增强安徽省可持续发展动能对推动长三角更高质量一体化发展和服务国家新发展格局具有重要意义。本文构建了面向联合国2030可持续发展目标(Sustainable Development Goals,SDGs)的可持续发展水平评估框架和指标体系,对2011~2021年安徽省...增强安徽省可持续发展动能对推动长三角更高质量一体化发展和服务国家新发展格局具有重要意义。本文构建了面向联合国2030可持续发展目标(Sustainable Development Goals,SDGs)的可持续发展水平评估框架和指标体系,对2011~2021年安徽省及其16个地级市可持续发展水平进行测算,计算各市经济、社会和环境维度可持续发展的耦合协调度,分析安徽省可持续发展水平的时空演化特征,利用Dagum基尼系数深入探究安徽省可持续发展水平区域差异的原因,并基于灰色关联度分析方法进一步揭示影响安徽省不同城市可持续发展水平的关键因素。研究结果表明:安徽省可持续发展综合指数以及3个子系统间的耦合协调度呈现不断提高的趋势,但可持续发展水平空间差异明显。安徽省可持续发展水平空间差异原因主要来自区域之间的差异,“皖中-皖北”和“皖中-皖南”的区域间差异明显高于“皖南-皖北”。不同维度下不同指标对各市可持续发展综合水平的影响表现出明显差异。对省会合肥而言,研发经费支出占比、公共服务支出比重、生活垃圾无害化处理率分别是经济、社会和环境子系统影响其可持续发展综合水平的首要因素。研究结果可为安徽省加快实现2030可持续发展目标和推动高质量发展提供科学支撑。展开更多
The rapid urbanization and increasing challenges are faced by cities globally,including climate change,population growth,and resource constraints.Sustainable smart city(also referred to as“smart sustainable city”)ca...The rapid urbanization and increasing challenges are faced by cities globally,including climate change,population growth,and resource constraints.Sustainable smart city(also referred to as“smart sustainable city”)can offer innovative solutions by integrating advanced technologies to build smarter,greener,and more livable urban environments with significant benefits.Using the Web of Science(WoS)database,this study examined:(i)the mainstream approaches and current research trends in the literature of sustainable smart city;(ii)the extent to which the research of sustainable smart city aligns with Sustainable Development Goals(SDGs);(iii)the current topics and collaboration patterns in sustainable smart city research;and(iv)the potential opportunities for future research on the sustainable smart city field.The findings indicated that research on sustainable smart city began in 2010 and gained significant momentum in 2013,with China leading,followed by Italy and Spain.Moreover,59.00%of the selected publications on the research of sustainable smart city focus on SDG 11(Sustainable Cities and Communities).Bibliometric analysis outcome revealed that artificial intelligence(AI),big data,machine learning,and deep learning are emerging research fields.The terms smart city,smart cities,and sustainability emerged as the top three co-occurring keywords with the highest link strength,followed by frequently co-occurring keywords such as AI,innovation,big data,urban governance,resilience,machine learning,and Internet of Things(IoT).The clustering results indicated that current studies explored the theoretical foundation,challenges,and future prospects of sustainable smart city,with an emphasis on sustainability.To further support urban sustainability and the attainment of SDGs,the future research of sustainable smart city should explore the application and implications of AI and big data on urban development including cybersecurity and governance challenges.展开更多
SDGSAT-1,the world's first science satellite dedicated to assisting the United Nations 2030 Sustainable Development Agenda,has been operational for over two and a half years.It provides valuable data to aid in imp...SDGSAT-1,the world's first science satellite dedicated to assisting the United Nations 2030 Sustainable Development Agenda,has been operational for over two and a half years.It provides valuable data to aid in implementing the Sustainable Development Goals internationally.Through its Open Science Program,the satellite has maintained consistent operations and delivered free data to scientific and technological users from 88 countries.This program has produced a wealth of scientific output,with 72 papers,including 28 on data processing methods and 44 on applications for monitoring progress toward SDGs related to sustainable cities,clean energy,life underwater,climate action,and clean water and sanitation.SDGSAT-1 is equipped with three key instruments:a multispectral imager,a thermal infrared spectrometer,and a glimmer imager,which have enabled ground-breaking research in a variety of domains such as water quality analysis,identification of industrial heat sources,assessment of environmental disaster impacts,and detection of forest fires.The precise measurements and ongoing monitoring made possible by this invaluable data significantly advance our understanding of various environmental phenomena.They are essential for making well-informed decisions on a local and global scale.Beyond its application to academic research,SDGSAT-1 promotes global cooperation and strengthens developing countries'capacity to accomplish their sustainable development goals.As the satellite continues to gather and distribute data,it plays a pivotal role in developing strategies for environmental protection,disaster management and relief,and resource allocation.These initiatives highlight the satellite's vital role in fostering international collaboration and technical innovation to advance scientific knowledge and promote a sustainable future.展开更多
联合国2030年可持续发展目标(sustainable development goals,SDGs)的本土化是现阶段落实SDGs的核心任务。针对现有研究空间尺度大、时间尺度短的特点,以黄土高原地区348个县域作为研究区,通过构建指标体系以及采用莫兰指数评估2000—2...联合国2030年可持续发展目标(sustainable development goals,SDGs)的本土化是现阶段落实SDGs的核心任务。针对现有研究空间尺度大、时间尺度短的特点,以黄土高原地区348个县域作为研究区,通过构建指标体系以及采用莫兰指数评估2000—2020年可持续发展水平及时空演进特征,并利用灰色马尔科夫模型对未来可持续发展趋势进行探究。结果表明:黄土高原地区可持续发展水平在2000—2020年呈波动式上升,与中国整体平均水平间的差距逐渐缩小。各县域发展存在一定差距,青海省所辖县域处于绝对的劣势地位。各县域之间的空间正向关联性逐渐缩小,高-高聚集地区越来越多,未来10年可持续发展水平将持续提高。展开更多
The county(city)located on the northern slope of the Kunlun Mountains is the primary area to solidify and extend the success of Xinjiang Uygur Autonomous Region,China in poverty alleviation.Its Sustainable Development...The county(city)located on the northern slope of the Kunlun Mountains is the primary area to solidify and extend the success of Xinjiang Uygur Autonomous Region,China in poverty alleviation.Its Sustainable Development Goals(SDGs)are intertwined with the concerted economic and social development of Xinjiang and the objective of achieving shared prosperity within the region.This study established a sustainable development evaluation framework by selecting 15 SDGs and 20 secondary indicators from the United Nations’SDGs.The aim of this study is to quantitatively assess the progress of SDGs at the county(city)level on the northern slope of the Kunlun Mountains.The results indicate that there are substantial variations in the scores of SDGs among the nine counties and one city located on the northern slope of the Kunlun Mountains.Notable high scores of SDGs are observed in the central and eastern regions,whereas lower scores are prevalent in the western areas.The scores of SDGs,in descending order,are as follows:62.22 for Minfeng County,54.22 for Hotan City,50.21 for Qiemo County,42.54 for Moyu County,41.56 for Ruoqiang County,41.39 for Qira County,39.86 for Lop County,38.25 for Yutian County,38.10 for Pishan County,and 36.87 for Hotan County.The performances of SDGs reveal that Hotan City,Lop County,Minfeng County,and Ruoqiang County have significant sustainable development capacity because they have three or more SDGs ranked as green color.However,Hotan County,Moyu County,Qira County,and Yutian County show the poorest performance,as they lack SDGs with green color.It is important to establish and enhance mechanisms that can ensure sustained income growth among poverty alleviation beneficiaries,sustained improvement in the capacity of rural governance,and the gradual improvement of social security system.These measures will facilitate the effective implementation of SDGs.Finally,this study offers a valuable support for governmental authorities and relevant departments in their decision-making processes.In addition,these results hold significant reference value for assessing SDGs at the county(city)level,particularly in areas characterized by low levels of economic development.展开更多
Reliable and up-to-date geospatial data plays a fundamental role in Sustainable Development Goals(SDGs)monitoring.Aiming to providing such geospa-tial data,numerous algorithms,solutions and frame-works have been devel...Reliable and up-to-date geospatial data plays a fundamental role in Sustainable Development Goals(SDGs)monitoring.Aiming to providing such geospa-tial data,numerous algorithms,solutions and frame-works have been developed in recent years.A mong oth-ers,A rtificial Intelligence(AI)based techniques have been widely used for the tasks of processing geospatial data.Nowadays,this topic is blooming so fast and to a vast extent in the field of Geomatics that a new subdo-main seems to arise,namely GeoAI[1-2].Even for a very quick and brief glance inthe Internet,people can find a lot of applications,projects,blogs and research articles about GeoAI,w hereas new approaches to GeoAI have been proposed and tested.展开更多
This study examines the transformative role of self-help groups(SHGs)in the socioeconomic development of rural women in Cooch Behar District,India,and their contribution toward achieving Sustainable Development Goals(...This study examines the transformative role of self-help groups(SHGs)in the socioeconomic development of rural women in Cooch Behar District,India,and their contribution toward achieving Sustainable Development Goals(SDGs)of the United Nations.In this study,we explored the effect of SHGs on rural women by specifically addressing SDGs,such as no poverty(SDG 1),zero hunger(SDG 2),good health and well-being(SDG 3),quality education(SDG 4),and gender equality(SDG 5).Given this issue,a cross-sectional survey and comparison analyses are needed to assess the socioeconomic development of rural women and their awareness level before and after the participation of rural women in SHGs.The survey conducted as part of this study was divided into three sections,namely,demographic characteristics,socioeconomic development,and awareness level,with each focusing on different aspects.A group of 400 individuals who were part of SHGs completed the questionnaire survey form.The results showed that the participation of rural women in SHGs significantly improved their socioeconomic development and awareness level,as supported by both mean values and t test results.Memberships in SHGs and microcredit programs were the major elements that boosted the socioeconomic development of rural women,which also achieves SDGs 1,2,3,4,and 5.This study revealed that participation in SHGs and related financial services significantly aided rural women in economically disadvantaged communities in accumulating savings and initiating entrepreneurial ventures.Moreover,participation in SHGs was instrumental in enhancing the self-confidence,self-efficacy,and overall self-esteem of rural women.Finally,doing so enabled them to move more freely for work and other activities and to make family and common decisions.展开更多
Poverty has always been a global concern that has restricted human development.The first goal(SDG 1)of the United Nations Sustainable Development Goals(SDGs)is to eliminate all forms of poverty all over the world.The ...Poverty has always been a global concern that has restricted human development.The first goal(SDG 1)of the United Nations Sustainable Development Goals(SDGs)is to eliminate all forms of poverty all over the world.The establishment of a scientific and effective localized SDG 1 evaluation and monitoring method is the key to achieving SDG 1.This paper proposes SDG 1 China district and county-level localization evaluation method based on multi-source remote sensing data for the United Nations Sustainable Development Framework.The temporal and spatial distribution characteristics of China’s poverty areas and their SDG 1 evaluation values in 2012,2014,2016,and 2018 have been analyzed.Based on the SDGs global indicator framework,this paper first constructed SDG 1 China’s district and county localization indicator system and then extracted multidimensional feature factors from nighttime light images,land cover data,and digital elevation model data.Secondly,we establish SDG 1 China’s localized partial least squares estimation model and SDG 1 China’s localized machine learning estimation model.Finally,we analyze and verify the spatiotemporal distribution characteristics of China’s poverty areas and counties and their SDG 1 evaluation values.The results show that SDG 1 China’s district and county localization indicator system proposed in this study and SDG 1 China’s localized partial least squares estimation model can better reflect the poverty level of China’s districts and counties.The estimated model R^(2) is 0.65,which can identify 72.77%of China’s national poverty counties.From 2012 to 2018,the spatial distribution pattern of SDG evaluation values in China’s districts and counties is that the SDG evaluation values gradually increase from western China to eastern China.In addition,the average SDG 1 evaluation value of China’s districts and counties increased by 23%from 2012 to 2018.This paper is oriented to the United Nations SDGs framework,explores the SDG 1 localized evaluation method of China’s districts and counties based on multisource remote sensing data,and provides a scientific and rapid regional poverty monitoring and evaluation program for the implementation of the 2030 agenda poverty alleviation goals.展开更多
In order to further ensure that the 2030 Agenda for Sustainable Development is to be implemented and the action measures of all countries are consistent, the United Nations has put forward a set of indicators to monit...In order to further ensure that the 2030 Agenda for Sustainable Development is to be implemented and the action measures of all countries are consistent, the United Nations has put forward a set of indicators to monitor and evaluate the progress of global sustainable development. This set of evaluation indicators is aimed for global and regional progress. An important feature of the evaluation indicators is that they are internationally comparable, but due to the large differences in the levels of sustainable development among countries, this framework of evaluation indicators has a disadvantage that it does not apply to tracking the progress of sustainable development at the national level. This paper focuses on the analysis of specific issues in the application of the global sustainable development indicators framework to meet the goals and targets of the UN and builds a system of evaluation indicators to assess the progress of sustainable development at the national level in China, and offers a perspective to assess China’s progress as well.展开更多
文摘增强安徽省可持续发展动能对推动长三角更高质量一体化发展和服务国家新发展格局具有重要意义。本文构建了面向联合国2030可持续发展目标(Sustainable Development Goals,SDGs)的可持续发展水平评估框架和指标体系,对2011~2021年安徽省及其16个地级市可持续发展水平进行测算,计算各市经济、社会和环境维度可持续发展的耦合协调度,分析安徽省可持续发展水平的时空演化特征,利用Dagum基尼系数深入探究安徽省可持续发展水平区域差异的原因,并基于灰色关联度分析方法进一步揭示影响安徽省不同城市可持续发展水平的关键因素。研究结果表明:安徽省可持续发展综合指数以及3个子系统间的耦合协调度呈现不断提高的趋势,但可持续发展水平空间差异明显。安徽省可持续发展水平空间差异原因主要来自区域之间的差异,“皖中-皖北”和“皖中-皖南”的区域间差异明显高于“皖南-皖北”。不同维度下不同指标对各市可持续发展综合水平的影响表现出明显差异。对省会合肥而言,研发经费支出占比、公共服务支出比重、生活垃圾无害化处理率分别是经济、社会和环境子系统影响其可持续发展综合水平的首要因素。研究结果可为安徽省加快实现2030可持续发展目标和推动高质量发展提供科学支撑。
文摘The rapid urbanization and increasing challenges are faced by cities globally,including climate change,population growth,and resource constraints.Sustainable smart city(also referred to as“smart sustainable city”)can offer innovative solutions by integrating advanced technologies to build smarter,greener,and more livable urban environments with significant benefits.Using the Web of Science(WoS)database,this study examined:(i)the mainstream approaches and current research trends in the literature of sustainable smart city;(ii)the extent to which the research of sustainable smart city aligns with Sustainable Development Goals(SDGs);(iii)the current topics and collaboration patterns in sustainable smart city research;and(iv)the potential opportunities for future research on the sustainable smart city field.The findings indicated that research on sustainable smart city began in 2010 and gained significant momentum in 2013,with China leading,followed by Italy and Spain.Moreover,59.00%of the selected publications on the research of sustainable smart city focus on SDG 11(Sustainable Cities and Communities).Bibliometric analysis outcome revealed that artificial intelligence(AI),big data,machine learning,and deep learning are emerging research fields.The terms smart city,smart cities,and sustainability emerged as the top three co-occurring keywords with the highest link strength,followed by frequently co-occurring keywords such as AI,innovation,big data,urban governance,resilience,machine learning,and Internet of Things(IoT).The clustering results indicated that current studies explored the theoretical foundation,challenges,and future prospects of sustainable smart city,with an emphasis on sustainability.To further support urban sustainability and the attainment of SDGs,the future research of sustainable smart city should explore the application and implications of AI and big data on urban development including cybersecurity and governance challenges.
文摘SDGSAT-1,the world's first science satellite dedicated to assisting the United Nations 2030 Sustainable Development Agenda,has been operational for over two and a half years.It provides valuable data to aid in implementing the Sustainable Development Goals internationally.Through its Open Science Program,the satellite has maintained consistent operations and delivered free data to scientific and technological users from 88 countries.This program has produced a wealth of scientific output,with 72 papers,including 28 on data processing methods and 44 on applications for monitoring progress toward SDGs related to sustainable cities,clean energy,life underwater,climate action,and clean water and sanitation.SDGSAT-1 is equipped with three key instruments:a multispectral imager,a thermal infrared spectrometer,and a glimmer imager,which have enabled ground-breaking research in a variety of domains such as water quality analysis,identification of industrial heat sources,assessment of environmental disaster impacts,and detection of forest fires.The precise measurements and ongoing monitoring made possible by this invaluable data significantly advance our understanding of various environmental phenomena.They are essential for making well-informed decisions on a local and global scale.Beyond its application to academic research,SDGSAT-1 promotes global cooperation and strengthens developing countries'capacity to accomplish their sustainable development goals.As the satellite continues to gather and distribute data,it plays a pivotal role in developing strategies for environmental protection,disaster management and relief,and resource allocation.These initiatives highlight the satellite's vital role in fostering international collaboration and technical innovation to advance scientific knowledge and promote a sustainable future.
文摘联合国2030年可持续发展目标(sustainable development goals,SDGs)的本土化是现阶段落实SDGs的核心任务。针对现有研究空间尺度大、时间尺度短的特点,以黄土高原地区348个县域作为研究区,通过构建指标体系以及采用莫兰指数评估2000—2020年可持续发展水平及时空演进特征,并利用灰色马尔科夫模型对未来可持续发展趋势进行探究。结果表明:黄土高原地区可持续发展水平在2000—2020年呈波动式上升,与中国整体平均水平间的差距逐渐缩小。各县域发展存在一定差距,青海省所辖县域处于绝对的劣势地位。各县域之间的空间正向关联性逐渐缩小,高-高聚集地区越来越多,未来10年可持续发展水平将持续提高。
基金financially supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region,China(2022D01B234).
文摘The county(city)located on the northern slope of the Kunlun Mountains is the primary area to solidify and extend the success of Xinjiang Uygur Autonomous Region,China in poverty alleviation.Its Sustainable Development Goals(SDGs)are intertwined with the concerted economic and social development of Xinjiang and the objective of achieving shared prosperity within the region.This study established a sustainable development evaluation framework by selecting 15 SDGs and 20 secondary indicators from the United Nations’SDGs.The aim of this study is to quantitatively assess the progress of SDGs at the county(city)level on the northern slope of the Kunlun Mountains.The results indicate that there are substantial variations in the scores of SDGs among the nine counties and one city located on the northern slope of the Kunlun Mountains.Notable high scores of SDGs are observed in the central and eastern regions,whereas lower scores are prevalent in the western areas.The scores of SDGs,in descending order,are as follows:62.22 for Minfeng County,54.22 for Hotan City,50.21 for Qiemo County,42.54 for Moyu County,41.56 for Ruoqiang County,41.39 for Qira County,39.86 for Lop County,38.25 for Yutian County,38.10 for Pishan County,and 36.87 for Hotan County.The performances of SDGs reveal that Hotan City,Lop County,Minfeng County,and Ruoqiang County have significant sustainable development capacity because they have three or more SDGs ranked as green color.However,Hotan County,Moyu County,Qira County,and Yutian County show the poorest performance,as they lack SDGs with green color.It is important to establish and enhance mechanisms that can ensure sustained income growth among poverty alleviation beneficiaries,sustained improvement in the capacity of rural governance,and the gradual improvement of social security system.These measures will facilitate the effective implementation of SDGs.Finally,this study offers a valuable support for governmental authorities and relevant departments in their decision-making processes.In addition,these results hold significant reference value for assessing SDGs at the county(city)level,particularly in areas characterized by low levels of economic development.
文摘Reliable and up-to-date geospatial data plays a fundamental role in Sustainable Development Goals(SDGs)monitoring.Aiming to providing such geospa-tial data,numerous algorithms,solutions and frame-works have been developed in recent years.A mong oth-ers,A rtificial Intelligence(AI)based techniques have been widely used for the tasks of processing geospatial data.Nowadays,this topic is blooming so fast and to a vast extent in the field of Geomatics that a new subdo-main seems to arise,namely GeoAI[1-2].Even for a very quick and brief glance inthe Internet,people can find a lot of applications,projects,blogs and research articles about GeoAI,w hereas new approaches to GeoAI have been proposed and tested.
文摘This study examines the transformative role of self-help groups(SHGs)in the socioeconomic development of rural women in Cooch Behar District,India,and their contribution toward achieving Sustainable Development Goals(SDGs)of the United Nations.In this study,we explored the effect of SHGs on rural women by specifically addressing SDGs,such as no poverty(SDG 1),zero hunger(SDG 2),good health and well-being(SDG 3),quality education(SDG 4),and gender equality(SDG 5).Given this issue,a cross-sectional survey and comparison analyses are needed to assess the socioeconomic development of rural women and their awareness level before and after the participation of rural women in SHGs.The survey conducted as part of this study was divided into three sections,namely,demographic characteristics,socioeconomic development,and awareness level,with each focusing on different aspects.A group of 400 individuals who were part of SHGs completed the questionnaire survey form.The results showed that the participation of rural women in SHGs significantly improved their socioeconomic development and awareness level,as supported by both mean values and t test results.Memberships in SHGs and microcredit programs were the major elements that boosted the socioeconomic development of rural women,which also achieves SDGs 1,2,3,4,and 5.This study revealed that participation in SHGs and related financial services significantly aided rural women in economically disadvantaged communities in accumulating savings and initiating entrepreneurial ventures.Moreover,participation in SHGs was instrumental in enhancing the self-confidence,self-efficacy,and overall self-esteem of rural women.Finally,doing so enabled them to move more freely for work and other activities and to make family and common decisions.
基金supported by the National Natural Science Foundation of China[grant numbers 41971423 and 31972951]the Natural Science Foundation of Hunan Province[grant numbers 2020JJ3020 and 2020JJ5164]+1 种基金the Science and Technology Planning Project of Hunan Province[grant numbers 2019RS2043 and 2019GK2132]the Postgraduate Scientific Research Innovation Project of Hunan Province[grant number CX20210991].
文摘Poverty has always been a global concern that has restricted human development.The first goal(SDG 1)of the United Nations Sustainable Development Goals(SDGs)is to eliminate all forms of poverty all over the world.The establishment of a scientific and effective localized SDG 1 evaluation and monitoring method is the key to achieving SDG 1.This paper proposes SDG 1 China district and county-level localization evaluation method based on multi-source remote sensing data for the United Nations Sustainable Development Framework.The temporal and spatial distribution characteristics of China’s poverty areas and their SDG 1 evaluation values in 2012,2014,2016,and 2018 have been analyzed.Based on the SDGs global indicator framework,this paper first constructed SDG 1 China’s district and county localization indicator system and then extracted multidimensional feature factors from nighttime light images,land cover data,and digital elevation model data.Secondly,we establish SDG 1 China’s localized partial least squares estimation model and SDG 1 China’s localized machine learning estimation model.Finally,we analyze and verify the spatiotemporal distribution characteristics of China’s poverty areas and counties and their SDG 1 evaluation values.The results show that SDG 1 China’s district and county localization indicator system proposed in this study and SDG 1 China’s localized partial least squares estimation model can better reflect the poverty level of China’s districts and counties.The estimated model R^(2) is 0.65,which can identify 72.77%of China’s national poverty counties.From 2012 to 2018,the spatial distribution pattern of SDG evaluation values in China’s districts and counties is that the SDG evaluation values gradually increase from western China to eastern China.In addition,the average SDG 1 evaluation value of China’s districts and counties increased by 23%from 2012 to 2018.This paper is oriented to the United Nations SDGs framework,explores the SDG 1 localized evaluation method of China’s districts and counties based on multisource remote sensing data,and provides a scientific and rapid regional poverty monitoring and evaluation program for the implementation of the 2030 agenda poverty alleviation goals.
文摘In order to further ensure that the 2030 Agenda for Sustainable Development is to be implemented and the action measures of all countries are consistent, the United Nations has put forward a set of indicators to monitor and evaluate the progress of global sustainable development. This set of evaluation indicators is aimed for global and regional progress. An important feature of the evaluation indicators is that they are internationally comparable, but due to the large differences in the levels of sustainable development among countries, this framework of evaluation indicators has a disadvantage that it does not apply to tracking the progress of sustainable development at the national level. This paper focuses on the analysis of specific issues in the application of the global sustainable development indicators framework to meet the goals and targets of the UN and builds a system of evaluation indicators to assess the progress of sustainable development at the national level in China, and offers a perspective to assess China’s progress as well.
