Spatial–temporal variation in soil organic carbon is an important factor for national targets to mitigate climate change and land degradation impacts. In this research, we took Guangdong Province of China as the study area, evaluated the spatial–temporal distributions of soil organic carbon using data from three China Geochemical Baseline projects (conducted in 2009, 2016, and 2023, respectively), and quantified the main driving factors of spatial–temporal variations in soil organic carbon using the random forest algorithm, further predicting the density and inventories of soil organic carbon. The results demonstrate that the mean value of SOC in Guangdong in 2009 was 0.81%; in 2016 it was 1.13%; and in 2023 it was 1.02%. The inventories of soil organic carbon (0–30 cm) in Guangdong Province were 0.61 Pg in 2009, 0.74 Pg in 2016, and 0.62 Pg in 2023. Soil in Guangdong acted as a carbon sink from 2009 to 2023 as a whole, and the most important driving force behind spatial–temporal variations in soil organic carbon was temperature, followed by precipitation and vegetation cover.
{"title":"Spatial–Temporal Variations in Soil Organic Carbon and Driving Factors in Guangdong, China (2009–2023)","authors":"Mi Tian, Chao Wu, Xin Zhu, Qin Hu, Xueqiu Wang, Binbin Sun, Jian Zhou, Wei Wang, Q. Chi, Hanliang Liu, Yuheng Liu, Jiwu Yang, Xurong Li","doi":"10.3390/land13071096","DOIUrl":"https://doi.org/10.3390/land13071096","url":null,"abstract":"Spatial–temporal variation in soil organic carbon is an important factor for national targets to mitigate climate change and land degradation impacts. In this research, we took Guangdong Province of China as the study area, evaluated the spatial–temporal distributions of soil organic carbon using data from three China Geochemical Baseline projects (conducted in 2009, 2016, and 2023, respectively), and quantified the main driving factors of spatial–temporal variations in soil organic carbon using the random forest algorithm, further predicting the density and inventories of soil organic carbon. The results demonstrate that the mean value of SOC in Guangdong in 2009 was 0.81%; in 2016 it was 1.13%; and in 2023 it was 1.02%. The inventories of soil organic carbon (0–30 cm) in Guangdong Province were 0.61 Pg in 2009, 0.74 Pg in 2016, and 0.62 Pg in 2023. Soil in Guangdong acted as a carbon sink from 2009 to 2023 as a whole, and the most important driving force behind spatial–temporal variations in soil organic carbon was temperature, followed by precipitation and vegetation cover.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819964","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 current greenway systems in China are relatively homogenous, whereas recreational groups and their needs are highly diverse. This discrepancy has resulted in increasingly severe behavioral conflicts during greenway recreation. However, scholarly research on behavioral conflicts in greenway recreational activities is lacking. Recreationists’ perceptions of conflict negatively impact their evaluation of the recreational experience, thereby limiting the ecological and recreational benefits of greenways. Therefore, it is crucial to categorize these conflicts, understand their formation mechanisms, and identify influencing factors, so as to put forward targeted management strategies for greenway construction. This study selected urban segments of greenways along the Wei and Feng rivers in Xi’an, Shaanxi Province, China. Field observation, semi-structured interviews, and NVivo 12 three-level coding were used to investigate and analyze the main types of behavioral conflicts perceived by various recreational groups on urban greenways and the factors influencing these perceptions. The results indicate that the primary types of behavioral conflicts are danger perception, space occupancy, environmental damage, and noise disturbance. Younger groups, highly educated individuals, local residents, and those with exercise as their primary recreational purpose are more likely to perceive conflicts. In addition, recreationists also focus on the completeness of greenway infrastructure, the richness of green landscapes, and the adequacy of behavior management. These findings can help greenway managers and planners understand the perception of recreational conflicts, enabling the formulation of targeted design strategies and management measures to mitigate these conflicts in urban greenway recreation.
{"title":"Behavioral Conflicts in Urban Greenway Recreation: A Case Study of the “Three Rivers and One Mountain” Greenway in Xi’an, China","authors":"Xiaolu Yang, Jingyi Zhang, Yueyang Yu, Xiu-Juan Qiao","doi":"10.3390/land13071097","DOIUrl":"https://doi.org/10.3390/land13071097","url":null,"abstract":"The current greenway systems in China are relatively homogenous, whereas recreational groups and their needs are highly diverse. This discrepancy has resulted in increasingly severe behavioral conflicts during greenway recreation. However, scholarly research on behavioral conflicts in greenway recreational activities is lacking. Recreationists’ perceptions of conflict negatively impact their evaluation of the recreational experience, thereby limiting the ecological and recreational benefits of greenways. Therefore, it is crucial to categorize these conflicts, understand their formation mechanisms, and identify influencing factors, so as to put forward targeted management strategies for greenway construction. This study selected urban segments of greenways along the Wei and Feng rivers in Xi’an, Shaanxi Province, China. Field observation, semi-structured interviews, and NVivo 12 three-level coding were used to investigate and analyze the main types of behavioral conflicts perceived by various recreational groups on urban greenways and the factors influencing these perceptions. The results indicate that the primary types of behavioral conflicts are danger perception, space occupancy, environmental damage, and noise disturbance. Younger groups, highly educated individuals, local residents, and those with exercise as their primary recreational purpose are more likely to perceive conflicts. In addition, recreationists also focus on the completeness of greenway infrastructure, the richness of green landscapes, and the adequacy of behavior management. These findings can help greenway managers and planners understand the perception of recreational conflicts, enabling the formulation of targeted design strategies and management measures to mitigate these conflicts in urban greenway recreation.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820382","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}
L. Tripolskaja, M. Toleikienė, Aida Skersiene, Agnė Veršulienė
To prevent the degradation of light-textured soils, it is advisable to use them for grasslands. These soil management systems help with the faster accumulation of soil organic carbon (SOC), thereby improving the soil’s properties and reducing carbon emissions from agricultural land. In this experiment, we studied the distribution of multi-component perennial grass roots in the Arenosol profile and their impact on SOC sequestration in temperate climate zones. Our research aimed to identify differences in root biomass at depths of 0–15 cm, 15–30 cm, and 30–50 cm and to assess their correlation with SOC and dissolved organic carbon (DOC) in the soil. The roots, shoots, and soil samples of fertilized and unfertilized grasslands were collected at the flowering stage and after the final grass harvest two years in a row. Our findings revealed that, in sandy loam Arenosol rich in stones, 12.4–15.9 Mg ha−1 of root biomass was accumulated at 0–50 cm of soil depth. The application of NPK fertilizers did not significantly affect grass root biomass, but significantly affected shoot biomass. Most roots (84–88%) were concentrated in the 0–15 cm layer. On average, 5.10–6.62 Mg ha−1 of organic carbon (OC) was stored in the roots of perennial grasses within 0–50 cm of soil depth. We found that the SOC content in the 0–50 cm soil layer correlated more strongly (r = 0.62, p < 0.001) with C accumulated in the roots of the corresponding layer than with shoot biomass (r = 0.41, p = 0.04). However, a significant correlation was found between DOC and shoot biomass (r = 0.68, p < 0.001) and between DOC and the biomass of residues (r = 0.71, p < 0.001), explaining the significant increase in DOC in the 30–50 cm soil layer and indicating the leaching of mobile soil organic matter (SOM) substances from the above-ground biomass using fertilizers.
{"title":"Biomass of Shoots and Roots of Multicomponent Grasslands and Their Impact on Soil Carbon Accumulation in Arenosol Rich in Stones","authors":"L. Tripolskaja, M. Toleikienė, Aida Skersiene, Agnė Veršulienė","doi":"10.3390/land13071098","DOIUrl":"https://doi.org/10.3390/land13071098","url":null,"abstract":"To prevent the degradation of light-textured soils, it is advisable to use them for grasslands. These soil management systems help with the faster accumulation of soil organic carbon (SOC), thereby improving the soil’s properties and reducing carbon emissions from agricultural land. In this experiment, we studied the distribution of multi-component perennial grass roots in the Arenosol profile and their impact on SOC sequestration in temperate climate zones. Our research aimed to identify differences in root biomass at depths of 0–15 cm, 15–30 cm, and 30–50 cm and to assess their correlation with SOC and dissolved organic carbon (DOC) in the soil. The roots, shoots, and soil samples of fertilized and unfertilized grasslands were collected at the flowering stage and after the final grass harvest two years in a row. Our findings revealed that, in sandy loam Arenosol rich in stones, 12.4–15.9 Mg ha−1 of root biomass was accumulated at 0–50 cm of soil depth. The application of NPK fertilizers did not significantly affect grass root biomass, but significantly affected shoot biomass. Most roots (84–88%) were concentrated in the 0–15 cm layer. On average, 5.10–6.62 Mg ha−1 of organic carbon (OC) was stored in the roots of perennial grasses within 0–50 cm of soil depth. We found that the SOC content in the 0–50 cm soil layer correlated more strongly (r = 0.62, p < 0.001) with C accumulated in the roots of the corresponding layer than with shoot biomass (r = 0.41, p = 0.04). However, a significant correlation was found between DOC and shoot biomass (r = 0.68, p < 0.001) and between DOC and the biomass of residues (r = 0.71, p < 0.001), explaining the significant increase in DOC in the 30–50 cm soil layer and indicating the leaching of mobile soil organic matter (SOM) substances from the above-ground biomass using fertilizers.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820091","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}
Quantitative assessment and trade-off/synergy analysis of land use multifunctions can effectively identify regional conflicts and dominant functions, providing decision support for promoting sustainable socio-economic and land use development. However, current research in this field still faces challenges due to coarse scale of studies and limited availability of accurate data. Taking Harbin City as a research case, this research employed an improved mutation level method, Pearson correlation analysis, and a multi-scale geographically weighted regression model to comprehensively investigate the profiling of land use multifunctions and their trade-off /synergy relationships. The comparative advantage theory was adopted to identify dominant functional zones using the NRCA index at a grid scale, in order to achieve a territorial spatial functional zoning delineation. The results showed that there were intricate trade-off/synergy relationships among production–living–ecology functions. Moreover, the types and intensity of trade-off/synergy evolved continuously with socio-economic development and regional resource endowment disparities. Due to its exceptional resource endowment, the agricultural dominated, urban dominated, and ecological dominated functional areas accounted for a significant proportion of 29%, 7%, and 26%, respectively. However, owing to the intricate trade-offs/synergies inherent in land use multifunctions, only a mere 2% (agricultural), 1% (urban), and 1% (ecological) of the area were identified as Optimization Guidance Zones. Conversely, Remediation Improvement Zones constituted the largest share at 63% of the total area, with agricultural, urban, and ecological Remediation Improvement Zones accounting for approximately 33%, 12%, and 18%, respectively. Based on the results of the type and intensity of trade-off/synergy among production–living–ecological functions, as well as the dominant zones and the integrated territorial spatial functional zoning delineation, this article provided targeted recommendations for the sustainable development of the region. These recommendations took into account both resource endowment and socio-economic development characteristics specific to the study area. The study aims to contribute to related research gaps, while providing valuable insights for other regional studies.
{"title":"Spatial Identification and Evaluation of Land Use Multifunctions and Their Interrelationships Improve Territorial Space Zoning Management in Harbin, China","authors":"Yafang Zhao, Jiafu Liu, Jie Zhang, Xiaonan Zhang, Hongbo Li, Fengjie Gao, Yucheng Zhan","doi":"10.3390/land13071092","DOIUrl":"https://doi.org/10.3390/land13071092","url":null,"abstract":"Quantitative assessment and trade-off/synergy analysis of land use multifunctions can effectively identify regional conflicts and dominant functions, providing decision support for promoting sustainable socio-economic and land use development. However, current research in this field still faces challenges due to coarse scale of studies and limited availability of accurate data. Taking Harbin City as a research case, this research employed an improved mutation level method, Pearson correlation analysis, and a multi-scale geographically weighted regression model to comprehensively investigate the profiling of land use multifunctions and their trade-off /synergy relationships. The comparative advantage theory was adopted to identify dominant functional zones using the NRCA index at a grid scale, in order to achieve a territorial spatial functional zoning delineation. The results showed that there were intricate trade-off/synergy relationships among production–living–ecology functions. Moreover, the types and intensity of trade-off/synergy evolved continuously with socio-economic development and regional resource endowment disparities. Due to its exceptional resource endowment, the agricultural dominated, urban dominated, and ecological dominated functional areas accounted for a significant proportion of 29%, 7%, and 26%, respectively. However, owing to the intricate trade-offs/synergies inherent in land use multifunctions, only a mere 2% (agricultural), 1% (urban), and 1% (ecological) of the area were identified as Optimization Guidance Zones. Conversely, Remediation Improvement Zones constituted the largest share at 63% of the total area, with agricultural, urban, and ecological Remediation Improvement Zones accounting for approximately 33%, 12%, and 18%, respectively. Based on the results of the type and intensity of trade-off/synergy among production–living–ecological functions, as well as the dominant zones and the integrated territorial spatial functional zoning delineation, this article provided targeted recommendations for the sustainable development of the region. These recommendations took into account both resource endowment and socio-economic development characteristics specific to the study area. The study aims to contribute to related research gaps, while providing valuable insights for other regional studies.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823305","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 exponential growth of user-contributed data provides a comprehensive basis for assessing collective perceptions of landscape change. A variety of possible public data sources exist, such as geospatial data from social media or volunteered geographic information (VGI). Key challenges with such “opportunistic” data sampling are variability in platform popularity and bias due to changing user groups and contribution rules. In this study, we use five case studies to demonstrate how intra- and inter-dataset comparisons can help to assess the temporality of landscape scenic resources, such as identifying seasonal characteristics for a given area or testing hypotheses about shifting popularity trends observed in the field. By focusing on the consistency and reproducibility of temporal patterns for selected scenic resources and comparisons across different dimensions of data, we aim to contribute to the development of systematic methods for disentangling the perceived impact of events and trends from other technological and social phenomena included in the data. The proposed techniques may help to draw attention to overlooked or underestimated patterns of landscape change, fill in missing data between periodic surveys, or corroborate and support field observations. Despite limitations, the results provide a comprehensive basis for developing indicators with a high degree of timeliness for monitoring perceived landscape change over time.
{"title":"Assessing Perceived Landscape Change from Opportunistic Spatiotemporal Occurrence Data","authors":"A. Dunkel, Dirk Burghardt","doi":"10.3390/land13071091","DOIUrl":"https://doi.org/10.3390/land13071091","url":null,"abstract":"The exponential growth of user-contributed data provides a comprehensive basis for assessing collective perceptions of landscape change. A variety of possible public data sources exist, such as geospatial data from social media or volunteered geographic information (VGI). Key challenges with such “opportunistic” data sampling are variability in platform popularity and bias due to changing user groups and contribution rules. In this study, we use five case studies to demonstrate how intra- and inter-dataset comparisons can help to assess the temporality of landscape scenic resources, such as identifying seasonal characteristics for a given area or testing hypotheses about shifting popularity trends observed in the field. By focusing on the consistency and reproducibility of temporal patterns for selected scenic resources and comparisons across different dimensions of data, we aim to contribute to the development of systematic methods for disentangling the perceived impact of events and trends from other technological and social phenomena included in the data. The proposed techniques may help to draw attention to overlooked or underestimated patterns of landscape change, fill in missing data between periodic surveys, or corroborate and support field observations. Despite limitations, the results provide a comprehensive basis for developing indicators with a high degree of timeliness for monitoring perceived landscape change over time.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822194","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}
Christophe Sannier, Eva Ivits, G. Maucha, Joachim Maes, Lewis Dijkstra
The European Copernicus Land Monitoring Service (CLMS) has been producing datasets on imperviousness every 3 years since 2006. However, for 2018, the input for the production of the imperviousness dataset was switched from mixed inputs to the Sentinel constellation. While this led to an improvement in the spatial detail from 20 m to 10 m, this also resulted in a break in the time series as the 2018 update was not comparable to the previous reference years. In addition, the European CLMS has been producing a new dataset from 2018 onward entitled CLC+ Backbone, which also includes a sealed area thematic class. When comparing both datasets with sampled reference data, it appears that the imperviousness dataset substantially underestimates sealed areas at the European level. However, the CLC+ dataset is only available from 2018 and currently does not include any change layer. To address these issues, a harmonized continental soil sealing combined dataset for Europe was produced for the entire observation period. This new dataset has been validated to be the best current dataset for monitoring soil sealing as a direct input for European policies with an estimated total sealed area of 175,664 km2 over Europe and an increase in sealed areas of 1297 km2 or 0.7% between 2015 and 2018, which is comparable to previous time periods. Finally, recommendations for future updates and the validation of imperviousness degree geospatial products are given.
{"title":"Harmonized Pan-European Time Series for Monitoring Soil Sealing","authors":"Christophe Sannier, Eva Ivits, G. Maucha, Joachim Maes, Lewis Dijkstra","doi":"10.3390/land13071087","DOIUrl":"https://doi.org/10.3390/land13071087","url":null,"abstract":"The European Copernicus Land Monitoring Service (CLMS) has been producing datasets on imperviousness every 3 years since 2006. However, for 2018, the input for the production of the imperviousness dataset was switched from mixed inputs to the Sentinel constellation. While this led to an improvement in the spatial detail from 20 m to 10 m, this also resulted in a break in the time series as the 2018 update was not comparable to the previous reference years. In addition, the European CLMS has been producing a new dataset from 2018 onward entitled CLC+ Backbone, which also includes a sealed area thematic class. When comparing both datasets with sampled reference data, it appears that the imperviousness dataset substantially underestimates sealed areas at the European level. However, the CLC+ dataset is only available from 2018 and currently does not include any change layer. To address these issues, a harmonized continental soil sealing combined dataset for Europe was produced for the entire observation period. This new dataset has been validated to be the best current dataset for monitoring soil sealing as a direct input for European policies with an estimated total sealed area of 175,664 km2 over Europe and an increase in sealed areas of 1297 km2 or 0.7% between 2015 and 2018, which is comparable to previous time periods. Finally, recommendations for future updates and the validation of imperviousness degree geospatial products are given.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821308","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}
Alexandru Dragan, Remus Crețan, Mihaela Ancuța Lungu
There has been a debate recently on how the population in traditional mining areas of Central and Eastern Europe faces precarity and marginalization. A spatial approach was employed in a Romanian context using available statistical data on a south Carpathian area (i.e., Gorj County). We also conducted surveys and in-depth interviews with residents in one of the rural communities of Gorj. Our findings highlight that a large number of rural localities in this county are technically, economically, and socially underdeveloped. Many inhabitants face a lack of financial resources and employment opportunities, which has led to the emigration of young people to larger Romanian cities or to other countries. We conclude that in order to avoid a much deeper social and spatial marginalization of local inhabitants, an integrated strategy is needed to target economic and social development, investment in infrastructure and public services, the promotion of employment and training opportunities, and to better integrate local culture and traditions into tourism.
{"title":"Neglected and Peripheral Spaces: Challenges of Socioeconomic Marginalization in a South Carpathian Area","authors":"Alexandru Dragan, Remus Crețan, Mihaela Ancuța Lungu","doi":"10.3390/land13071086","DOIUrl":"https://doi.org/10.3390/land13071086","url":null,"abstract":"There has been a debate recently on how the population in traditional mining areas of Central and Eastern Europe faces precarity and marginalization. A spatial approach was employed in a Romanian context using available statistical data on a south Carpathian area (i.e., Gorj County). We also conducted surveys and in-depth interviews with residents in one of the rural communities of Gorj. Our findings highlight that a large number of rural localities in this county are technically, economically, and socially underdeveloped. Many inhabitants face a lack of financial resources and employment opportunities, which has led to the emigration of young people to larger Romanian cities or to other countries. We conclude that in order to avoid a much deeper social and spatial marginalization of local inhabitants, an integrated strategy is needed to target economic and social development, investment in infrastructure and public services, the promotion of employment and training opportunities, and to better integrate local culture and traditions into tourism.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821524","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}
Mia Callenberg, Aloke Barnwal, Mohamed Imam Bakarr
Cities were at the center of the COVID-19 pandemic due to the concentration of affected populations and economic activities that needed to be revived to support global recovery. While cities offer strong economic and social benefits due to density, proximity, and global connectivity, the pandemic had a tremendous impact on their vital functions. It resulted in lost lives and livelihoods and deepened economic and social divides. Furthermore, the pandemic exacerbated many existing environmental challenges in cities. This presented an opportunity to tackle these interlinked challenges in an integrated manner. Evidence suggests that many city leaders integrated environmental sustainability as an important element to complement their emergency responses. Drawing from experiences in cities around the world, particularly those participating in the Sustainable Cities Program supported by the Global Environment Facility (GEF), this paper describes how integrated solutions were applied to tackle the COVID-19 pandemic. Consistent with a Healthy Planet Healthy People concept, a framework is proposed for sustainable urban transformation and to build cities that are resilient to shocks and stresses. With global environmental benefits at the core, the framework highlights the importance of integration, inclusion, and innovation as key approaches in steering the future green growth and prosperity of cities.
{"title":"COVID-19 Pandemic and Sustainable Urban Transformation: Perspectives on City-Level Actions and a Framework for the Future","authors":"Mia Callenberg, Aloke Barnwal, Mohamed Imam Bakarr","doi":"10.3390/land13071093","DOIUrl":"https://doi.org/10.3390/land13071093","url":null,"abstract":"Cities were at the center of the COVID-19 pandemic due to the concentration of affected populations and economic activities that needed to be revived to support global recovery. While cities offer strong economic and social benefits due to density, proximity, and global connectivity, the pandemic had a tremendous impact on their vital functions. It resulted in lost lives and livelihoods and deepened economic and social divides. Furthermore, the pandemic exacerbated many existing environmental challenges in cities. This presented an opportunity to tackle these interlinked challenges in an integrated manner. Evidence suggests that many city leaders integrated environmental sustainability as an important element to complement their emergency responses. Drawing from experiences in cities around the world, particularly those participating in the Sustainable Cities Program supported by the Global Environment Facility (GEF), this paper describes how integrated solutions were applied to tackle the COVID-19 pandemic. Consistent with a Healthy Planet Healthy People concept, a framework is proposed for sustainable urban transformation and to build cities that are resilient to shocks and stresses. With global environmental benefits at the core, the framework highlights the importance of integration, inclusion, and innovation as key approaches in steering the future green growth and prosperity of cities.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821293","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}
Urban green infrastructure construction and economic growth are necessary ways and important supports to promote sustainable development. Exploring their coupling coordination relationship is important for achieving high-quality economic development. This study uses the entropy method, coupling coordination degree, kernel density estimation, the Dagum Gini coefficient, and spatial autocorrelation to explore the spatial-temporal pattern characteristics and coupling coordination relationship between green infrastructure construction and economic development for 273 cities in Chinese mainland in 2010–2020. The results show that the level of China’s green infrastructure construction and economic development gradually increased during 2010–2020. There were significant regional differences in space, exhibiting a decreasing spatial pattern from east to west. The coupling coordination degree was constantly improving. The overall Gini coefficient shows an upward trend. Among the four regions, eastern China has the greatest intraregional variation. The uneven level of coupled coordination is mainly from interregional variation. There was a significant positive spatial autocorrelation relationship, and cities that had a higher degree of coupling coordination tended to agglomeration development. Meanwhile, it also had certain spatial heterogeneity. China’s entire level of coupling coordination degree still has much room for improvement. The study is of great significance in reducing disparities between regions and strengthening regional spatial coordination development.
{"title":"Spatial-Temporal Coupling Coordination Relationship between Urban Green Infrastructure Construction and Economic Development in China","authors":"Weiwei Wang, Yanping Wen, Wan-xu Chen, Yiran Qu","doi":"10.3390/land13071095","DOIUrl":"https://doi.org/10.3390/land13071095","url":null,"abstract":"Urban green infrastructure construction and economic growth are necessary ways and important supports to promote sustainable development. Exploring their coupling coordination relationship is important for achieving high-quality economic development. This study uses the entropy method, coupling coordination degree, kernel density estimation, the Dagum Gini coefficient, and spatial autocorrelation to explore the spatial-temporal pattern characteristics and coupling coordination relationship between green infrastructure construction and economic development for 273 cities in Chinese mainland in 2010–2020. The results show that the level of China’s green infrastructure construction and economic development gradually increased during 2010–2020. There were significant regional differences in space, exhibiting a decreasing spatial pattern from east to west. The coupling coordination degree was constantly improving. The overall Gini coefficient shows an upward trend. Among the four regions, eastern China has the greatest intraregional variation. The uneven level of coupled coordination is mainly from interregional variation. There was a significant positive spatial autocorrelation relationship, and cities that had a higher degree of coupling coordination tended to agglomeration development. Meanwhile, it also had certain spatial heterogeneity. China’s entire level of coupling coordination degree still has much room for improvement. The study is of great significance in reducing disparities between regions and strengthening regional spatial coordination development.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820838","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}
Since the socio-economic reform in 1978, rural China has undergone drastic spatial restructuring, and the trend of multifunctional development and dynamic evolution of settlements in the countryside have become increasingly obvious. Functions and settlements are the important parts of rural areas. Rural multifunction is a new perspective to explore the diversified development paths of the countryside, and rural settlements provide basic support for rural multifunction. Clarifying the complex coupling coordination relationship between rural functional diversification (RFD) and rural settlement evolution (RSE), and identifying the spatial heterogeneity of their interactions is the key to promoting the rural revitalization strategy. This study analyzes the spatiotemporal changes in rural functions and rural settlements at the township level, alongside assessing various forms and the extent of coupled development. Therein, we consider the advantages of different coupling types of townships and propose four development paths for rural settlements to improve the adaptability of rural functions and settlements. The results show that: (1) The functions and settlements in the study area are characterized by significant spatial and temporal dynamics, indicating that the traditional mountainous countryside is in a process of rapid development and change. (2) The coupling coordination degree of RFD and RSE increases yearly, generally transitioning from the moderate imbalance to the basic coordination stage, and the coordinated townships have obvious spatial agglomeration. (3) Based on the elasticity coefficient model, this paper summarizes four coupling models of RFD and RSE to guide the optimization of rural settlement development paths. This research provides scientific guidance for developing countries in the spatial planning of rural territories and the optimization of rural settlements.
{"title":"Coupling Coordination Relationship and Spatiotemporal Heterogeneity between Functional Diversification and Settlement Evolution in Traditional Mountain Areas (2000–2020): A Case Study of Fengjie County, China","authors":"Wenxin Zhao, Yangbing Li, Qingrong Wang, Jing’an Shao","doi":"10.3390/land13071090","DOIUrl":"https://doi.org/10.3390/land13071090","url":null,"abstract":"Since the socio-economic reform in 1978, rural China has undergone drastic spatial restructuring, and the trend of multifunctional development and dynamic evolution of settlements in the countryside have become increasingly obvious. Functions and settlements are the important parts of rural areas. Rural multifunction is a new perspective to explore the diversified development paths of the countryside, and rural settlements provide basic support for rural multifunction. Clarifying the complex coupling coordination relationship between rural functional diversification (RFD) and rural settlement evolution (RSE), and identifying the spatial heterogeneity of their interactions is the key to promoting the rural revitalization strategy. This study analyzes the spatiotemporal changes in rural functions and rural settlements at the township level, alongside assessing various forms and the extent of coupled development. Therein, we consider the advantages of different coupling types of townships and propose four development paths for rural settlements to improve the adaptability of rural functions and settlements. The results show that: (1) The functions and settlements in the study area are characterized by significant spatial and temporal dynamics, indicating that the traditional mountainous countryside is in a process of rapid development and change. (2) The coupling coordination degree of RFD and RSE increases yearly, generally transitioning from the moderate imbalance to the basic coordination stage, and the coordinated townships have obvious spatial agglomeration. (3) Based on the elasticity coefficient model, this paper summarizes four coupling models of RFD and RSE to guide the optimization of rural settlement development paths. This research provides scientific guidance for developing countries in the spatial planning of rural territories and the optimization of rural settlements.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823189","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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