Lulu Chen, Hong Leng, Jian Dai, Yi Liu, Ziqing Yuan
To address current ecological issues and a lack of historical preservation in Beijing’s waterfront, it has become necessary to establish an urban design project that optimizes these aspects. This study focuses on “Beijing’s Waterfront Overall Urban Design,” a project that integrates government requirements with Beijing’s waterfront urban design characteristics and problems to establish an urban layer system from two dimensions: historical and ecological. It explores how the urban layer system can be applied to Beijing’s overall waterfront urban design, from investigation to evaluation, analysis, visualization, and strategy development. First, an urban layer system for Beijing’s waterfront was established from a historical perspective, based on urban setting and construction stages and space utilization, referring to the literature and field surveys. The evolution of urban layers of waterbodies, the water–city relationship, and water functions was systematically analyzed. Second, an urban layer system was established for the ecological dimension of Beijing’s waterfront based on a literature review, expert interviews, and analytic hierarchy process methods. It included four urban layers: waterbody, greening, shoreline, and ecological function. The quality of the ecological urban design of 54 waterfront reaches in Beijing was evaluated using questionnaires and field surveys. Third, a series of urban layer maps was generated using the mapping method. Finally, urban design strategies were developed based on the combined historical and ecological characteristics and problems of Beijing’s waterfront. The results of this study and the concept of an urban layer system for waterfront urban design can benefit waterfront urban design projects and future studies.
{"title":"Urban Waterfront Regeneration on Ecological and Historical Dimensions: Insight from a Unique Case in Beijing, China","authors":"Lulu Chen, Hong Leng, Jian Dai, Yi Liu, Ziqing Yuan","doi":"10.3390/land13050674","DOIUrl":"https://doi.org/10.3390/land13050674","url":null,"abstract":"To address current ecological issues and a lack of historical preservation in Beijing’s waterfront, it has become necessary to establish an urban design project that optimizes these aspects. This study focuses on “Beijing’s Waterfront Overall Urban Design,” a project that integrates government requirements with Beijing’s waterfront urban design characteristics and problems to establish an urban layer system from two dimensions: historical and ecological. It explores how the urban layer system can be applied to Beijing’s overall waterfront urban design, from investigation to evaluation, analysis, visualization, and strategy development. First, an urban layer system for Beijing’s waterfront was established from a historical perspective, based on urban setting and construction stages and space utilization, referring to the literature and field surveys. The evolution of urban layers of waterbodies, the water–city relationship, and water functions was systematically analyzed. Second, an urban layer system was established for the ecological dimension of Beijing’s waterfront based on a literature review, expert interviews, and analytic hierarchy process methods. It included four urban layers: waterbody, greening, shoreline, and ecological function. The quality of the ecological urban design of 54 waterfront reaches in Beijing was evaluated using questionnaires and field surveys. Third, a series of urban layer maps was generated using the mapping method. Finally, urban design strategies were developed based on the combined historical and ecological characteristics and problems of Beijing’s waterfront. The results of this study and the concept of an urban layer system for waterfront urban design can benefit waterfront urban design projects and future studies.","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":"140984653","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}
Various methods for evaluating the visual quality of landscapes have been continuously studied. In the era of the rapid development of big data, methods to obtain evaluation data efficiently and accurately have received attention. However, few studies have been conducted to optimize the evaluation methods for landscape visual quality. Here, we aim to develop an evaluation model that is model fine-tuned using Scenic Beauty Evaluation (SBE) results. In elucidating the methodology, it is imperative to delve into the intricacies of refining the evaluation process. First, fine-tuning the model can be initiated with a scoring test on a small population, serving as an efficient starting point. Second, determining the optimal hyperparameter settings necessitates establishing intervals within a threshold range tailored to the characteristics of the dataset. Third, from the pool of fine-tuned models, selecting the one exhibiting optimal performance is crucial for accurately predicting the visual quality of the landscape within the study population. Lastly, through the interpolation process, discernible differences in landscape aesthetics within the core monitoring area can be visually distinguished, thereby reinforcing the reliability and practicality of the new method. In order to demonstrate the efficiency and practicality of the new method, we chose the core section of the famous Beijing–Hangzhou Grand Canal in Wujiang District, China, as a case study. The results show the following: (1) Fine-tuning the model can start with a scoring test on a small population. (2) The optimal hyperparameter setting intervals of the model need to be set in a threshold range according to different dataset characteristics. (3) The model with optimal performance is selected among the four fine-tuning models for predicting the visual quality of the landscape in the study population. (4) After the interpolation process, the differences in landscape aesthetics within the core monitoring area can be visually distinguished. We believe that the new method is efficient, accurate, and practically applicable for improving landscape visual quality evaluation.
{"title":"A New Approach to Landscape Visual Quality Assessment from a Fine-Tuning Perspective","authors":"Rong Fan, Yingze Chen, Ken P. Yocom","doi":"10.3390/land13050673","DOIUrl":"https://doi.org/10.3390/land13050673","url":null,"abstract":"Various methods for evaluating the visual quality of landscapes have been continuously studied. In the era of the rapid development of big data, methods to obtain evaluation data efficiently and accurately have received attention. However, few studies have been conducted to optimize the evaluation methods for landscape visual quality. Here, we aim to develop an evaluation model that is model fine-tuned using Scenic Beauty Evaluation (SBE) results. In elucidating the methodology, it is imperative to delve into the intricacies of refining the evaluation process. First, fine-tuning the model can be initiated with a scoring test on a small population, serving as an efficient starting point. Second, determining the optimal hyperparameter settings necessitates establishing intervals within a threshold range tailored to the characteristics of the dataset. Third, from the pool of fine-tuned models, selecting the one exhibiting optimal performance is crucial for accurately predicting the visual quality of the landscape within the study population. Lastly, through the interpolation process, discernible differences in landscape aesthetics within the core monitoring area can be visually distinguished, thereby reinforcing the reliability and practicality of the new method. In order to demonstrate the efficiency and practicality of the new method, we chose the core section of the famous Beijing–Hangzhou Grand Canal in Wujiang District, China, as a case study. The results show the following: (1) Fine-tuning the model can start with a scoring test on a small population. (2) The optimal hyperparameter setting intervals of the model need to be set in a threshold range according to different dataset characteristics. (3) The model with optimal performance is selected among the four fine-tuning models for predicting the visual quality of the landscape in the study population. (4) After the interpolation process, the differences in landscape aesthetics within the core monitoring area can be visually distinguished. We believe that the new method is efficient, accurate, and practically applicable for improving landscape visual quality evaluation.","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":"140982824","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}
Nanling Mountain region is a typical southern hilly region, which plays an important ecological and environmental protection role in China’s overall land protection pattern. Based on the remote sensing image data of Longnan City in Nanling Mountain region in 2013, 2018 and 2023, this paper interpreted the land use type and analyzed the land use transfer situation by using land use transfer flow, and a land use transfer matrix. At the same time, based on the remote sensing ecological index (RSEI) model, the ecological environmental quality of Longnan City from 2013 to 2023 was retrieved. The temporal and spatial response model of the ecological environmental quality to land use transfer in Longnan City from 2013 to 2023 was discussed based on spatial autocorrelation and a geographical detector. The results show that from 2013 to 2023, the decrease of forest land (16.23 km2) and the increase of construction land (13.25 km2) were the main land use transfers in Longnan City. The ecological environment indexes of Longnan City in 2013, 2018 and 2023 were 0.789, 0.917 and 0.872, respectively, showing a trend of “first rising and then decreasing”. The ecological environmental quality in the north of Longnan City was significantly lower than that in the south, and the poor ecological quality area appeared in and around the northern main urban area, showing a trend of “inward contraction”. Forest land, garden land, grassland, cultivated land and water area have a positive impact on ecological environmental quality, while traffic land, construction land and other land have a negative impact on ecological environmental quality. The response of ecological environmental quality to different land use transfer modes is related to the change of the overall ecological environmental quality. The interaction between land use and land cover change (LUCC) and other factors had a great impact on the evolution of ecological environmental quality in Longnan City.
{"title":"Temporal and Spatial Response of Ecological Environmental Quality to Land Use Transfer in Nanling Mountain Region, China Based on RSEI: A Case Study of Longnan City","authors":"Qiulin Xiong, Qingwen Hong, Wenbo Chen","doi":"10.3390/land13050675","DOIUrl":"https://doi.org/10.3390/land13050675","url":null,"abstract":"Nanling Mountain region is a typical southern hilly region, which plays an important ecological and environmental protection role in China’s overall land protection pattern. Based on the remote sensing image data of Longnan City in Nanling Mountain region in 2013, 2018 and 2023, this paper interpreted the land use type and analyzed the land use transfer situation by using land use transfer flow, and a land use transfer matrix. At the same time, based on the remote sensing ecological index (RSEI) model, the ecological environmental quality of Longnan City from 2013 to 2023 was retrieved. The temporal and spatial response model of the ecological environmental quality to land use transfer in Longnan City from 2013 to 2023 was discussed based on spatial autocorrelation and a geographical detector. The results show that from 2013 to 2023, the decrease of forest land (16.23 km2) and the increase of construction land (13.25 km2) were the main land use transfers in Longnan City. The ecological environment indexes of Longnan City in 2013, 2018 and 2023 were 0.789, 0.917 and 0.872, respectively, showing a trend of “first rising and then decreasing”. The ecological environmental quality in the north of Longnan City was significantly lower than that in the south, and the poor ecological quality area appeared in and around the northern main urban area, showing a trend of “inward contraction”. Forest land, garden land, grassland, cultivated land and water area have a positive impact on ecological environmental quality, while traffic land, construction land and other land have a negative impact on ecological environmental quality. The response of ecological environmental quality to different land use transfer modes is related to the change of the overall ecological environmental quality. The interaction between land use and land cover change (LUCC) and other factors had a great impact on the evolution of ecological environmental quality in Longnan City.","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":"140983905","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}
Cultivated land plays a crucial role as the basis of grain production, and it is essential to effectively manage the unregulated expansion of non-grain production (NGP) on cultivated land in order to safeguard food security. The study of NGP has garnered significant attention from scholars, but the prediction of NGP trends is relatively uncommon. Therefore, we focused on Jiangsu Province, a significant grain production region in China, as the study area. We extracted data on cultivated land for non-grain production (NGPCL) in 2000, 2005, 2010, 2015, and 2019, and calculated the ratio of non-grain production (NGPR) for each county unit in the province. On this basis, Kernel Density Estimation (KDE) and spatial autocorrelation analysis tools were utilized to uncover the spatio-temporal evolution of NGP in Jiangsu Province. Finally, the Patch-Generating Land Use Simulation (PLUS) model was utilized to predict the trend of NGP in Jiangsu Province in 2038 under the three development scenarios of natural development (NDS), cultivated land protection (CPS), and food security (FSS). After analyzing the results, we came to the following conclusions:(1) During the period of 2000–2019, the NGPCL area and NGPR in Jiangsu Province exhibited a general decreasing trend. (2) The level of NGP displayed a spatial distribution pattern of being “higher in the south and central and lower in the north”. (3) The results of multi-scenario simulation show that under the NDS, the area of NGPCL and cultivated land for grain production (GPCL) decreases significantly; under the CPS, the decrease in NGPCL and GPCL is smaller than that of the NDS. Under the FSS, NGPCL decreases, while GPCL increases. These results can provide reference for the implementation of land use planning, the delineation of the cultivated land protection bottom line, and the implementation of thee cultivated land use control system in the study area.
{"title":"Spatio-Temporal Evolution and Multi-Scenario Simulation of Non-Grain Production on Cultivated Land in Jiangsu Province, China","authors":"Chengge Jiang, Lingzhi Wang, Wenhua Guo, Huiling Chen, Anqi Liang, Mingying Sun, Xinyao Li, Hichem Omrani","doi":"10.3390/land13050670","DOIUrl":"https://doi.org/10.3390/land13050670","url":null,"abstract":"Cultivated land plays a crucial role as the basis of grain production, and it is essential to effectively manage the unregulated expansion of non-grain production (NGP) on cultivated land in order to safeguard food security. The study of NGP has garnered significant attention from scholars, but the prediction of NGP trends is relatively uncommon. Therefore, we focused on Jiangsu Province, a significant grain production region in China, as the study area. We extracted data on cultivated land for non-grain production (NGPCL) in 2000, 2005, 2010, 2015, and 2019, and calculated the ratio of non-grain production (NGPR) for each county unit in the province. On this basis, Kernel Density Estimation (KDE) and spatial autocorrelation analysis tools were utilized to uncover the spatio-temporal evolution of NGP in Jiangsu Province. Finally, the Patch-Generating Land Use Simulation (PLUS) model was utilized to predict the trend of NGP in Jiangsu Province in 2038 under the three development scenarios of natural development (NDS), cultivated land protection (CPS), and food security (FSS). After analyzing the results, we came to the following conclusions:(1) During the period of 2000–2019, the NGPCL area and NGPR in Jiangsu Province exhibited a general decreasing trend. (2) The level of NGP displayed a spatial distribution pattern of being “higher in the south and central and lower in the north”. (3) The results of multi-scenario simulation show that under the NDS, the area of NGPCL and cultivated land for grain production (GPCL) decreases significantly; under the CPS, the decrease in NGPCL and GPCL is smaller than that of the NDS. Under the FSS, NGPCL decreases, while GPCL increases. These results can provide reference for the implementation of land use planning, the delineation of the cultivated land protection bottom line, and the implementation of thee cultivated land use control system in the study area.","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":"140982982","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 study of urban land use efficiency is of great significance for optimizing the spatial allocation of urban land, thereby promoting the intensive use of urban land and the transformation of economic development modes. Taking the Yangtze River Economic Belt (YREB) as the study object, we chose the undesirable Slacks-Based Measure (SBM) model to calculate the urban land use efficiency (ULUE). Then, we utilized the spatial correlation analysis and econometric methods to discuss its spatio-temporal features and influential factors. The results show the following: (1) The urban land use efficiency in the YREB steadily improved from 2010 to 2022, but the inter-regional efficiency gap evidently increased. (2) There is an efficiency value to be found in a multi-center network structure, and it forms a “core-periphery” distribution pattern. The high-efficiency areas in the downstream and upstream regions of the YREB are gradually increasing, while the efficiency value in the midstream area remains low. (3) The urban efficiency values have strong correlation, and they are mainly “High-High agglomeration” and “Low-Low agglomeration”, and they show significant regional characteristics. (4) The economic level, industrial structure, and urbanization have obvious motivating effects on ULUE, and the positive spatial spillover effect is clear. The foreign direct investment and land finance hinder the boost of efficiency, and the latter has a negative spatial spillover role on the ULUE in the downstream cities.
{"title":"Evaluation and Influential Factors of Urban Land Use Efficiency in Yangtze River Economic Belt","authors":"Dongqing Han, Zhengxu Cao","doi":"10.3390/land13050671","DOIUrl":"https://doi.org/10.3390/land13050671","url":null,"abstract":"The study of urban land use efficiency is of great significance for optimizing the spatial allocation of urban land, thereby promoting the intensive use of urban land and the transformation of economic development modes. Taking the Yangtze River Economic Belt (YREB) as the study object, we chose the undesirable Slacks-Based Measure (SBM) model to calculate the urban land use efficiency (ULUE). Then, we utilized the spatial correlation analysis and econometric methods to discuss its spatio-temporal features and influential factors. The results show the following: (1) The urban land use efficiency in the YREB steadily improved from 2010 to 2022, but the inter-regional efficiency gap evidently increased. (2) There is an efficiency value to be found in a multi-center network structure, and it forms a “core-periphery” distribution pattern. The high-efficiency areas in the downstream and upstream regions of the YREB are gradually increasing, while the efficiency value in the midstream area remains low. (3) The urban efficiency values have strong correlation, and they are mainly “High-High agglomeration” and “Low-Low agglomeration”, and they show significant regional characteristics. (4) The economic level, industrial structure, and urbanization have obvious motivating effects on ULUE, and the positive spatial spillover effect is clear. The foreign direct investment and land finance hinder the boost of efficiency, and the latter has a negative spatial spillover role on the ULUE in the downstream cities.","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":"140984521","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}
Rafaela Tiengo, Silvia Merino-De-Miguel, Jéssica Uchôa, Artur Gil
Small oceanic islands, such as São Miguel Island in the Azores (Portugal), face heightened susceptibility to the adverse impacts of climate change, biological invasions, and land cover changes, posing threats to biodiversity and ecosystem functions and services. Over the years, persistent conservation endeavors, notably those supported by the EU LIFE Programme since 2003, have played a pivotal role in alleviating biodiversity decline, particularly in the eastern region of São Miguel Island. This study advocates the application of remote sensing data and techniques to support the management and effective monitoring of LIFE Nature projects with land cover impacts. A land cover change detection approach utilizing Rao’s Q diversity index identified and assessed changes from 2002 to 2021 in intervention areas. The study analyzed the changes in LIFE project areas using ASTER, Landsat 8, and Sentinel 2 data through Google Earth Engine on Google Colab (with Python). This methodological approach identified and assessed land cover changes in project intervention areas within defined timelines. This technological integration enhances the potential of remote sensing for near-real-time monitoring of conservation projects, making it possible to assess their land cover impacts and intervention achievements.
亚速尔群岛（葡萄牙）的圣米格尔岛等海洋小岛更容易受到气候变化、生物入侵和土地覆盖变化的不利影响，对生物多样性以及生态系统功能和服务构成威胁。多年来，坚持不懈的保护工作，特别是自 2003 年以来由欧盟 LIFE 计划支持的工作，在缓解生物多样性衰退方面发挥了关键作用，尤其是在圣米格尔岛东部地区。本研究提倡应用遥感数据和技术来支持管理和有效监测对土地覆被有影响的 LIFE 自然项目。利用 Rao's Q 多样性指数的土地覆被变化检测方法确定并评估了干预区域从 2002 年到 2021 年的变化。该研究利用 ASTER、Landsat 8 和 Sentinel 2 数据，通过 Google Colab 上的 Google 地球引擎（使用 Python）分析了 LIFE 项目区的变化。这种方法确定并评估了项目干预区在规定时间内的土地覆被变化。这种技术整合增强了遥感技术对保护项目进行近实时监测的潜力，使评估其土地覆被影响和干预成果成为可能。
{"title":"A Land Cover Change Detection Approach to Assess the Effectiveness of Conservation Projects: A Study Case on the EU-Funded LIFE Projects in São Miguel Island, Azores (2002–2021)","authors":"Rafaela Tiengo, Silvia Merino-De-Miguel, Jéssica Uchôa, Artur Gil","doi":"10.3390/land13050666","DOIUrl":"https://doi.org/10.3390/land13050666","url":null,"abstract":"Small oceanic islands, such as São Miguel Island in the Azores (Portugal), face heightened susceptibility to the adverse impacts of climate change, biological invasions, and land cover changes, posing threats to biodiversity and ecosystem functions and services. Over the years, persistent conservation endeavors, notably those supported by the EU LIFE Programme since 2003, have played a pivotal role in alleviating biodiversity decline, particularly in the eastern region of São Miguel Island. This study advocates the application of remote sensing data and techniques to support the management and effective monitoring of LIFE Nature projects with land cover impacts. A land cover change detection approach utilizing Rao’s Q diversity index identified and assessed changes from 2002 to 2021 in intervention areas. The study analyzed the changes in LIFE project areas using ASTER, Landsat 8, and Sentinel 2 data through Google Earth Engine on Google Colab (with Python). This methodological approach identified and assessed land cover changes in project intervention areas within defined timelines. This technological integration enhances the potential of remote sensing for near-real-time monitoring of conservation projects, making it possible to assess their land cover impacts and intervention achievements.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140986083","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}
Vladica Ristić, Igor Trišić, S. Štetić, M. Maksin, Florin Nechita, A. Candrea, Marko Pavlović, Andreea Hertanu
The Nature Park Ponjavica (NP) is the habitat of strictly protected plant and animal species, located in AP Vojvodina, in southern Banat (Northern Serbia). The area of the park covers 302.96 ha. Protection zones I, II, and III have been established in the protected area of the NP. The NP includes the middle course of the Ponjavica River, which has preserved characteristics of watercourses of plain areas and coastal remains of wetland habitats. The most valuable area of this park in terms of protection is an island with an area of slightly less than 1 hectare. According to the IUCN (International Union for Conservation of Nature), the NP is classified as the fourth category—Habitat and species management area. The good geographical position of NP is one of its main characteristics. The NP can be a destination where specific forms of tourism can be developed, such as ecotourism, nature-based tourism, birdwatching, scientific and research tourism, etc. Numerous historical sites represent a significant potential for the development of cultural tourism. The research examined the influence of institutional, economic, ecological, and socio-cultural sustainability on the respondents’ satisfaction. The quantitative methodology in this research included a questionnaire as a survey instrument for respondents. A total of 547 residents were surveyed. The results of the research indicate that there is considerable satisfaction among residents with sustainable tourism. The results of the research can help in the development of numerous tourism development strategies in which the wetland is the primary resource.
{"title":"Institutional, Ecological, Economic, and Socio-Cultural Sustainability—Evidence from Ponjavica Nature Park","authors":"Vladica Ristić, Igor Trišić, S. Štetić, M. Maksin, Florin Nechita, A. Candrea, Marko Pavlović, Andreea Hertanu","doi":"10.3390/land13050669","DOIUrl":"https://doi.org/10.3390/land13050669","url":null,"abstract":"The Nature Park Ponjavica (NP) is the habitat of strictly protected plant and animal species, located in AP Vojvodina, in southern Banat (Northern Serbia). The area of the park covers 302.96 ha. Protection zones I, II, and III have been established in the protected area of the NP. The NP includes the middle course of the Ponjavica River, which has preserved characteristics of watercourses of plain areas and coastal remains of wetland habitats. The most valuable area of this park in terms of protection is an island with an area of slightly less than 1 hectare. According to the IUCN (International Union for Conservation of Nature), the NP is classified as the fourth category—Habitat and species management area. The good geographical position of NP is one of its main characteristics. The NP can be a destination where specific forms of tourism can be developed, such as ecotourism, nature-based tourism, birdwatching, scientific and research tourism, etc. Numerous historical sites represent a significant potential for the development of cultural tourism. The research examined the influence of institutional, economic, ecological, and socio-cultural sustainability on the respondents’ satisfaction. The quantitative methodology in this research included a questionnaire as a survey instrument for respondents. A total of 547 residents were surveyed. The results of the research indicate that there is considerable satisfaction among residents with sustainable tourism. The results of the research can help in the development of numerous tourism development strategies in which the wetland is the primary resource.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140987086","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}
G. Herman, Lucian Blaga, Claudiu Filimon, T. Caciora, L. Filimon, Laura Mariana Herman, Jan A. Wendt
Tourism is one of the emerging branches of the economy, playing an important role in the development of specific economies within local communities. In this context, the perspectives of exploiting historical monuments, seen as raw material in the tourism industry, represent a desirable goal worth considering at the locality and territorial administrative unit level. The purpose of this study is to highlight the relationship between historical monuments, viewed as factors generating tourist motivation and tourism. This was made possible by conducting a spatial analysis (at the level of territorial administrative units and localities) of the defining criteria for historical monuments and tourism in Bihor County, Romania. The research methodology involved the use of multicriteria analysis to identify and establish the types of relationships between historical monuments and tourism, at a spatial level. The results of the study aimed to present an image of the spatial distribution of the characteristics of historical monuments and tourism, as well as to establish and depict spatial relationships between them, thus partially confirming the working hypothesis that the number and importance of historical monuments influence and determine tourist activity within a given area. Thus, although the studied area has 455 historical monuments, they are not exploited from a tourist point of view, with there being no strong relationships, except at the level of 19 territorial administrative units (18.8%), respectively, in 15 localities (3.3%). Among them, the obtained values stand out for the territorial administrative units of Oradea and Biharia, respectively, in the localities of Oradea and Beiuș.
{"title":"Spatial Distribution of Relationship between Historical Monuments and Tourism: The Case Study of Bihor County in Romania","authors":"G. Herman, Lucian Blaga, Claudiu Filimon, T. Caciora, L. Filimon, Laura Mariana Herman, Jan A. Wendt","doi":"10.3390/land13050668","DOIUrl":"https://doi.org/10.3390/land13050668","url":null,"abstract":"Tourism is one of the emerging branches of the economy, playing an important role in the development of specific economies within local communities. In this context, the perspectives of exploiting historical monuments, seen as raw material in the tourism industry, represent a desirable goal worth considering at the locality and territorial administrative unit level. The purpose of this study is to highlight the relationship between historical monuments, viewed as factors generating tourist motivation and tourism. This was made possible by conducting a spatial analysis (at the level of territorial administrative units and localities) of the defining criteria for historical monuments and tourism in Bihor County, Romania. The research methodology involved the use of multicriteria analysis to identify and establish the types of relationships between historical monuments and tourism, at a spatial level. The results of the study aimed to present an image of the spatial distribution of the characteristics of historical monuments and tourism, as well as to establish and depict spatial relationships between them, thus partially confirming the working hypothesis that the number and importance of historical monuments influence and determine tourist activity within a given area. Thus, although the studied area has 455 historical monuments, they are not exploited from a tourist point of view, with there being no strong relationships, except at the level of 19 territorial administrative units (18.8%), respectively, in 15 localities (3.3%). Among them, the obtained values stand out for the territorial administrative units of Oradea and Biharia, respectively, in the localities of Oradea and Beiuș.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140986736","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}
Creating a walkable environment is an essential step toward the 2030 Sustainable Development Goals. Nevertheless, not all people can enjoy a walkable environment, and neighborhoods with different socioeconomic status are found to vary greatly with walkability. Former studies have typically unraveled the relationship between neighborhood deprivation and walkability from a temporally static perspective and the produced estimations to a point-in-time snapshot were believed to incorporate great uncertainties. The ways in which neighborhood walkability changes over time in association with deprivation remain unclear. Using the case of the Hangzhou metropolitan area, we first measured the neighborhood walkability from 2016 to 2018 by calculating a set of revised walk scores. Further, we applied a machine learning algorithm, the kernel-based regularized least squares regression in particular, to unravel how neighborhood walkability changes in relation to deprivation over time. The results not only capture the nonlinearity in the relationship between neighborhood deprivation and walkability over time, but also highlight the marginal effects of each neighborhood deprivation indicator. Additionally, comparisons of the outputs between the machine learning algorithm and OLS regression illustrated that the machine learning approach did tell a different story and should contribute to remedying the contradictory conclusions in earlier studies. This paper is believed to renew the understanding of social inequalities in walkability by bringing the significance of temporal dynamics and structural interdependences to the fore.
{"title":"Unraveling the Dynamic Relationship between Neighborhood Deprivation and Walkability over Time: A Machine Learning Approach","authors":"Qian Wang, Guie Li, Min Weng","doi":"10.3390/land13050667","DOIUrl":"https://doi.org/10.3390/land13050667","url":null,"abstract":"Creating a walkable environment is an essential step toward the 2030 Sustainable Development Goals. Nevertheless, not all people can enjoy a walkable environment, and neighborhoods with different socioeconomic status are found to vary greatly with walkability. Former studies have typically unraveled the relationship between neighborhood deprivation and walkability from a temporally static perspective and the produced estimations to a point-in-time snapshot were believed to incorporate great uncertainties. The ways in which neighborhood walkability changes over time in association with deprivation remain unclear. Using the case of the Hangzhou metropolitan area, we first measured the neighborhood walkability from 2016 to 2018 by calculating a set of revised walk scores. Further, we applied a machine learning algorithm, the kernel-based regularized least squares regression in particular, to unravel how neighborhood walkability changes in relation to deprivation over time. The results not only capture the nonlinearity in the relationship between neighborhood deprivation and walkability over time, but also highlight the marginal effects of each neighborhood deprivation indicator. Additionally, comparisons of the outputs between the machine learning algorithm and OLS regression illustrated that the machine learning approach did tell a different story and should contribute to remedying the contradictory conclusions in earlier studies. This paper is believed to renew the understanding of social inequalities in walkability by bringing the significance of temporal dynamics and structural interdependences to the fore.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140986943","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}
Protecting cropland quality is a fundamental national policy that China must adhere to for the long term. This study examines the impact of market-oriented allocation of land factors on farmers’ cropland quality protection behaviors and its mechanism of action, based on survey data from 3804 farm households in the 2020 China Rural Revitalization Survey (CRRS). The study employs the Ordered Probit (O-probit) model, the mediated effect model, and other econometric tools to analyze the data. The study found that the market-oriented allocation of land factors can significantly promote farmers’ adoption of cropland quality protection behaviors. The robustness test supports this conclusion. The market-oriented allocation of land factors indirectly promotes the adoption of cropland quality protection by expanding the plot size and improving agricultural income. The analysis of heterogeneity indicates that farmers are more likely to adopt cropland quality protection behaviors in the plains, suburban areas, or areas with better developed labor markets. Therefore, it is essential to continue promoting market-oriented reforms of rural land factors, actively promoting land transfer policies, and guiding the development of agricultural operations towards scaling, specialization, and modernization. This will achieve the rational allocation of land resources. It is important to consider geographical variations in each area when implementing policies to guarantee effective utilization and protection of cropland.
{"title":"Can Market-Oriented Allocation of Land Factors Promote the Adoption of Cropland Quality Protection Behaviors by Farmers: Evidence from Rural China","authors":"Lulin Shen, Fang Wang","doi":"10.3390/land13050665","DOIUrl":"https://doi.org/10.3390/land13050665","url":null,"abstract":"Protecting cropland quality is a fundamental national policy that China must adhere to for the long term. This study examines the impact of market-oriented allocation of land factors on farmers’ cropland quality protection behaviors and its mechanism of action, based on survey data from 3804 farm households in the 2020 China Rural Revitalization Survey (CRRS). The study employs the Ordered Probit (O-probit) model, the mediated effect model, and other econometric tools to analyze the data. The study found that the market-oriented allocation of land factors can significantly promote farmers’ adoption of cropland quality protection behaviors. The robustness test supports this conclusion. The market-oriented allocation of land factors indirectly promotes the adoption of cropland quality protection by expanding the plot size and improving agricultural income. The analysis of heterogeneity indicates that farmers are more likely to adopt cropland quality protection behaviors in the plains, suburban areas, or areas with better developed labor markets. Therefore, it is essential to continue promoting market-oriented reforms of rural land factors, actively promoting land transfer policies, and guiding the development of agricultural operations towards scaling, specialization, and modernization. This will achieve the rational allocation of land resources. It is important to consider geographical variations in each area when implementing policies to guarantee effective utilization and protection of cropland.","PeriodicalId":37702,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140986986","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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