LULC) are caused by several factors, including climate change, socio-demographic dynamics, human pressures and urban sprawl. These factors alter the structure and functionality of ecosystems and their capacity to provide ecosystem goods and services to society. The study of LULC changes is important for understanding the dynamics of relationships between environmental, social and economic components and for analyzing the factors affecting natural capital. Including ecosystem services (ES) in spatial planning tools and sectoral policies is useful for improving governance. In this paper, the impact of LULC changes on ES provision has been estimated. To this end, we carried out a literature review (Step 1) to select the biophysical and economic coefficients of ES supply by land cover classes and collect them in a database (Step 2). We subsequently aggregated the economic and biophysical coefficients by macro classes (Step 3) and, using the benefit transfer approach, we estimated the change in the supply of ESs concerning permanence and transition phenomena in Italy from 1990 to 2018 (Step 4). The transition phenomena analysis also allowed us to evaluate the consequences of urbanization and urban green space governance on ES supply. Indeed, these urban green spaces can help reduce risks to people’s health and safety and mitigate the effects induced by climate change. In total, approximately 800 coefficients (biophysical and economic) of ESs supplied by Corine Land Cover classes were acquired. The results show a reduction in the annual supply of ecosystem services of EUR 927 million (2022) caused by LULC changes between 1990 and 2018. This research proposes a methodology to improve knowledge of ESs concerning anthropogenic impacts and to support land-use planning policies regarding Agenda 2030 for Sustainable Development Goals.
{"title":"Impact of Land Use Changes on Ecosystem Services Supply: A Meta Analysis of the Italian Context","authors":"Davide Marino, Antonio Barone, Angelo Marucci, Silvia Pili, M. Palmieri","doi":"10.3390/land12122173","DOIUrl":"https://doi.org/10.3390/land12122173","url":null,"abstract":"Changes in land use and land cover (LULC) are caused by several factors, including climate change, socio-demographic dynamics, human pressures and urban sprawl. These factors alter the structure and functionality of ecosystems and their capacity to provide ecosystem goods and services to society. The study of LULC changes is important for understanding the dynamics of relationships between environmental, social and economic components and for analyzing the factors affecting natural capital. Including ecosystem services (ES) in spatial planning tools and sectoral policies is useful for improving governance. In this paper, the impact of LULC changes on ES provision has been estimated. To this end, we carried out a literature review (Step 1) to select the biophysical and economic coefficients of ES supply by land cover classes and collect them in a database (Step 2). We subsequently aggregated the economic and biophysical coefficients by macro classes (Step 3) and, using the benefit transfer approach, we estimated the change in the supply of ESs concerning permanence and transition phenomena in Italy from 1990 to 2018 (Step 4). The transition phenomena analysis also allowed us to evaluate the consequences of urbanization and urban green space governance on ES supply. Indeed, these urban green spaces can help reduce risks to people’s health and safety and mitigate the effects induced by climate change. In total, approximately 800 coefficients (biophysical and economic) of ESs supplied by Corine Land Cover classes were acquired. The results show a reduction in the annual supply of ecosystem services of EUR 927 million (2022) caused by LULC changes between 1990 and 2018. This research proposes a methodology to improve knowledge of ESs concerning anthropogenic impacts and to support land-use planning policies regarding Agenda 2030 for Sustainable Development Goals.","PeriodicalId":37702,"journal":{"name":"Land","volume":"54 2","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138967092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The diamondback terrapin (Malaclemys terrapin), a brackish water turtle species native to the eastern United States, is under “special concern” in the state of New Jersey, due to decreasing habitat from development and changing climatic conditions. Diamondback terrapins reside in saline marshes and coastal wetlands and nest in sandy substrate, primarily beaches and dunes, in June and July. New Jersey is vulnerable to sea level rise, leaving diamondback terrapin habitats and nesting areas at risk of inundation under future climate scenarios, and, as the most densely populated state, subject to continual development pressures on potentially conservable land. Changing sea levels and climatic conditions will cause accretion and migration of marshes into open grassy land, yielding new potential terrapin habitats, though changing temperatures could affect the availability of male-producing nesting sites and impact potential nesting patterns. This study spatially modeled lost, gained, and changed habitat and nesting areas under sea level rise scenarios for 2050 and 2100 in New Jersey and quantified these by municipality to offer insights into potential conservable land that may mitigate these changes for the vulnerable species. The results indicate an overall decrease in potential habitat coupled with a decrease in both overall and male-producing nesting ranges.
{"title":"Estimating Changing Marshland Habitat and Conservation Potential for Diamondback Terrapins (Malaclemys terrapin) in New Jersey under Climate Change","authors":"Jacqueline R. Ganter, Zachary Christman","doi":"10.3390/land12122170","DOIUrl":"https://doi.org/10.3390/land12122170","url":null,"abstract":"The diamondback terrapin (Malaclemys terrapin), a brackish water turtle species native to the eastern United States, is under “special concern” in the state of New Jersey, due to decreasing habitat from development and changing climatic conditions. Diamondback terrapins reside in saline marshes and coastal wetlands and nest in sandy substrate, primarily beaches and dunes, in June and July. New Jersey is vulnerable to sea level rise, leaving diamondback terrapin habitats and nesting areas at risk of inundation under future climate scenarios, and, as the most densely populated state, subject to continual development pressures on potentially conservable land. Changing sea levels and climatic conditions will cause accretion and migration of marshes into open grassy land, yielding new potential terrapin habitats, though changing temperatures could affect the availability of male-producing nesting sites and impact potential nesting patterns. This study spatially modeled lost, gained, and changed habitat and nesting areas under sea level rise scenarios for 2050 and 2100 in New Jersey and quantified these by municipality to offer insights into potential conservable land that may mitigate these changes for the vulnerable species. The results indicate an overall decrease in potential habitat coupled with a decrease in both overall and male-producing nesting ranges.","PeriodicalId":37702,"journal":{"name":"Land","volume":"67 10","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138998575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yannick Useni Sikuzani, Médard Mpanda Mukenza, Héritier Khoji Muteya, Nadège Cirezi Cizungu, François Malaisse, Jan Bogaert
In the Lubumbashi charcoal production basin (LCPB) in Southeastern DR Congo, agricultural and charcoal production activities regularly give rise to fires that lead to considerable degradation of the miombo open forest. This study analyzes the drivers of the spatiotemporal distribution of active fires and burnt areas in the LCPB by processing MODIS and Landsat data. In addition, a kernel density analysis method (KDE) was used to estimate fire risk, while the effect of the road network and dwellings on vegetation fires was highlighted in areas between a 0 and 3000 m radius. The obtained results revealed that fires in the LCPB generally occur between April and November, mainly during the day, between 11 a.m. and 12 p.m. These fires are concentrated in the central and southwestern part of the LCPB, more specifically in the savannahs and near roads. From 2002 to 2022, an average of 11,237 active fires and an average of 6337 km2 of burnt areas were recorded in the LCPB. Each year, these fires peak in August, and despite their steady decline, the few fires that have affected the forests have caused more devastation (more than 2790 km2/year) than those observed in the fields and savannah. These figures highlight the imperative need to put in place fire prevention and management measures in the LCPB, with particular emphasis on awareness, monitoring, and fire-fighting measures.
{"title":"Vegetation Fires in the Lubumbashi Charcoal Production Basin (The Democratic Republic of the Congo): Drivers, Extent and Spatiotemporal Dynamics","authors":"Yannick Useni Sikuzani, Médard Mpanda Mukenza, Héritier Khoji Muteya, Nadège Cirezi Cizungu, François Malaisse, Jan Bogaert","doi":"10.3390/land12122171","DOIUrl":"https://doi.org/10.3390/land12122171","url":null,"abstract":"In the Lubumbashi charcoal production basin (LCPB) in Southeastern DR Congo, agricultural and charcoal production activities regularly give rise to fires that lead to considerable degradation of the miombo open forest. This study analyzes the drivers of the spatiotemporal distribution of active fires and burnt areas in the LCPB by processing MODIS and Landsat data. In addition, a kernel density analysis method (KDE) was used to estimate fire risk, while the effect of the road network and dwellings on vegetation fires was highlighted in areas between a 0 and 3000 m radius. The obtained results revealed that fires in the LCPB generally occur between April and November, mainly during the day, between 11 a.m. and 12 p.m. These fires are concentrated in the central and southwestern part of the LCPB, more specifically in the savannahs and near roads. From 2002 to 2022, an average of 11,237 active fires and an average of 6337 km2 of burnt areas were recorded in the LCPB. Each year, these fires peak in August, and despite their steady decline, the few fires that have affected the forests have caused more devastation (more than 2790 km2/year) than those observed in the fields and savannah. These figures highlight the imperative need to put in place fire prevention and management measures in the LCPB, with particular emphasis on awareness, monitoring, and fire-fighting measures.","PeriodicalId":37702,"journal":{"name":"Land","volume":"2 6","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138996736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The COVID-19 lockdown has deepened inequity among vulnerable groups, such as the elderly. Reducing inequity in access to essential service facilities is an effective way to improve community resilience in dealing with pandemics. In this research, three indexes were created to measure community resilience in accessing essential services. Specifically, we have considered the different walking capacity and different needs of the elderly and the general population. We selected Shanghai as the case for our research and analyzed the spatial patterns of both space-based and population-based essential service facilities. The Lorenz curve and the Gini coefficient were used to measure the spatial equity. And, we attempted to reveal the relationships between the population density and three indexes through bivariate Local Indicators of Spatial Association. The results suggest that the Diversity Index enjoys the highest equity, followed by the Demand Accessibility Index, and the equity of the Per Capita Quantity Index is the lowest. Furthermore, the accessibility of essential services in urban areas is excellent, while in some suburban areas it is low. Our findings contribute valuable scientific insights for policy makers to strengthen community resilience and address inequities for immediate or long-term measures.
{"title":"Community Resilience in Accessing Essential Service Facilities Considering Equity and Aging Demand: A Case of Shanghai, China","authors":"Xiaohe Zhang, Haixiao Pan","doi":"10.3390/land12122167","DOIUrl":"https://doi.org/10.3390/land12122167","url":null,"abstract":"The COVID-19 lockdown has deepened inequity among vulnerable groups, such as the elderly. Reducing inequity in access to essential service facilities is an effective way to improve community resilience in dealing with pandemics. In this research, three indexes were created to measure community resilience in accessing essential services. Specifically, we have considered the different walking capacity and different needs of the elderly and the general population. We selected Shanghai as the case for our research and analyzed the spatial patterns of both space-based and population-based essential service facilities. The Lorenz curve and the Gini coefficient were used to measure the spatial equity. And, we attempted to reveal the relationships between the population density and three indexes through bivariate Local Indicators of Spatial Association. The results suggest that the Diversity Index enjoys the highest equity, followed by the Demand Accessibility Index, and the equity of the Per Capita Quantity Index is the lowest. Furthermore, the accessibility of essential services in urban areas is excellent, while in some suburban areas it is low. Our findings contribute valuable scientific insights for policy makers to strengthen community resilience and address inequities for immediate or long-term measures.","PeriodicalId":37702,"journal":{"name":"Land","volume":"16 21","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138972368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrew Clark, Craig Shephard, Andrew Robson, Joel McKechnie, R. B. Morrison, Abbie Rankin
As the global population rises, there is an ever-increasing demand for food, in terms of volume, quality and sustainable production. Protected Cropping Structures (PCS) provide controlled farming environments that support the optimum use of crop inputs for plant growth, faster production cycles, multiple growing seasons per annum and increased yield, while offering greater control of pests, disease and adverse weather. Globally, there has been a rapid increase in the adoption of PCS. However, there remains a concerning knowledge gap in the availability of accurate and up-to-date spatial information that defines the extent (location and area) of PCS. This data is fundamental for providing metrics that inform decision making around forward selling, labour, processing and infrastructure requirements, traceability, biosecurity and natural disaster preparedness and response. This project addresses this need, by developing a national map of PCS for Australia using remotely sensed imagery and deep learning analytics, ancillary data, field validation and industry engagement. The resulting map presents the location and extent of all commercial glasshouses, polyhouses, polytunnels, shadehouses and permanent nets with an area of >0.2 ha. The outcomes of the project revealed deep learning techniques can accurately map PCS with models achieving F-Scores > 0.9 and accelerate the mapping where suitable imagery is available. Location-based tools supported by web mapping applications were critical for the validation of PCS locations and for building industry awareness and engagement. The final national PCS map is publicly available through an online dashboard which summarises the area of PCS structures at a range of scales including state/territory, local government area and individual structure. The outcomes of this project have set a global standard on how this level of mapping can be achieved through a collaborative, multifaceted approach.
{"title":"A Multifaceted Approach to Developing an Australian National Map of Protected Cropping Structures","authors":"Andrew Clark, Craig Shephard, Andrew Robson, Joel McKechnie, R. B. Morrison, Abbie Rankin","doi":"10.3390/land12122168","DOIUrl":"https://doi.org/10.3390/land12122168","url":null,"abstract":"As the global population rises, there is an ever-increasing demand for food, in terms of volume, quality and sustainable production. Protected Cropping Structures (PCS) provide controlled farming environments that support the optimum use of crop inputs for plant growth, faster production cycles, multiple growing seasons per annum and increased yield, while offering greater control of pests, disease and adverse weather. Globally, there has been a rapid increase in the adoption of PCS. However, there remains a concerning knowledge gap in the availability of accurate and up-to-date spatial information that defines the extent (location and area) of PCS. This data is fundamental for providing metrics that inform decision making around forward selling, labour, processing and infrastructure requirements, traceability, biosecurity and natural disaster preparedness and response. This project addresses this need, by developing a national map of PCS for Australia using remotely sensed imagery and deep learning analytics, ancillary data, field validation and industry engagement. The resulting map presents the location and extent of all commercial glasshouses, polyhouses, polytunnels, shadehouses and permanent nets with an area of >0.2 ha. The outcomes of the project revealed deep learning techniques can accurately map PCS with models achieving F-Scores > 0.9 and accelerate the mapping where suitable imagery is available. Location-based tools supported by web mapping applications were critical for the validation of PCS locations and for building industry awareness and engagement. The final national PCS map is publicly available through an online dashboard which summarises the area of PCS structures at a range of scales including state/territory, local government area and individual structure. The outcomes of this project have set a global standard on how this level of mapping can be achieved through a collaborative, multifaceted approach.","PeriodicalId":37702,"journal":{"name":"Land","volume":"2 5","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To mitigate the urban heat island phenomenon at night, cool, fresh air can be introduced into the city to circulate and dissipate the heat absorbed during the day, thereby reducing high urban air temperatures. In other words, cold air flow (CAF) generated by mountainous and green areas should be introduced to as wide an area as possible within the city. To this end, it is necessary to first understand the characteristics of urban spatial factors that impact CAF, and to conduct concrete and quantitative analyses of how these urban spatial characteristics are contributing to air temperature reduction. In this study, the following are conducted: (1) an analysis of the relationship between cold air volume flux (CAVF) and the amount of air temperature reduction; (2) urban spatial categorization; (3) an analysis of the relationship between CAVF and the amount of air temperature reduction by urban spatial type; (4) a regression analysis between the amount of air temperature reduction and urban spatial characteristic factors that affect CAF; and finally, (5) the use of CAF to reduce urban air temperatures in urban planning and a design is proposed. Urban space was categorized into nine types using the results of the tertile analysis of CAVF and urban temperature reduction. It was determined that building height (BH) has a positive (+) influence on all urban spatial types, while building area ratio (BA) has a negative (−) effect. However, in the case of wall area index (WAI), the direction of influence varied depending on the development density; relatively low BA areas should focus on development that increases height to increase WAI, while relatively high BA areas should focus on development that reduces BA to reduce WAI by targeting development types closer to the tower type. And even in areas with similar development density, influence varies depending on the terrain elevation. Moreover, it is necessary to prepare improvement measures to increase the factors with CAF that positively influence air temperature reduction and decrease those with negative influence according to the characteristics of urban spatial types. Such results quantitatively and specifically confirmed the effects of spatial factors that affect CAF by urban spatial type on air temperature reduction. The results of this study can be used as useful information for the efficient use of CAF, a major element of urban ecosystem services.
为了缓解夜间的城市热岛现象，可以将新鲜的冷空气引入城市，使白天吸收的热量循环散失，从而降低城市的高气温。换句话说，应在城市中尽可能广泛地引入山地和绿地产生的冷空气流（CAF）。为此，有必要首先了解影响冷气流的城市空间因素特征，并对这些城市空间特征如何促进气温降低进行具体的定量分析。本研究主要进行了以下工作：（1）分析冷空气量通量（CAVF）与气温降低量之间的关系；（2）城市空间分类；（3）按城市空间类型分析冷空气量通量与气温降低量之间的关系；（4）气温降低量与影响冷空气量通量的城市空间特征因素之间的回归分析；最后，（5）提出在城市规划中利用冷空气量通量降低城市气温的方法和设计方案。根据 CAVF 和城市气温降低的三阶分析结果，将城市空间划分为九种类型。结果表明，建筑高度（BH）对所有城市空间类型都有正面（+）影响，而建筑容积率（BA）则有负面（-）影响。然而，就墙体面积指数（WAI）而言，其影响方向因开发密度而异；BA 相对较低的地区应侧重于增加高度以提高 WAI 的开发，而 BA 相对较高的地区则应侧重于降低 BA 以减少 WAI 的开发，其开发类型应更接近塔楼类型。即使在开发密度相近的地区，影响也会因地势高低而不同。此外，有必要根据城市空间类型的特点，制定改进措施，增加对气温降低有积极影响的 CAF 因素，减少有消极影响的 CAF 因素。这些结果定量、具体地证实了城市空间类型中影响 CAF 的空间因素对气温降低的影响。本研究的结果可作为有效利用 CAF 这一城市生态系统服务主要元素的有用信息。
{"title":"Analysis of Spatial Characteristics Contributing to Urban Cold Air Flow","authors":"Hyunsu Kim, Kyushik Oh, Ilsun Yoo","doi":"10.3390/land12122165","DOIUrl":"https://doi.org/10.3390/land12122165","url":null,"abstract":"To mitigate the urban heat island phenomenon at night, cool, fresh air can be introduced into the city to circulate and dissipate the heat absorbed during the day, thereby reducing high urban air temperatures. In other words, cold air flow (CAF) generated by mountainous and green areas should be introduced to as wide an area as possible within the city. To this end, it is necessary to first understand the characteristics of urban spatial factors that impact CAF, and to conduct concrete and quantitative analyses of how these urban spatial characteristics are contributing to air temperature reduction. In this study, the following are conducted: (1) an analysis of the relationship between cold air volume flux (CAVF) and the amount of air temperature reduction; (2) urban spatial categorization; (3) an analysis of the relationship between CAVF and the amount of air temperature reduction by urban spatial type; (4) a regression analysis between the amount of air temperature reduction and urban spatial characteristic factors that affect CAF; and finally, (5) the use of CAF to reduce urban air temperatures in urban planning and a design is proposed. Urban space was categorized into nine types using the results of the tertile analysis of CAVF and urban temperature reduction. It was determined that building height (BH) has a positive (+) influence on all urban spatial types, while building area ratio (BA) has a negative (−) effect. However, in the case of wall area index (WAI), the direction of influence varied depending on the development density; relatively low BA areas should focus on development that increases height to increase WAI, while relatively high BA areas should focus on development that reduces BA to reduce WAI by targeting development types closer to the tower type. And even in areas with similar development density, influence varies depending on the terrain elevation. Moreover, it is necessary to prepare improvement measures to increase the factors with CAF that positively influence air temperature reduction and decrease those with negative influence according to the characteristics of urban spatial types. Such results quantitatively and specifically confirmed the effects of spatial factors that affect CAF by urban spatial type on air temperature reduction. The results of this study can be used as useful information for the efficient use of CAF, a major element of urban ecosystem services.","PeriodicalId":37702,"journal":{"name":"Land","volume":"34 6","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139002660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Effectively managing the diversity and complexity of human settlements is pivotal in tackling the sustainability challenges we face in the Anthropocene. Conceptualizing a city’s human settlement as a unified social–ecological system and investigating its system archetype and evolutionary pattern offer a promising approach to understanding sustainability challenges within specific spatio-temporal contexts. This study introduced a novel approach to assessing and characterizing human settlements using a spatio-temporal two-tier structure archetype analysis for human settlement systems. Applying inductive clustering to an integrated dataset, we identified five typical human settlement systems for 2019 and eight change patterns (2001–2019) in the Yangtze River Delta region. By linking inductively recognized human settlement systems into deductive categories of human-nature connectedness and associating inductive change patterns with deduced phases within the adaptive cycle, we defined five system spatial archetypes and three archetypical evolutionary patterns, revealing the typical interaction between them. This enabled us to understand sustainability challenges for each interaction, formulating seven tailored solutions to promote place-based development in human settlements. Generally, our approach showcases considerable potential in uncovering human settlement challenges, ultimately contributing to addressing these challenges at the local level within the broader context of global sustainability issues.
{"title":"Integrating System Spatial Archetypes and Archetypical Evolutionary Patterns of Human Settlements: Towards Place-Based Sustainable Development","authors":"Wenlin Gao, Wanyue Lyu, Binyi Liu","doi":"10.3390/land12122164","DOIUrl":"https://doi.org/10.3390/land12122164","url":null,"abstract":"Effectively managing the diversity and complexity of human settlements is pivotal in tackling the sustainability challenges we face in the Anthropocene. Conceptualizing a city’s human settlement as a unified social–ecological system and investigating its system archetype and evolutionary pattern offer a promising approach to understanding sustainability challenges within specific spatio-temporal contexts. This study introduced a novel approach to assessing and characterizing human settlements using a spatio-temporal two-tier structure archetype analysis for human settlement systems. Applying inductive clustering to an integrated dataset, we identified five typical human settlement systems for 2019 and eight change patterns (2001–2019) in the Yangtze River Delta region. By linking inductively recognized human settlement systems into deductive categories of human-nature connectedness and associating inductive change patterns with deduced phases within the adaptive cycle, we defined five system spatial archetypes and three archetypical evolutionary patterns, revealing the typical interaction between them. This enabled us to understand sustainability challenges for each interaction, formulating seven tailored solutions to promote place-based development in human settlements. Generally, our approach showcases considerable potential in uncovering human settlement challenges, ultimately contributing to addressing these challenges at the local level within the broader context of global sustainability issues.","PeriodicalId":37702,"journal":{"name":"Land","volume":"39 2","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Applying the livelihood resilience theory to the relocation of coal mining villages, the present study explored the levels and the factors hindering livelihood resilience among farmers under different relocation models. This has important implications for enhancing the livelihood resilience of farmers during coal mining relocation and promoting rural revitalization in coal mining areas. Based on the livelihood resilience framework and the actual conditions of mining areas, we formulated an evaluation index system, employed the stratified mean square deviation method to determine weights, used the comprehensive index method to assess the livelihood resilience level, and investigated the obstacles to livelihood resilience among farmers under different relocation models using the random forest model. The results indicate the following: first, the overall livelihood resilience level in the coal mining relocation area of Huaibei City is low and is not significantly different among the four types, with the ranking being as follows: central village agglomeration type > township-centered village construction type > mining-village combination type > suburban community type. Significant differences exist in the indicators and dispersion levels of the resilience dimensions of buffering capacity, self-organization ability, and learning ability among farmers under different relocation models. Second, factors such as household deposits, labor force quantity, social networks, and participation in village collective meetings significantly affect the livelihood resilience level of farmers. However, the degree of influence varies under different relocation models. Third, improvements such as increasing employment opportunities, investing in education resources, and building social networks are necessary to improve farmers’ livelihoods under the four types of relocation models.
{"title":"Impact of Different Models of Relocating Coal Mining Villages on the Livelihood Resilience of Rural Households—A Case Study of Huaibei City, Anhui Province","authors":"Jing Wang, Peijun Wang, Chunbo Zhu, Yue Wang, Zixiao Zhou","doi":"10.3390/land12122169","DOIUrl":"https://doi.org/10.3390/land12122169","url":null,"abstract":"Applying the livelihood resilience theory to the relocation of coal mining villages, the present study explored the levels and the factors hindering livelihood resilience among farmers under different relocation models. This has important implications for enhancing the livelihood resilience of farmers during coal mining relocation and promoting rural revitalization in coal mining areas. Based on the livelihood resilience framework and the actual conditions of mining areas, we formulated an evaluation index system, employed the stratified mean square deviation method to determine weights, used the comprehensive index method to assess the livelihood resilience level, and investigated the obstacles to livelihood resilience among farmers under different relocation models using the random forest model. The results indicate the following: first, the overall livelihood resilience level in the coal mining relocation area of Huaibei City is low and is not significantly different among the four types, with the ranking being as follows: central village agglomeration type > township-centered village construction type > mining-village combination type > suburban community type. Significant differences exist in the indicators and dispersion levels of the resilience dimensions of buffering capacity, self-organization ability, and learning ability among farmers under different relocation models. Second, factors such as household deposits, labor force quantity, social networks, and participation in village collective meetings significantly affect the livelihood resilience level of farmers. However, the degree of influence varies under different relocation models. Third, improvements such as increasing employment opportunities, investing in education resources, and building social networks are necessary to improve farmers’ livelihoods under the four types of relocation models.","PeriodicalId":37702,"journal":{"name":"Land","volume":"2 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Convention on Biological Diversity (CBD) has been a pivotal international instrument for global biodiversity conservation since 1992. The recent Kunming-Montreal Global Biodiversity Framework (GBF) aims to provide a pathway for the CBD for the present decade. However, the practicalities of land use and biodiversity conservation pose significant challenges. Drawing from diverse literature and reports, we identify nine implementation challenges for the GBF. These encompass harmonising conservation with sustainable development, integrating local values and indigenous knowledge, adopting a holistic landscape approach, and prioritising effective local governance. A shift from broad targets to explicit conservation metrics is vital. We propose strategies emphasising building institutional capacity for localised, participatory conservation and policy-making processes. This article offers suggestions for improving the GBF’s implementation and shaping future policy frameworks.
{"title":"Challenges to Implementing the Kunming-Montreal Global Biodiversity Framework","authors":"Qingyang Li, Yingxue Ge, Jeffrey A. Sayer","doi":"10.3390/land12122166","DOIUrl":"https://doi.org/10.3390/land12122166","url":null,"abstract":"The Convention on Biological Diversity (CBD) has been a pivotal international instrument for global biodiversity conservation since 1992. The recent Kunming-Montreal Global Biodiversity Framework (GBF) aims to provide a pathway for the CBD for the present decade. However, the practicalities of land use and biodiversity conservation pose significant challenges. Drawing from diverse literature and reports, we identify nine implementation challenges for the GBF. These encompass harmonising conservation with sustainable development, integrating local values and indigenous knowledge, adopting a holistic landscape approach, and prioritising effective local governance. A shift from broad targets to explicit conservation metrics is vital. We propose strategies emphasising building institutional capacity for localised, participatory conservation and policy-making processes. This article offers suggestions for improving the GBF’s implementation and shaping future policy frameworks.","PeriodicalId":37702,"journal":{"name":"Land","volume":"95 3","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138975461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In key moments of urban history, urban design is confronted with the emergence of new paradigmatic design models, such as the garden city and the radiant city. Recently, the Smart City seems to have gained centre stage in the public debate. However, despite its emblazoned technological features, the Smart City remains a hazy concept in the urban design domain to such an extent that almost any form can be built under the Smart City label. While this may sound libertarian and progressist, it is also concerning since different urban forms are associated with different societal outcomes. This paper aims to investigate the forms of Smart City districts through morphometric comparison. More specifically, it proposes a replicable methodology based on 18 metrics of urban form and statistical analysis to compare a Smart City district with other city areas with known design models of reference. Such a methodology is applied to three case studies on the French Riviera: Méridia, a Smart City district, Hôtel-des-Postes, a 19th-century traditional district, and Sophia Antipolis, a sprawling technopark. The results show that Méridia has a hybrid form that partly resembles Hôtel-des-Postes (higher densities, gridiron plan, and functional mix) and partly Sophia Antipolis (bulky buildings with large setbacks). However, the top–down approach used in the production of the physical space ultimately renders Méridia more similar to Sophia Antipolis than Hôtel-des-Postes. This study provides one of the first morphometric characterisations of a Smart City district, but also a replicable methodology that can further the morphological understanding of the Smart City phenomenon worldwide.
{"title":"Exploring the Form of a Smart City District: A Morphometric Comparison with Examples of Previous Design Models","authors":"A. Venerandi, Giovanni Fusco, M. Caglioni","doi":"10.3390/land12122159","DOIUrl":"https://doi.org/10.3390/land12122159","url":null,"abstract":"In key moments of urban history, urban design is confronted with the emergence of new paradigmatic design models, such as the garden city and the radiant city. Recently, the Smart City seems to have gained centre stage in the public debate. However, despite its emblazoned technological features, the Smart City remains a hazy concept in the urban design domain to such an extent that almost any form can be built under the Smart City label. While this may sound libertarian and progressist, it is also concerning since different urban forms are associated with different societal outcomes. This paper aims to investigate the forms of Smart City districts through morphometric comparison. More specifically, it proposes a replicable methodology based on 18 metrics of urban form and statistical analysis to compare a Smart City district with other city areas with known design models of reference. Such a methodology is applied to three case studies on the French Riviera: Méridia, a Smart City district, Hôtel-des-Postes, a 19th-century traditional district, and Sophia Antipolis, a sprawling technopark. The results show that Méridia has a hybrid form that partly resembles Hôtel-des-Postes (higher densities, gridiron plan, and functional mix) and partly Sophia Antipolis (bulky buildings with large setbacks). However, the top–down approach used in the production of the physical space ultimately renders Méridia more similar to Sophia Antipolis than Hôtel-des-Postes. This study provides one of the first morphometric characterisations of a Smart City district, but also a replicable methodology that can further the morphological understanding of the Smart City phenomenon worldwide.","PeriodicalId":37702,"journal":{"name":"Land","volume":"84 4","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139004344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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