Shu-qin He, Jian Luo, Zicheng Zheng, Wenfeng Ding, Jigen Liu
The occurrence and development of rill erosion depends on the hydraulic characteristics of water flow and underlying soil surface features. Our experiments include one-rainfall-intensity treatments (2.0 mm min−1) and various microtopographic levels based on different tillage practices with smooth slope (CK), artificial digging (AD), and ridge tillage (RT) on a 15° slope. The results indicate the following: (1) The soil roughness index values were in the order of CK < AD < RT, and the spatial variability of different tillage practices had strong autocorrelations during different rill erosive stages. The codomain values decreased with the increase in microtopography. (2) The multifractal dimension values of tillage practices in various erosive stages were in the order of RT > AD > CT. The microtopography of different tilled slopes showed strong multifractal characteristics, and the multifractal characteristics were stronger as the microrelief heterogeneity increased. For the CK slope, the generalized fractal dimension span (ΔD) ranged between 0.0019 and 0.0058. For the AD slope, ΔD was between 0.2901 and 0.5112. And, for the RT slope, ΔD was between 0.4235 and 0.7626. (3) With the evolution of rill erosion, the flow pattern on different tilled slopes changed from subcritical transition flow to supercritical transition flow. (4) Soil roughness index and ΔD had good correlations with hydrodynamic parameters. The stronger the erosive energy of runoff was, the higher the spatial heterogeneity of microtopography was. This study is expected to provide a theoretical basis for revealing the hydrodynamic mechanism of rill erosion in slope farmland.
Rill 侵蚀的发生和发展取决于水流的水力特征和下层土壤表面特征。我们的实验包括一个降雨强度处理（2.0 毫米/分钟-1）和不同的微地形水平，这些微地形水平基于在 15° 坡度上的平滑坡（CK）、人工挖掘（AD）和脊耕（RT）等不同耕作方式。结果表明(1）土壤粗糙度指数值按 CK < AD < RT 的顺序排列，不同耕作方式在不同垄蚀阶段的空间变异具有较强的自相关性。随着微地形的增加，分域值降低。(2）不同耕作方式在不同侵蚀阶段的多分形维值顺序为 RT > AD > CT。不同耕作坡面的微地形表现出较强的多分形特征，且随着微退异质性的增加，多分形特征更强。对于 CK 斜坡，广义分形维度跨度（ΔD）介于 0.0019 和 0.0058 之间。对于 AD 斜坡，ΔD 介于 0.2901 和 0.5112 之间。而对于 RT 斜坡，ΔD 介于 0.4235 和 0.7626 之间。(3) 随着碾压侵蚀的演变，不同耕作坡面的水流模式由亚临界过渡流转变为超临界过渡流。(4) 土壤粗糙度指数和ΔD 与水动力参数具有良好的相关性。径流侵蚀能量越强，微地形的空间异质性越高。该研究有望为揭示坡耕地碾压侵蚀的水动力机制提供理论依据。
{"title":"Response of Hydrodynamic Characteristics to Tillage-Induced Microtopography of Rill Erosion Processes under Heavy Rainfalls","authors":"Shu-qin He, Jian Luo, Zicheng Zheng, Wenfeng Ding, Jigen Liu","doi":"10.3390/land13050685","DOIUrl":"https://doi.org/10.3390/land13050685","url":null,"abstract":"The occurrence and development of rill erosion depends on the hydraulic characteristics of water flow and underlying soil surface features. Our experiments include one-rainfall-intensity treatments (2.0 mm min−1) and various microtopographic levels based on different tillage practices with smooth slope (CK), artificial digging (AD), and ridge tillage (RT) on a 15° slope. The results indicate the following: (1) The soil roughness index values were in the order of CK < AD < RT, and the spatial variability of different tillage practices had strong autocorrelations during different rill erosive stages. The codomain values decreased with the increase in microtopography. (2) The multifractal dimension values of tillage practices in various erosive stages were in the order of RT > AD > CT. The microtopography of different tilled slopes showed strong multifractal characteristics, and the multifractal characteristics were stronger as the microrelief heterogeneity increased. For the CK slope, the generalized fractal dimension span (ΔD) ranged between 0.0019 and 0.0058. For the AD slope, ΔD was between 0.2901 and 0.5112. And, for the RT slope, ΔD was between 0.4235 and 0.7626. (3) With the evolution of rill erosion, the flow pattern on different tilled slopes changed from subcritical transition flow to supercritical transition flow. (4) Soil roughness index and ΔD had good correlations with hydrodynamic parameters. The stronger the erosive energy of runoff was, the higher the spatial heterogeneity of microtopography was. This study is expected to provide a theoretical basis for revealing the hydrodynamic mechanism of rill erosion in slope farmland.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980023","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}
Sanaa Fadil, Imane Sebari, Moulay Mohamed Ajerame, Rayhana Ajeddour, Ibtihal El Maghraoui, Kenza Ait El kadi, Yahya Zefri, Mouad Jabrane
Spatialization of biomass and carbon stocks is essential for a good understanding of the forest stand and its characteristics, especially in degraded Mediterranean cork oak forests. Furthermore, the analysis of biomass and carbon stock changes and dynamics is essential for understanding the carbon cycle, in particular carbon emissions and stocks, in order to make projections, especially in the context of climate change. In this research, we use a multidimensional framework integrating forest survey data, LiDAR UAV data, and extracted vegetation indices from Landsat imagery (NDVI, ARVI, CIG, etc.) to model and spatialize cork oak biomass and carbon stocks on a large scale. For this purpose, we explore the use of univariate and multivariate regression modeling and examine several types of regression, namely, multiple linear regression, stepwise linear regression, random forest regression, simple linear regression, logarithmic regression, and quadratic and cubic regression. The results show that for multivariate regression, stepwise regression gives good results, with R2 equal to 80% and 65% and RMSE equal to 2.59 and 1.52 Mg/ha for biomass and carbon stock, respectively. Random forest regression, chosen as the ML algorithm, gives acceptable results, explaining 80% and 60% of the variation in biomass and carbon stock, respectively, and an RMSE of 2.74 and 1.72 Mg/ha for biomass and carbon stock, respectively. For the univariate regression, the simple linear regression is chosen because it gives satisfactory results, close to those of the quadratic and cubic regressions, but with a simpler equation. The vegetation index chosen is ARVI, which shows good performance indices, close to those of the NDVI and CIG. The assessment of biomass and carbon stock changes in the study area over 35 years (1985–2020) showed a slight increase of less than 10 Mg/ha and a decrease in biomass and carbon stock over a large area.
{"title":"An Integrating Framework for Biomass and Carbon Stock Spatialization and Dynamics Assessment Using Unmanned Aerial Vehicle LiDAR (LiDAR UAV) Data, Landsat Imagery, and Forest Survey Data in the Mediterranean Cork Oak Forest of Maamora","authors":"Sanaa Fadil, Imane Sebari, Moulay Mohamed Ajerame, Rayhana Ajeddour, Ibtihal El Maghraoui, Kenza Ait El kadi, Yahya Zefri, Mouad Jabrane","doi":"10.3390/land13050688","DOIUrl":"https://doi.org/10.3390/land13050688","url":null,"abstract":"Spatialization of biomass and carbon stocks is essential for a good understanding of the forest stand and its characteristics, especially in degraded Mediterranean cork oak forests. Furthermore, the analysis of biomass and carbon stock changes and dynamics is essential for understanding the carbon cycle, in particular carbon emissions and stocks, in order to make projections, especially in the context of climate change. In this research, we use a multidimensional framework integrating forest survey data, LiDAR UAV data, and extracted vegetation indices from Landsat imagery (NDVI, ARVI, CIG, etc.) to model and spatialize cork oak biomass and carbon stocks on a large scale. For this purpose, we explore the use of univariate and multivariate regression modeling and examine several types of regression, namely, multiple linear regression, stepwise linear regression, random forest regression, simple linear regression, logarithmic regression, and quadratic and cubic regression. The results show that for multivariate regression, stepwise regression gives good results, with R2 equal to 80% and 65% and RMSE equal to 2.59 and 1.52 Mg/ha for biomass and carbon stock, respectively. Random forest regression, chosen as the ML algorithm, gives acceptable results, explaining 80% and 60% of the variation in biomass and carbon stock, respectively, and an RMSE of 2.74 and 1.72 Mg/ha for biomass and carbon stock, respectively. For the univariate regression, the simple linear regression is chosen because it gives satisfactory results, close to those of the quadratic and cubic regressions, but with a simpler equation. The vegetation index chosen is ARVI, which shows good performance indices, close to those of the NDVI and CIG. The assessment of biomass and carbon stock changes in the study area over 35 years (1985–2020) showed a slight increase of less than 10 Mg/ha and a decrease in biomass and carbon stock over a large area.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980829","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}
Recreational ecosystem services (RESs) are the subset of ecosystem services (ESs) that contribute to human society through recreation, recreation opportunities, and experiences. Existing RESs mostly focus on a single recreational landscape; alternatively, when mapping RESs, multiple types of landscapes are often drawn together, ignoring the differences in recreational landscape (RL) types and affecting the accuracy of the mapping. At the same time, quantifying the monetary value of RESs has been a challenge due to the lack of market substitutes that can approximate the prices associated with these non-excludable goods. This study used the MaxENT model, then classified and used recreational resource POI data, combined with environmental data on the existence or generation of different types of RL, mapped RES from the perspective of RL supply, and conducted monetization and evaluations of RL. The results show that the models’ AUC values are all greater than 0.7, and the distribution of RL supply can be drawn relatively accurately. The Qinghai–Tibet Plateau National Park Group (QTPNPG) has the largest high-quality geomorphic recreational landscape (69,081.02 km2), followed by a high-quality biological recreational landscape (59,348.65 km2) and a high-quality hydrological recreational landscape (33,251.20 km2). The national parks in the eastern part of the Qinghai–Tibet Plateau have a larger proportion of high-value areas of the RES. The total monetary value of the RES is CNY 8.323 billion, and the average monetary value of RES per unit area is CNY 20,200/km2. Our study optimizes the method of mapping RESs and provides a new way of quantifying the monetary value of RESs. The results can provide a reference for the recreational development of THE QTPNPG and its contribution to regional sustainable development.
{"title":"Recreational Ecosystem Services in the Qinghai–Tibet Plateau National Park Group: Mapping, Monetization, and Evaluation","authors":"Mengqi Yuan, Fang Han, Xuankai Ma, Tian Wang, Qixiang Liang","doi":"10.3390/land13050682","DOIUrl":"https://doi.org/10.3390/land13050682","url":null,"abstract":"Recreational ecosystem services (RESs) are the subset of ecosystem services (ESs) that contribute to human society through recreation, recreation opportunities, and experiences. Existing RESs mostly focus on a single recreational landscape; alternatively, when mapping RESs, multiple types of landscapes are often drawn together, ignoring the differences in recreational landscape (RL) types and affecting the accuracy of the mapping. At the same time, quantifying the monetary value of RESs has been a challenge due to the lack of market substitutes that can approximate the prices associated with these non-excludable goods. This study used the MaxENT model, then classified and used recreational resource POI data, combined with environmental data on the existence or generation of different types of RL, mapped RES from the perspective of RL supply, and conducted monetization and evaluations of RL. The results show that the models’ AUC values are all greater than 0.7, and the distribution of RL supply can be drawn relatively accurately. The Qinghai–Tibet Plateau National Park Group (QTPNPG) has the largest high-quality geomorphic recreational landscape (69,081.02 km2), followed by a high-quality biological recreational landscape (59,348.65 km2) and a high-quality hydrological recreational landscape (33,251.20 km2). The national parks in the eastern part of the Qinghai–Tibet Plateau have a larger proportion of high-value areas of the RES. The total monetary value of the RES is CNY 8.323 billion, and the average monetary value of RES per unit area is CNY 20,200/km2. Our study optimizes the method of mapping RESs and provides a new way of quantifying the monetary value of RESs. The results can provide a reference for the recreational development of THE QTPNPG and its contribution to regional sustainable development.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128352","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}
Natividad Miledy Alberto Then, Ramón Delanoy, Pedro Antonio Nuñez-Ramos, Oscar Díaz Rizo, Lizaira Bello
Heavy metal pollution in agricultural soils is one of the main problems in agricultural production worldwide, which threatens human health and the environment. To evaluate the pollution levels of heavy metals and the ecological risks in an agricultural area from Sánchez Ramírez Province, Dominican Republic, the concentration levels of heavy metals (Fe, Mn, Cr, Ni, Cu, Zn, Pb, and As) were measured using energy-dispersive X-ray fluorescence spectroscopy (EDXRF). Several pollution indices, including the geo-accumulation index (Igeo), enrichment factor (EF), and single pollution index (PI), were used to investigate the pollution status. The spatial distribution of different heavy metals in the studied soils was also determined. The mean concentrations of Fe, Mn, Cr, Ni, Cu, Zn, Pb, and As were 73735, 1616, 426; 34; 20; 200; 43; and 5 mg kg−1, respectively. These results indicated that the mean concentration of Cr, Cu, Zn, and Pb exceeded FAO-recommended levels for healthy agricultural soils. However, the potential ecological risks assessment indicated a low-risk status. The results obtained could help improve soil–rice–environment management practices and prevent heavy metal pollution in this type of production system, protecting the health of the local population and the environment.
农业土壤中的重金属污染是全球农业生产中的主要问题之一，威胁着人类健康和环境。为了评估多米尼加共和国桑切斯-拉米雷斯省农业区的重金属污染水平和生态风险，使用能量色散 X 射线荧光光谱法（EDXRF）测量了重金属（铁、锰、铬、镍、铜、锌、铅和砷）的浓度水平。采用了多种污染指数（包括地理累积指数（Igeo）、富集因子（EF）和单一污染指数（PI））来研究污染状况。此外，还测定了研究土壤中不同重金属的空间分布。铁、锰、铬、镍、铜、锌、铅和砷的平均浓度分别为 73735、1616、426、34、20、200、43 和 5 毫克/千克。这些结果表明，铬、铜、锌和铅的平均浓度超过了联合国粮农组织对健康农业土壤的建议水平。不过，潜在生态风险评估显示其处于低风险状态。这些结果有助于改进土壤-水稻-环境管理方法，防止此类生产系统中的重金属污染，保护当地居民的健康和环境。
{"title":"Assessment of Soil Heavy Metal Pollution and the Ecological Risk in an Agricultural Area from Sánchez Ramírez Province, Dominican Republic","authors":"Natividad Miledy Alberto Then, Ramón Delanoy, Pedro Antonio Nuñez-Ramos, Oscar Díaz Rizo, Lizaira Bello","doi":"10.3390/land13050684","DOIUrl":"https://doi.org/10.3390/land13050684","url":null,"abstract":"Heavy metal pollution in agricultural soils is one of the main problems in agricultural production worldwide, which threatens human health and the environment. To evaluate the pollution levels of heavy metals and the ecological risks in an agricultural area from Sánchez Ramírez Province, Dominican Republic, the concentration levels of heavy metals (Fe, Mn, Cr, Ni, Cu, Zn, Pb, and As) were measured using energy-dispersive X-ray fluorescence spectroscopy (EDXRF). Several pollution indices, including the geo-accumulation index (Igeo), enrichment factor (EF), and single pollution index (PI), were used to investigate the pollution status. The spatial distribution of different heavy metals in the studied soils was also determined. The mean concentrations of Fe, Mn, Cr, Ni, Cu, Zn, Pb, and As were 73735, 1616, 426; 34; 20; 200; 43; and 5 mg kg−1, respectively. These results indicated that the mean concentration of Cr, Cu, Zn, and Pb exceeded FAO-recommended levels for healthy agricultural soils. However, the potential ecological risks assessment indicated a low-risk status. The results obtained could help improve soil–rice–environment management practices and prevent heavy metal pollution in this type of production system, protecting the health of the local population and the environment.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140979334","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}
Zhaoyu Zhou, Fan Yang, Jiayu Li, Jiale Li, Zhuojun Zou
To alleviate the contradiction between high-density urban spatial environments and high-frequency citizens’ activities, it is vital to determine the degree of openness of waterfront space, figure out the matching relationship between spatial openness and vitality intensity, identify imbalanced spatial zones and divide the order of intervention, and compensate for the limitations of subjective judgment in traditional planning decisions. This paper uses the Changsha Xiangjiang River waterfront space as a research sample based on multi-source data. It constructs the evaluation indicators system and research framework for the degree of openness of waterfront space. Then, by evaluating the openness and vitality intensity of the waterfront space and adopting the quadrant division method, waterfront space zones with a mismatched openness and vitality intensity were identified. Finally, planning interventions are prioritized based on a priority index. The results show the following: (1) The openness and vitality of the waterfront space of Xiangjiang River show the spatial distribution characteristics of “high in the middle and low in the north and south” and “high on the east bank and low on the west bank”. (2) Fifteen low-quality waterfront spatial zones with “low vitality intensity and low openness” and one with a severe imbalance of “low openness–high vitality intensity” were identified. These waterfront spatial zones cannot meet the requirements for the high-quality development of waterfront space. (3) The study delineates five priority levels for planning interventions. Among them, three waterfront space zones belong to priority V, mainly distributed north and south of the Xiangjiang River. Five waterfront spatial zones belonging to priority IV are concentrated in the middle of the Xiangjiang River. The above areas need to be prioritized for improvement to accurately promote the overall balanced development of the waterfront space.
{"title":"Identification of Critical Areas of Openness–Vitality Intensity Imbalance in Waterfront Spaces and Prioritization of Interventions: A Case Study of Xiangjiang River in Changsha, China","authors":"Zhaoyu Zhou, Fan Yang, Jiayu Li, Jiale Li, Zhuojun Zou","doi":"10.3390/land13050686","DOIUrl":"https://doi.org/10.3390/land13050686","url":null,"abstract":"To alleviate the contradiction between high-density urban spatial environments and high-frequency citizens’ activities, it is vital to determine the degree of openness of waterfront space, figure out the matching relationship between spatial openness and vitality intensity, identify imbalanced spatial zones and divide the order of intervention, and compensate for the limitations of subjective judgment in traditional planning decisions. This paper uses the Changsha Xiangjiang River waterfront space as a research sample based on multi-source data. It constructs the evaluation indicators system and research framework for the degree of openness of waterfront space. Then, by evaluating the openness and vitality intensity of the waterfront space and adopting the quadrant division method, waterfront space zones with a mismatched openness and vitality intensity were identified. Finally, planning interventions are prioritized based on a priority index. The results show the following: (1) The openness and vitality of the waterfront space of Xiangjiang River show the spatial distribution characteristics of “high in the middle and low in the north and south” and “high on the east bank and low on the west bank”. (2) Fifteen low-quality waterfront spatial zones with “low vitality intensity and low openness” and one with a severe imbalance of “low openness–high vitality intensity” were identified. These waterfront spatial zones cannot meet the requirements for the high-quality development of waterfront space. (3) The study delineates five priority levels for planning interventions. Among them, three waterfront space zones belong to priority V, mainly distributed north and south of the Xiangjiang River. Five waterfront spatial zones belonging to priority IV are concentrated in the middle of the Xiangjiang River. The above areas need to be prioritized for improvement to accurately promote the overall balanced development of the waterfront space.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140981614","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}
Achieving the goal of integrated urban–rural development is to achieve a spatially balanced development of the constituent elements of urban–rural relations in China. Rural populations and land dedicated to construction are the main components of the countryside in traditional agricultural areas; they play an important role in the development of the countryside itself in terms of urban and rural land use and in the formation of urban and rural development patterns. This study analyzes the spatial and temporal changes in rural populations and construction land at the township level, alongside assessing various forms and the extent of coupled development. Herein, we consider the role of urban–rural attractiveness and propose a framework for relationships between urban and rural development based on different forms of coupled development; a model of urban–rural forces is constructed to determine spatial patterns of urban–rural development at the township level that may transpire in the future. Our study shows that the rural population and construction land in the study area are characterized by significant spatial and temporal dynamics, indicating that traditional rural areas are in a process of rapid development and change. The results of our measurements of township-level coupling indicate that there exist four development patterns within urban–rural development: the A-type is most likely to produce new cities or satellite towns in the future and form new urban areas; the B-type is the area most likely to cease and be annexed to other villages or cities to meet building targets; the C-type comprises areas to be focused on in the future to attract populations and strictly control the growth of rural construction land areas (to avoid land transforming into the B-type); and the D-type refers to lands upon which regional township centers may develop in the future, becoming an area devoted to rural revitalization. The A-type and D-type are prioritized for the allocation of construction land, which can be contracted from types B and C. The results of this study have provided important reference for the formulation of population and construction land control policies in accordance with local conditions and the realization of integrated urban and rural development strategies.
实现城乡一体化发展的目标，就是要实现中国城乡关系构成要素在空间上的均衡发展。农村人口和建设用地是传统农业地区农村的主要构成要素，对城乡土地利用和城乡发展格局的形成具有重要作用。本研究分析了乡镇一级农村人口和建设用地的时空变化，同时评估了耦合发展的各种形式和程度。在此，我们考虑了城乡吸引力的作用，提出了基于不同耦合发展形式的城乡发展关系框架；构建了城乡力量模型，以确定未来可能出现的乡镇层面的城乡发展空间模式。研究表明，研究区域的农村人口和建设用地具有显著的时空动态特征，表明传统农村地区正处于快速发展和变化的过程中。我们对乡镇层面耦合的测量结果表明，城乡发展存在四种发展模式：A 型是未来最有可能产生新城或卫星城，形成新城区的区域；B 型是为完成建设指标，最有可能停止建设并被其他村庄或城市兼并的区域；C 型是未来重点吸引人口，严格控制农村建设用地增长的区域（避免土地向 B 型转变）；D 型是指未来可能发展区域性乡镇中心的土地，成为乡村振兴的专门区域。研究成果为因地制宜制定人口和建设用地调控政策、实现城乡一体化发展战略提供了重要参考。
{"title":"Coupling of Changing Trends in Population and Construction Land in Traditional Rural Areas and Spatial Patterns in Urban–Rural Development, 2016–2021: A Case Study of Heilongjiang Province, China","authors":"Jia Lin, Guoming Du, Ying Zhang, Xiaoyang Yu","doi":"10.3390/land13050683","DOIUrl":"https://doi.org/10.3390/land13050683","url":null,"abstract":"Achieving the goal of integrated urban–rural development is to achieve a spatially balanced development of the constituent elements of urban–rural relations in China. Rural populations and land dedicated to construction are the main components of the countryside in traditional agricultural areas; they play an important role in the development of the countryside itself in terms of urban and rural land use and in the formation of urban and rural development patterns. This study analyzes the spatial and temporal changes in rural populations and construction land at the township level, alongside assessing various forms and the extent of coupled development. Herein, we consider the role of urban–rural attractiveness and propose a framework for relationships between urban and rural development based on different forms of coupled development; a model of urban–rural forces is constructed to determine spatial patterns of urban–rural development at the township level that may transpire in the future. Our study shows that the rural population and construction land in the study area are characterized by significant spatial and temporal dynamics, indicating that traditional rural areas are in a process of rapid development and change. The results of our measurements of township-level coupling indicate that there exist four development patterns within urban–rural development: the A-type is most likely to produce new cities or satellite towns in the future and form new urban areas; the B-type is the area most likely to cease and be annexed to other villages or cities to meet building targets; the C-type comprises areas to be focused on in the future to attract populations and strictly control the growth of rural construction land areas (to avoid land transforming into the B-type); and the D-type refers to lands upon which regional township centers may develop in the future, becoming an area devoted to rural revitalization. The A-type and D-type are prioritized for the allocation of construction land, which can be contracted from types B and C. The results of this study have provided important reference for the formulation of population and construction land control policies in accordance with local conditions and the realization of integrated urban and rural development strategies.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980532","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}
Agricultural activities are the second largest source of greenhouse gas emissions, and carbon emissions from agricultural land use (CEALU) have become a hot issue across the world. Although there are some studies on the impact of high-standard farmland construction policies on carbon emissions, they focus on quantitative analysis and do not give sufficient consideration to the relationship between HSFC and CEALU. Therefore, in this study, by relying on provincial panel data of China for the period 2005–2017, the effect of the high-standard basic farmland construction policy on carbon emissions from agricultural land use per unit area and its regional differences were quantitatively analyzed using the difference-in-difference (DID) model. The results showed that: (1) China’s CEALU per unit area presented a fluctuating upward change, but the growth rate slowed down during the period 2005–2017, from 392.58 kg/ha to 457.72 kg/ha, with an average annual growth rate of 1.31%; (2) the high-standard farmland construction (HSFC) policy led a significant carbon emission reduction effect in agricultural land use and reduced the CEALU per unit area by 10.80% on average. With the promotion of this policy, its carbon emission reduction effect in agricultural land use presented an overall increasing change; (3) the carbon emission reduction effect of the high-standard farmland construction policy in agricultural land use was significant in central China, but non-significant in eastern China and western China.
{"title":"The Impact of High-Standard Farmland Construction Policies on the Carbon Emissions from Agricultural Land Use (CEALU)","authors":"Fangsheng Liu, Jian Lin","doi":"10.3390/land13050672","DOIUrl":"https://doi.org/10.3390/land13050672","url":null,"abstract":"Agricultural activities are the second largest source of greenhouse gas emissions, and carbon emissions from agricultural land use (CEALU) have become a hot issue across the world. Although there are some studies on the impact of high-standard farmland construction policies on carbon emissions, they focus on quantitative analysis and do not give sufficient consideration to the relationship between HSFC and CEALU. Therefore, in this study, by relying on provincial panel data of China for the period 2005–2017, the effect of the high-standard basic farmland construction policy on carbon emissions from agricultural land use per unit area and its regional differences were quantitatively analyzed using the difference-in-difference (DID) model. The results showed that: (1) China’s CEALU per unit area presented a fluctuating upward change, but the growth rate slowed down during the period 2005–2017, from 392.58 kg/ha to 457.72 kg/ha, with an average annual growth rate of 1.31%; (2) the high-standard farmland construction (HSFC) policy led a significant carbon emission reduction effect in agricultural land use and reduced the CEALU per unit area by 10.80% on average. With the promotion of this policy, its carbon emission reduction effect in agricultural land use presented an overall increasing change; (3) the carbon emission reduction effect of the high-standard farmland construction policy in agricultural land use was significant in central China, but non-significant in eastern China and western China.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140985325","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}
Yuanjie Deng, Lu Ming, Yifeng Hai, Hang Chen, Dingdi Jize, Ji Luo, Xiaohan Yan, Xiaolong Zhang, Shunbo Yao, Mengyang Hou
China’s National Key Ecological Function Zones (NKEFZs) currently represent the largest and most extensive ecological conservation policy in China, with one of the core objectives of this policy being to improve eco-environmental quality (EEQ). This study regards the establishment of NKEFZs as a quasi-natural experiment. Based on panel data from 130 counties in Sichuan Province from 2001 to 2021, a multi-period difference-in-differences (DID) model was employed to evaluate the impact of NKEFZ establishment on EEQ. The findings indicate the following: ① The establishment of NKEFZs can significantly enhance the EEQ of the covered areas, albeit as a gradual long-term process. This conclusion not only meets the parallel-trends assumption but also holds true in a series of robustness tests such as placebo tests. ② Mechanism analysis reveals that NKEFZs can enhance EEQ through the effects of optimizing land spatial allocation and upgrading industrial structure. ③ Heterogeneity analysis demonstrates that the beneficial effect of NKEFZs on EEQ varies across different functional zone types, geographic spaces and ethnic regions. Our study not only contributes to the accumulation of empirical evidence and institutional refinement in the sustainable implementation of ecological policies in China but also offers valuable insights and references for other countries in formulating policies for eco-environmental protection.
{"title":"Has the Establishment of National Key Ecological Function Zones Improved Eco-Environmental Quality?—Evidence from a Quasi-Natural Experiment in 130 Counties in Sichuan Province, China","authors":"Yuanjie Deng, Lu Ming, Yifeng Hai, Hang Chen, Dingdi Jize, Ji Luo, Xiaohan Yan, Xiaolong Zhang, Shunbo Yao, Mengyang Hou","doi":"10.3390/land13050677","DOIUrl":"https://doi.org/10.3390/land13050677","url":null,"abstract":"China’s National Key Ecological Function Zones (NKEFZs) currently represent the largest and most extensive ecological conservation policy in China, with one of the core objectives of this policy being to improve eco-environmental quality (EEQ). This study regards the establishment of NKEFZs as a quasi-natural experiment. Based on panel data from 130 counties in Sichuan Province from 2001 to 2021, a multi-period difference-in-differences (DID) model was employed to evaluate the impact of NKEFZ establishment on EEQ. The findings indicate the following: ① The establishment of NKEFZs can significantly enhance the EEQ of the covered areas, albeit as a gradual long-term process. This conclusion not only meets the parallel-trends assumption but also holds true in a series of robustness tests such as placebo tests. ② Mechanism analysis reveals that NKEFZs can enhance EEQ through the effects of optimizing land spatial allocation and upgrading industrial structure. ③ Heterogeneity analysis demonstrates that the beneficial effect of NKEFZs on EEQ varies across different functional zone types, geographic spaces and ethnic regions. Our study not only contributes to the accumulation of empirical evidence and institutional refinement in the sustainable implementation of ecological policies in China but also offers valuable insights and references for other countries in formulating policies for eco-environmental protection.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140983160","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}
Xin Nie, Hubin Ma, Sihan Chen, Kailu Li, Zhenhan Yu, Han Wang, Zhuxia Wei
Energy distribution justice is of primary concern within the energy justice framework and it is crucial to increase public acceptance of offshore wind energy and further advance its development. The rapid development of offshore wind energy in China has inevitably impacted the livelihoods of coastal vulnerable groups (CVGs) engaged in fisheries and tourism in the coastal zone. While current policies often compensate for livelihood losses through cash payments, the fiscal strain caused by COVID-19 renders this approach unsustainable. Consequently, this research pioneers the exploration of Chinese tourist groups’ landscape preferences towards offshore wind farms (OWFs). This study proposes a new approach to enhance OWF landscapes for tourism development, thereby balancing the distribution of costs and benefits between CVGs and tourists. The research focuses on Beihai City in the Beibu Gulf Economic Region, utilizing a combination of Q-methodology and choice experiments that incorporates cut-offs. Answers to eighty Q-methodology questionnaires and 1324 choice experiment questionnaires are obtained. The findings indicate that this region can achieve energy distribution justice by compensating for the livelihood losses of CVGs through tourism. Contrary to traditional assumptions about wind farm noise preferences, Chinese tourists prefer proximity to OWFs, as an appropriate coastal acoustics landscape can enhance their tourism experience. In light of these findings, this paper presents policy recommendations towards energy distribution justice.
{"title":"Offshore Wind Farms and Tourism Development Relationship to Energy Distribution Justice for the Beibu Gulf, China","authors":"Xin Nie, Hubin Ma, Sihan Chen, Kailu Li, Zhenhan Yu, Han Wang, Zhuxia Wei","doi":"10.3390/land13050678","DOIUrl":"https://doi.org/10.3390/land13050678","url":null,"abstract":"Energy distribution justice is of primary concern within the energy justice framework and it is crucial to increase public acceptance of offshore wind energy and further advance its development. The rapid development of offshore wind energy in China has inevitably impacted the livelihoods of coastal vulnerable groups (CVGs) engaged in fisheries and tourism in the coastal zone. While current policies often compensate for livelihood losses through cash payments, the fiscal strain caused by COVID-19 renders this approach unsustainable. Consequently, this research pioneers the exploration of Chinese tourist groups’ landscape preferences towards offshore wind farms (OWFs). This study proposes a new approach to enhance OWF landscapes for tourism development, thereby balancing the distribution of costs and benefits between CVGs and tourists. The research focuses on Beihai City in the Beibu Gulf Economic Region, utilizing a combination of Q-methodology and choice experiments that incorporates cut-offs. Answers to eighty Q-methodology questionnaires and 1324 choice experiment questionnaires are obtained. The findings indicate that this region can achieve energy distribution justice by compensating for the livelihood losses of CVGs through tourism. Contrary to traditional assumptions about wind farm noise preferences, Chinese tourists prefer proximity to OWFs, as an appropriate coastal acoustics landscape can enhance their tourism experience. In light of these findings, this paper presents policy recommendations towards energy distribution justice.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140983503","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}
Large-scale management is the key to realizing long-term agricultural growth in smallholder countries. Land-scale management and service-scale management are two forms of agricultural large-scale management. The former is committed to changing the small-scale management pattern, but the latter tends to maintain it. There has been a lack of discussion and controversy about the relationship between the two. From the perspective of market maturity, this paper explores whether the two are complementary or mutually exclusive and how their complementary or mutually exclusive relationship affects agricultural green productivity. The results show the following: Land-scale management and service-scale management are complementary, not superficially contradictory. The benign interaction between the two has a consistent improvement effect on green productivity in both the short and long term, which has spatial spillovers appearing in the long term. The reasons are as follows: The farmland rental market can reverse the inhibitory effect of the current low-maturity outsourcing services market on green productivity. The outsourcing services market can delay the arrival of the inflection point beyond which expansion of farmland rental transactions reduces green productivity, and amplify the positive effect of farmland rental on it. Although the degree of benign interaction between the two forms of large-scale management has gradually increased in recent years, it is still low overall. Agricultural large-scale management in China is still in the stage driven by land-scale management. Smallholder countries such as China need not worry prematurely about which large-scale management path to take, and they should treat both forms of large-scale management with an equal perspective to accelerate the high-level interaction between them.
{"title":"Farmland Rental Market, Outsourcing Services Market and Agricultural Green Productivity: Implications for Multiple Forms of Large-Scale Management","authors":"Heng Zhang, Xiangyu Guo","doi":"10.3390/land13050676","DOIUrl":"https://doi.org/10.3390/land13050676","url":null,"abstract":"Large-scale management is the key to realizing long-term agricultural growth in smallholder countries. Land-scale management and service-scale management are two forms of agricultural large-scale management. The former is committed to changing the small-scale management pattern, but the latter tends to maintain it. There has been a lack of discussion and controversy about the relationship between the two. From the perspective of market maturity, this paper explores whether the two are complementary or mutually exclusive and how their complementary or mutually exclusive relationship affects agricultural green productivity. The results show the following: Land-scale management and service-scale management are complementary, not superficially contradictory. The benign interaction between the two has a consistent improvement effect on green productivity in both the short and long term, which has spatial spillovers appearing in the long term. The reasons are as follows: The farmland rental market can reverse the inhibitory effect of the current low-maturity outsourcing services market on green productivity. The outsourcing services market can delay the arrival of the inflection point beyond which expansion of farmland rental transactions reduces green productivity, and amplify the positive effect of farmland rental on it. Although the degree of benign interaction between the two forms of large-scale management has gradually increased in recent years, it is still low overall. Agricultural large-scale management in China is still in the stage driven by land-scale management. Smallholder countries such as China need not worry prematurely about which large-scale management path to take, and they should treat both forms of large-scale management with an equal perspective to accelerate the high-level interaction between them.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140982907","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：