Urban planning and transportation policies are vital to creating sustainable and liveable cities. Transit-orientated development (TOD) has emerged as a prominent approach that emphasises the establishment of neighbourhoods with convenient access to public transportation, thereby promoting car-free lifestyles. This research investigates the connection between proximity to transit stations and local living habits in Auckland, New Zealand, which is a car-dependent city aiming to transition to a sustainable TOD model. We use geolocational data from mobile phones to measure the daily mobility patterns of residents living within a 15 min walking distance of various transit stations. Employing ordinary least squares (OLS) regression, we analyse the correlation between residents’ average travel distances and individual mobility, considering different station contexts. We aim to determine whether individuals living near transit stations are more inclined to participate in local activities and make a higher proportion of short-distance trips. The results illustrate that approximately 54% of the residents show dominant localised mobility patterns. Living near a station is significantly associated with shorter annual travel distances, although this trend varies by area. Notably, only about 16 of the 34 stations studied indicate that their local residents predominantly engage in ‘local’ travel patterns. Rural stations show less correlation, likely due to poor infrastructure and limited walkability. This study underscores the vital role of proximity to transit stations in promoting sustainable mobility. It serves as a foundational guide for urban planners and designers to make informed decisions that improve the built environment and optimise land use.
{"title":"Analysing the Relationship between Proximity to Transit Stations and Local Living Patterns: A Study of Human Mobility within a 15 Min Walking Distance through Mobile Location Data","authors":"I-Ting Chuang, Lee Beattie, Lei Feng","doi":"10.3390/urbansci7040105","DOIUrl":"https://doi.org/10.3390/urbansci7040105","url":null,"abstract":"Urban planning and transportation policies are vital to creating sustainable and liveable cities. Transit-orientated development (TOD) has emerged as a prominent approach that emphasises the establishment of neighbourhoods with convenient access to public transportation, thereby promoting car-free lifestyles. This research investigates the connection between proximity to transit stations and local living habits in Auckland, New Zealand, which is a car-dependent city aiming to transition to a sustainable TOD model. We use geolocational data from mobile phones to measure the daily mobility patterns of residents living within a 15 min walking distance of various transit stations. Employing ordinary least squares (OLS) regression, we analyse the correlation between residents’ average travel distances and individual mobility, considering different station contexts. We aim to determine whether individuals living near transit stations are more inclined to participate in local activities and make a higher proportion of short-distance trips. The results illustrate that approximately 54% of the residents show dominant localised mobility patterns. Living near a station is significantly associated with shorter annual travel distances, although this trend varies by area. Notably, only about 16 of the 34 stations studied indicate that their local residents predominantly engage in ‘local’ travel patterns. Rural stations show less correlation, likely due to poor infrastructure and limited walkability. This study underscores the vital role of proximity to transit stations in promoting sustainable mobility. It serves as a foundational guide for urban planners and designers to make informed decisions that improve the built environment and optimise land use.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135095233","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}
Assouhan Jonas Atchadé, Madjouma Kanda, Fousseni Folega, Abdoul Aziz Diouf, Symphorien Agbahoungba, Marra Dourma, Kperkouma Wala, Koffi Akpagana
Urbanization is a current concern, particularly in Africa, where it is expected to continue and increasingly threaten the effectiveness of plant biodiversity, natural carbon sinks, and the sustainability of cities. This paper investigates the structural parameters and carbon storage potential of trees in the land use units of the city of Cotonou in southern Benin. A total of 149 plots at 2500 m2 each were randomly generated, and trees with a diameter ≥ 10 cm were inventoried. ANOVA revealed that the means of structural parameters (diameter and height classes) and carbon stock rate varied significantly (p < 0.001) across land use units in the city. Tree basal area is estimated at 4.52 ± 5.24 m2 ha−1, with an average of 12.72 (13) feet ha−1. The average diameter of the trees is estimated at 57.94 ± 29.71 cm. Approximately 1000 kg ha−1 (0.94 × 103 kg ha−1) of carbon is stored in the city of Cotonou. Green spaces (1.21 × 103 kg ha−1) and roads (1.19 × 103 kg ha−1) are the units that recorded the highest carbon stocks. Khaya senegalensis, Mangifera indica, and Terminalia mentally lead the top ten species with high stock potential. This study demonstrates the contribution of urban trees to global atmospheric carbon reduction, which varies by species, land use units, and tree density. Future research could investigate an i-Tree Landscape approach for urban carbon estimation. This could reinforce urban carbon data availability for urban ecological planning.
城市化是当前的一个问题，特别是在非洲，预计它将继续并日益威胁到植物生物多样性的有效性、天然碳汇和城市的可持续性。本文调查了贝宁南部科托努市土地利用单元中树木的结构参数和碳储存潜力。随机生成面积为2500 m2的样地149块，对直径≥10 cm的树木进行了清查。方差分析显示，结构参数(直径和高度类别)和碳储量均值差异显著(p <0.001)。树基面积估计为4.52±5.24 m2 ha - 1，平均为12.72(13)英尺ha - 1。树木的平均直径估计为57.94±29.71厘米。科托努市储存了大约1000千克公顷- 1 (0.94 × 103千克公顷- 1)的碳。绿地(1.21 × 103 kg ha - 1)和道路(1.19 × 103 kg ha - 1)是碳储量最高的单元。senegalensis、Mangifera indica和Terminalia在心理上居前10位。研究表明，城市树木对全球大气碳减排的贡献随树种、土地利用单位和树木密度的变化而变化。未来的研究可以探索i-Tree景观方法用于城市碳估算。这可以增强城市碳数据在城市生态规划中的可用性。
{"title":"Urban Flora Structure and Carbon Storage Potential of Woody Trees in Different Land Use Units of Cotonou (West Africa)","authors":"Assouhan Jonas Atchadé, Madjouma Kanda, Fousseni Folega, Abdoul Aziz Diouf, Symphorien Agbahoungba, Marra Dourma, Kperkouma Wala, Koffi Akpagana","doi":"10.3390/urbansci7040106","DOIUrl":"https://doi.org/10.3390/urbansci7040106","url":null,"abstract":"Urbanization is a current concern, particularly in Africa, where it is expected to continue and increasingly threaten the effectiveness of plant biodiversity, natural carbon sinks, and the sustainability of cities. This paper investigates the structural parameters and carbon storage potential of trees in the land use units of the city of Cotonou in southern Benin. A total of 149 plots at 2500 m2 each were randomly generated, and trees with a diameter ≥ 10 cm were inventoried. ANOVA revealed that the means of structural parameters (diameter and height classes) and carbon stock rate varied significantly (p < 0.001) across land use units in the city. Tree basal area is estimated at 4.52 ± 5.24 m2 ha−1, with an average of 12.72 (13) feet ha−1. The average diameter of the trees is estimated at 57.94 ± 29.71 cm. Approximately 1000 kg ha−1 (0.94 × 103 kg ha−1) of carbon is stored in the city of Cotonou. Green spaces (1.21 × 103 kg ha−1) and roads (1.19 × 103 kg ha−1) are the units that recorded the highest carbon stocks. Khaya senegalensis, Mangifera indica, and Terminalia mentally lead the top ten species with high stock potential. This study demonstrates the contribution of urban trees to global atmospheric carbon reduction, which varies by species, land use units, and tree density. Future research could investigate an i-Tree Landscape approach for urban carbon estimation. This could reinforce urban carbon data availability for urban ecological planning.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135094467","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}
Andrii Biloshchytskyi, Oleksandr Kuchanskyi, Yurii Andrashko, Didar Yedilkhan, Alexandr Neftissov, Svitlana Biloshchytska, Beibut Amirgaliyev, Vladimir Vatskel
This study considers the creation of a network of moss-based biotechnological purification filters under the Smart City concept. The extent of the absorption of heavy metals and gases by Sphagnopsida moss under different conditions was investigated. The efficiency of air purification with biotechnological filters was also investigated in the city of Almaty, Republic of Kazakhstan, where an excess of the permissible concentration of harmful substances in the air, according to the WHO air quality guidelines, is recorded throughout the year. Data on the level of pollution recorded with sensors located in the largest Kazakhstani cities from 21 June 2020 to 4 June 2023 were selected as the basis for calculating purification efficiency. In total, there are 220 in 73 settlements of the Republic of Kazakhstan, with 80 such sensors located in the city of Almaty. Since creating a single biotechnological filter is expensive, our task was to calculate the air purification effect in the case of increasing the number of filters placed in polluted areas. We show that 10 filters provide an air purification efficiency of 0.77%, with 100 filters providing an air purification efficiency of 5.72% and 500 filters providing an air purification efficiency of 23.11%. A biotechnological filter for air purification based on moss was designed at Astana IT University by taking into consideration the climatic features, distribution, and types of pollution in the Republic of Kazakhstan. The obtained results are essential for ensuring compliance with the standard for environmental comfort in the Republic of Kazakhstan. Additionally, the research findings and the experience of implementing a moss-based biotechnological filter can be applied to designing similar air purification systems in other cities. This is of great importance for the advancement of the field of urban science.
{"title":"Reducing Outdoor Air Pollutants through a Moss-Based Biotechnological Purification Filter in Kazakhstan","authors":"Andrii Biloshchytskyi, Oleksandr Kuchanskyi, Yurii Andrashko, Didar Yedilkhan, Alexandr Neftissov, Svitlana Biloshchytska, Beibut Amirgaliyev, Vladimir Vatskel","doi":"10.3390/urbansci7040104","DOIUrl":"https://doi.org/10.3390/urbansci7040104","url":null,"abstract":"This study considers the creation of a network of moss-based biotechnological purification filters under the Smart City concept. The extent of the absorption of heavy metals and gases by Sphagnopsida moss under different conditions was investigated. The efficiency of air purification with biotechnological filters was also investigated in the city of Almaty, Republic of Kazakhstan, where an excess of the permissible concentration of harmful substances in the air, according to the WHO air quality guidelines, is recorded throughout the year. Data on the level of pollution recorded with sensors located in the largest Kazakhstani cities from 21 June 2020 to 4 June 2023 were selected as the basis for calculating purification efficiency. In total, there are 220 in 73 settlements of the Republic of Kazakhstan, with 80 such sensors located in the city of Almaty. Since creating a single biotechnological filter is expensive, our task was to calculate the air purification effect in the case of increasing the number of filters placed in polluted areas. We show that 10 filters provide an air purification efficiency of 0.77%, with 100 filters providing an air purification efficiency of 5.72% and 500 filters providing an air purification efficiency of 23.11%. A biotechnological filter for air purification based on moss was designed at Astana IT University by taking into consideration the climatic features, distribution, and types of pollution in the Republic of Kazakhstan. The obtained results are essential for ensuring compliance with the standard for environmental comfort in the Republic of Kazakhstan. Additionally, the research findings and the experience of implementing a moss-based biotechnological filter can be applied to designing similar air purification systems in other cities. This is of great importance for the advancement of the field of urban science.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135252240","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}
Municipalities are concerned with addressing social issues such as mobility inclusion and safety by increasing access to transport facilities and services for all groups in society to create equitable and equal access for all citizens. Moreover, the public transportation systems provided in cities have to be inclusive and safe, driven by emerging technologies such as Artificial Intelligence (AI)-based services that provide personalized recommendation to improve mobility inclusion and safety for all citizens in society, especially vulnerable road users such as senior citizens or older people. But at the moment, there are few studies that have investigated how municipalities can provide inclusive and safe public transportation in general and for senior citizens, particularly those aged 65 and above. Therefore, this study aimed to examine how to provide inclusive and safe mobility for senior citizens to improve out-of-home mobility services for senior citizens towards age-friendly cities and communities. Accordingly, a systematic literature review grounded on secondary data was adopted to investigate inclusive and safe mobility needs for senior citizens. The data were collected from previous research and existing documents, and a descriptive data analysis was carried out to provide insights on urban transportation policies related to senior citizens. Furthermore, case studies were adopted to present polices and strategies employed in Norway, Canada, the United States of America, the United Kingdom, Sweden, and Northern Ireland to identify measures employed to address the public transportation needs of an aging society, focusing on the provision of inclusive and safe mobility to senior citizens. Further findings from this study included the possible use of emerging technologies such as AI-based machine learning for inclusive and safe mobility.
{"title":"Inclusive and Safe Mobility Needs of Senior Citizens: Implications for Age-Friendly Cities and Communities","authors":"Anthony Jnr. Bokolo","doi":"10.3390/urbansci7040103","DOIUrl":"https://doi.org/10.3390/urbansci7040103","url":null,"abstract":"Municipalities are concerned with addressing social issues such as mobility inclusion and safety by increasing access to transport facilities and services for all groups in society to create equitable and equal access for all citizens. Moreover, the public transportation systems provided in cities have to be inclusive and safe, driven by emerging technologies such as Artificial Intelligence (AI)-based services that provide personalized recommendation to improve mobility inclusion and safety for all citizens in society, especially vulnerable road users such as senior citizens or older people. But at the moment, there are few studies that have investigated how municipalities can provide inclusive and safe public transportation in general and for senior citizens, particularly those aged 65 and above. Therefore, this study aimed to examine how to provide inclusive and safe mobility for senior citizens to improve out-of-home mobility services for senior citizens towards age-friendly cities and communities. Accordingly, a systematic literature review grounded on secondary data was adopted to investigate inclusive and safe mobility needs for senior citizens. The data were collected from previous research and existing documents, and a descriptive data analysis was carried out to provide insights on urban transportation policies related to senior citizens. Furthermore, case studies were adopted to present polices and strategies employed in Norway, Canada, the United States of America, the United Kingdom, Sweden, and Northern Ireland to identify measures employed to address the public transportation needs of an aging society, focusing on the provision of inclusive and safe mobility to senior citizens. Further findings from this study included the possible use of emerging technologies such as AI-based machine learning for inclusive and safe mobility.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135352120","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}
Global warming is precipitating an amplification of severe meteorological occurrences such as prolonged dry spells and episodes of elevated temperatures. These phenomena are instigating substantial elevations in environmental warmth, with metropolitan regions bearing the brunt of these impacts. Currently, extreme heat is already impacting 30% of the global populace, and forecasts suggest that this figure will escalate to 74% in the forthcoming years. One of the objectives outlined in the United Nations 2030 agenda, specifically within Sustainable Development Goal 11 (SDG11), is the attainment of sustainable urban development. To achieve this, it is imperative to scrutinize and delve into urban environmental conditions in order to understand their dynamics comprehensively. This understanding serves as the foundation for implementing mitigation and resilience strategies against climate change, ultimately enhancing the well-being of city residents. In this context, the field of remote sensing and geographic information systems has made substantial advancements. Notably, the UrbClim model, developed by the European Space Agency, facilitates the assessment of environmental conditions within numerous European urban centers. This research, utilizing data from UrbClim, examines the evolution of the heat stress index (Hi) during extreme heat conditions in Barcelona during the summer of 2017. Leveraging Landsat 8 satellite imagery, we derived the following variables: the normalized difference vegetation index and the normalized building difference index. Our findings reveal that during extreme heat conditions, the Hi index experiences an escalation, with areas characterized by a higher population density and industrial zones displaying lower resistance in contrast to regions with a lower population density and rural areas, which exhibit greater resilience to Hi. This disparity can be attributed to higher vegetation coverage and reduced building density in the latter areas. In this way, Hi increases more quickly and intensely and decreases more slowly when using high temperatures compared to average temperatures. This is of utmost importance for the future planning of new urban developments.
{"title":"Mitigation and Resilience of Local Climatic Zones to the Effects of Extreme Heat: Study on the City of Barcelona (Spain)","authors":"David Hidalgo García, Julián Arco Díaz","doi":"10.3390/urbansci7040102","DOIUrl":"https://doi.org/10.3390/urbansci7040102","url":null,"abstract":"Global warming is precipitating an amplification of severe meteorological occurrences such as prolonged dry spells and episodes of elevated temperatures. These phenomena are instigating substantial elevations in environmental warmth, with metropolitan regions bearing the brunt of these impacts. Currently, extreme heat is already impacting 30% of the global populace, and forecasts suggest that this figure will escalate to 74% in the forthcoming years. One of the objectives outlined in the United Nations 2030 agenda, specifically within Sustainable Development Goal 11 (SDG11), is the attainment of sustainable urban development. To achieve this, it is imperative to scrutinize and delve into urban environmental conditions in order to understand their dynamics comprehensively. This understanding serves as the foundation for implementing mitigation and resilience strategies against climate change, ultimately enhancing the well-being of city residents. In this context, the field of remote sensing and geographic information systems has made substantial advancements. Notably, the UrbClim model, developed by the European Space Agency, facilitates the assessment of environmental conditions within numerous European urban centers. This research, utilizing data from UrbClim, examines the evolution of the heat stress index (Hi) during extreme heat conditions in Barcelona during the summer of 2017. Leveraging Landsat 8 satellite imagery, we derived the following variables: the normalized difference vegetation index and the normalized building difference index. Our findings reveal that during extreme heat conditions, the Hi index experiences an escalation, with areas characterized by a higher population density and industrial zones displaying lower resistance in contrast to regions with a lower population density and rural areas, which exhibit greater resilience to Hi. This disparity can be attributed to higher vegetation coverage and reduced building density in the latter areas. In this way, Hi increases more quickly and intensely and decreases more slowly when using high temperatures compared to average temperatures. This is of utmost importance for the future planning of new urban developments.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135719513","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}
Francesco Cianfarani, Mohamed Abdelkarim, Deborah Richards, Rajith Kumar Kedarisetty
Vacant land in residual urban areas is a crucial resource to tackle the current climate and housing crises. In this study, we present the development of a geodatabase to determine the occurrence of vacant land in the urban core of Oklahoma City, USA (OKC), and assess its potential for infill housing. As a starting point, we define urban vacant land through a literature review. We present a description of the case study’s social and urbanistic context by highlighting its relevance to this study. We explain the methodology for the development of the geodatabase to quantify residual urban land in OKC’s urban core. We examine the spatial distribution and recurring characteristics of vacant parcels using QGIS, Python scripting for Rhinoceros 3D, and aerial imagery. We find that small parcels have higher vacancy rates than average-sized parcels and there is a correlation between higher vacancy rates and proximity to downtown and brownfields. Finally, we discuss the implications of the findings by assessing the urban vacant land potential for residential development and its contribution to OKC’s housing provision. Under all the proposed scenarios, the considered developable vacant land in the urban core could entirely fulfill the need for new housing units for the entire city.
{"title":"Assessing the Urban Vacant Land Potential for Infill Housing: A Case Study in Oklahoma City, USA","authors":"Francesco Cianfarani, Mohamed Abdelkarim, Deborah Richards, Rajith Kumar Kedarisetty","doi":"10.3390/urbansci7040101","DOIUrl":"https://doi.org/10.3390/urbansci7040101","url":null,"abstract":"Vacant land in residual urban areas is a crucial resource to tackle the current climate and housing crises. In this study, we present the development of a geodatabase to determine the occurrence of vacant land in the urban core of Oklahoma City, USA (OKC), and assess its potential for infill housing. As a starting point, we define urban vacant land through a literature review. We present a description of the case study’s social and urbanistic context by highlighting its relevance to this study. We explain the methodology for the development of the geodatabase to quantify residual urban land in OKC’s urban core. We examine the spatial distribution and recurring characteristics of vacant parcels using QGIS, Python scripting for Rhinoceros 3D, and aerial imagery. We find that small parcels have higher vacancy rates than average-sized parcels and there is a correlation between higher vacancy rates and proximity to downtown and brownfields. Finally, we discuss the implications of the findings by assessing the urban vacant land potential for residential development and its contribution to OKC’s housing provision. Under all the proposed scenarios, the considered developable vacant land in the urban core could entirely fulfill the need for new housing units for the entire city.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134957843","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}
Modern cities are full of complex and substantial engineering structures that differ by their geometry, sizes, operating conditions, and technologies used in their construction. During the engineering structures’ life cycle, they experience the effects of construction, environmental, and functional loads. Among those structures are bridges and road overpasses. The primary reason for these structures’ displacements is land subsidence. The paper addresses a particular case of geospatial monitoring of a road overpass that is affected by external loads invoked by the construction of a new subway line. The study examines the methods of machine learning data analysis and prediction for geospatial monitoring data. The monitoring data were gathered in automatic mode using a robotic total station with a frequency of 30 min, and were averaged daily. Regression analysis and neural network regression with machine learning have been tested on geospatial monitoring data. Apart from the determined spatial displacements, additional parameters were used. These parameters were the position of the tunnel boring machines, precipitation level, temperature variation, and subsidence coefficient. The primary output of the study is a set of prediction models for displacements of the overpass, and the developed recommendations for correctly choosing the prediction model and a set of parameters and hyperparameters. The suggested models and recommendations should be considered an indispensable part of geotechnical monitoring for modern cities.
{"title":"Analysis of Overpass Displacements Due to Subway Construction Land Subsidence Using Machine Learning","authors":"Roman Shults, Mykola Bilous, Azhar Ormambekova, Toleuzhan Nurpeissova, Andrii Khailak, Andriy Annenkov, Rustem Akhmetov","doi":"10.3390/urbansci7040100","DOIUrl":"https://doi.org/10.3390/urbansci7040100","url":null,"abstract":"Modern cities are full of complex and substantial engineering structures that differ by their geometry, sizes, operating conditions, and technologies used in their construction. During the engineering structures’ life cycle, they experience the effects of construction, environmental, and functional loads. Among those structures are bridges and road overpasses. The primary reason for these structures’ displacements is land subsidence. The paper addresses a particular case of geospatial monitoring of a road overpass that is affected by external loads invoked by the construction of a new subway line. The study examines the methods of machine learning data analysis and prediction for geospatial monitoring data. The monitoring data were gathered in automatic mode using a robotic total station with a frequency of 30 min, and were averaged daily. Regression analysis and neural network regression with machine learning have been tested on geospatial monitoring data. Apart from the determined spatial displacements, additional parameters were used. These parameters were the position of the tunnel boring machines, precipitation level, temperature variation, and subsidence coefficient. The primary output of the study is a set of prediction models for displacements of the overpass, and the developed recommendations for correctly choosing the prediction model and a set of parameters and hyperparameters. The suggested models and recommendations should be considered an indispensable part of geotechnical monitoring for modern cities.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135925335","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}
Muhammad Tayyab Naqash, Toqeer Ali Syed, Saad Said Alqahtani, Muhammad Shoaib Siddiqui, Ali Alzahrani, Muhammad Nauman
Sustainable urban water management is essential to handle water scarcity, leakage, and inefficient distribution. This paper covers water management in urban areas, including an introduction, an overview of water management practices, the characteristics and functioning of water distribution systems, monitoring and control systems for efficient distribution, smart systems for optimization, strategies for water conservation and waste management, per capita water demand analysis, and desalination plant overviews. The article proposes a blockchain-based water management architecture with IoT sensors for accurate reporting. The framework uses blockchain technology to authenticate and share real-time data between sensors and the water distribution dashboard. It also has a modular API for water leakage detection and flow control to decrease water waste and enhance distribution. The suggested approach might enhance water management; however, its execution is complex. Maintaining the framework’s efficacy is advised. The research provides insights into water management and proposes a technology solution employing blockchain and IoT sensors for trustworthy data reporting and effective water distribution to promote sustainable urban water management.
{"title":"A Blockchain Based Framework for Efficient Water Management and Leakage Detection in Urban Areas","authors":"Muhammad Tayyab Naqash, Toqeer Ali Syed, Saad Said Alqahtani, Muhammad Shoaib Siddiqui, Ali Alzahrani, Muhammad Nauman","doi":"10.3390/urbansci7040099","DOIUrl":"https://doi.org/10.3390/urbansci7040099","url":null,"abstract":"Sustainable urban water management is essential to handle water scarcity, leakage, and inefficient distribution. This paper covers water management in urban areas, including an introduction, an overview of water management practices, the characteristics and functioning of water distribution systems, monitoring and control systems for efficient distribution, smart systems for optimization, strategies for water conservation and waste management, per capita water demand analysis, and desalination plant overviews. The article proposes a blockchain-based water management architecture with IoT sensors for accurate reporting. The framework uses blockchain technology to authenticate and share real-time data between sensors and the water distribution dashboard. It also has a modular API for water leakage detection and flow control to decrease water waste and enhance distribution. The suggested approach might enhance water management; however, its execution is complex. Maintaining the framework’s efficacy is advised. The research provides insights into water management and proposes a technology solution employing blockchain and IoT sensors for trustworthy data reporting and effective water distribution to promote sustainable urban water management.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136096676","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}
Ndonaye Allarané, Vidjinnagni Vinasse Ametooyona Azagoun, Assouhan Jonas Atchadé, Follygan Hetcheli, Joanes Atela
Climate change and its corollaries suggest that urban planning tools and strategies need to integrate adaptation and resilience approaches into urban development. This study aims to inform decision makers and the scientific community of the importance of appropriating data on urban adaptation and resilience strategies in the city of N’Djaména. After sampling 519 city dwellers, oriented questionnaires and focus groups were used to collect socio-demographic parameters, major climate risks, their impacts on urban issues and the urban resilience strategies employed. The various exposure and impact indices were used to identify and prioritize climate risks and urban exposure issues with the populations concerned. The study highlighted three major climatic hazards, namely, flooding, heat waves and strong winds, and their impact on social and community facilities, the living environment and human health. Ten vulnerability factors have been identified, of which the intrinsically geophysical factors are most familiar to the city’s population. The principal component analysis (PCA) illustrates ten (10) strategies for adaptation and resilience to urban climate risks. To meet the climatic challenges in urban areas, this study makes several short-, medium- and long-term recommendations to decision makers.
{"title":"Urban Vulnerability and Adaptation Strategies against Recurrent Climate Risks in Central Africa: Evidence from N’Djaména City (Chad)","authors":"Ndonaye Allarané, Vidjinnagni Vinasse Ametooyona Azagoun, Assouhan Jonas Atchadé, Follygan Hetcheli, Joanes Atela","doi":"10.3390/urbansci7030097","DOIUrl":"https://doi.org/10.3390/urbansci7030097","url":null,"abstract":"Climate change and its corollaries suggest that urban planning tools and strategies need to integrate adaptation and resilience approaches into urban development. This study aims to inform decision makers and the scientific community of the importance of appropriating data on urban adaptation and resilience strategies in the city of N’Djaména. After sampling 519 city dwellers, oriented questionnaires and focus groups were used to collect socio-demographic parameters, major climate risks, their impacts on urban issues and the urban resilience strategies employed. The various exposure and impact indices were used to identify and prioritize climate risks and urban exposure issues with the populations concerned. The study highlighted three major climatic hazards, namely, flooding, heat waves and strong winds, and their impact on social and community facilities, the living environment and human health. Ten vulnerability factors have been identified, of which the intrinsically geophysical factors are most familiar to the city’s population. The principal component analysis (PCA) illustrates ten (10) strategies for adaptation and resilience to urban climate risks. To meet the climatic challenges in urban areas, this study makes several short-, medium- and long-term recommendations to decision makers.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136236423","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}
Research on the detection of informal settlements has increased in the past three decades owing to the availability of high- to very-high-spatial-resolution satellite imagery. The achievement of development goals, such as the Sustainable Development Goals, requires access to up-to-date information on informal settlements. This review provides an overview of studies that used object-based image analysis (OBIA) techniques to detect informal settlements using remotely sensed data. This paper focuses on three main aspects: image processing steps followed when detecting informal settlements using OBIA; informal settlement indicators and image-based proxies used to detect informal settlements; and a review of studies that extracted and analyzed informal settlement land use objects. The success of OBIA in detecting informal settlements depends on the understanding and selection of informal settlement indicators and image-based proxies used during image classification. To meet the local ontology of informal settlements, the transfer of OBIA mapping techniques requires the fine-tuning of the rulesets. Machine learning OBIA techniques using image proxies derived from multiple sensors increase the opportunities for detecting informal settlements on the city or national level.
{"title":"Mapping and Assessment of Housing Informality Using Object-Based Image Analysis: A Review","authors":"Naledzani Mudau, Paidamwoyo Mhangara","doi":"10.3390/urbansci7030098","DOIUrl":"https://doi.org/10.3390/urbansci7030098","url":null,"abstract":"Research on the detection of informal settlements has increased in the past three decades owing to the availability of high- to very-high-spatial-resolution satellite imagery. The achievement of development goals, such as the Sustainable Development Goals, requires access to up-to-date information on informal settlements. This review provides an overview of studies that used object-based image analysis (OBIA) techniques to detect informal settlements using remotely sensed data. This paper focuses on three main aspects: image processing steps followed when detecting informal settlements using OBIA; informal settlement indicators and image-based proxies used to detect informal settlements; and a review of studies that extracted and analyzed informal settlement land use objects. The success of OBIA in detecting informal settlements depends on the understanding and selection of informal settlement indicators and image-based proxies used during image classification. To meet the local ontology of informal settlements, the transfer of OBIA mapping techniques requires the fine-tuning of the rulesets. Machine learning OBIA techniques using image proxies derived from multiple sensors increase the opportunities for detecting informal settlements on the city or national level.","PeriodicalId":75284,"journal":{"name":"Urban science (Basel, Switzerland)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136101344","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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