Population migration,especially population inflow from epidemic areas,is a key source of the risk related to the coronavirus disease 2019(COVID-19)epidemic.This paper selects Guangdong Province,China,for a case study....Population migration,especially population inflow from epidemic areas,is a key source of the risk related to the coronavirus disease 2019(COVID-19)epidemic.This paper selects Guangdong Province,China,for a case study.It utilizes big data on population migration and the geospatial analysis technique to develop a model to achieve spatiotemporal analysis of COVID-19 risk.The model takes into consideration the risk differential between the source cities of population migration as well as the heterogeneity in the socioeconomic characteristics of the destination cities of population migration.It further incorporates a time-lag process based on the time distribution of the onset of the imported cases.In theory,the model will be able to predict the evolutional trend and spatial distribution of the COVID-19 risk for a certain time period in the future and provide support for advanced planning and targeted prevention measures.The research findings indicate the following:(1)The COVID-19 epidemic in Guangdong Province reached a turning point on January 29,2020,after which it showed a gradual decreasing trend.(2)Based on the time-lag analysis of the onset of the imported cases,it is common fora time interval to exist between case importation and illness onset,and the proportion of the cases with an interval of 1-14 days is relatively high.(3)There is evident spatial heterogeneity in the epidemic risk;the risk varies significantly between different areas based on their imported risk,susceptibility risk,and ability to prevent the spread.(4)The degree of connectedness and the scale of population migration between Guangdong’s prefecture-level cities and their counterparts in the source regions of the epidemic,as well as the transportation and location factors of the cities in Guangdong,have a significant impact on the risk classification of the cities in Guangdong.The first-tier cities-Shenzhen and Guangzhou-are high-risk regions.The cities in the Pearl River Delta that are adjacent to Shenzhen and Guangzhou,including Dongguan,Foshan,Huizhou,Zhuhai,Zhongshan,are medium-risk cities.The eastern,northern,and western parts of Guangdong,which are outside of the metropolitan areas of the Pearl River Delta,are considered to have low risks.Therefore,the government should develop prevention and control measures that are specific to different regions based on their risk classification to enable targeted prevention and ensure the smooth operation of society.展开更多
Objective Human brucellosis is a serious public health concern in the Xilingol League,Inner Mongolia;however,the epidemic trends are unclear.Method In this study,Joinpoint regression analysis and spatiotemporal analys...Objective Human brucellosis is a serious public health concern in the Xilingol League,Inner Mongolia;however,the epidemic trends are unclear.Method In this study,Joinpoint regression analysis and spatiotemporal analysis were applied to investigate the epidemic evolution of human brucellosis.Result From 2004 to 2023,a total of 35,747 cases were reported,with an annual average of 1787.35cases and an annual average incidence rate of 176.04/100,000.The incidence increased from 173.96/100,000 in 2004 to 500.71/100,000 in 2009 and fluctuated to 61.43/100,000 in 2023.Three epidemic join points were observed in which the disease experienced an alternative rise and fall,peaking in 2009(APC=21.73,P>0.001)and 2020(APC=21.51,P>0.001).The disease showed a persistent decline trend in lentitude(AAPC=–5.30,P>0.001),suggesting challenges in disease control and a higher risk of rebound.The most cases were reported in Xilinhot City(n=4,777),followed by 4,391 in Sonid Left Banner,and 4,324 in Abaga Banner.Spatiotemporal analysis revealed two high clusters(CI and CII)from 2005 to 2012,the high cluster encompassing eight counties and shifting from north to south.Conclusion The present analysis highlights that human brucellosis has decreased significantly in the Xilingol League,but the epidemic is still severe;further implementation of a strict control program is necessary.展开更多
Road traffic crashes are becoming thorny issues being faced worldwide.Traffic crashes are spatiotemporal events and the research on the spatiotemporal patterns and variation trends of traffic crashes has been carried ...Road traffic crashes are becoming thorny issues being faced worldwide.Traffic crashes are spatiotemporal events and the research on the spatiotemporal patterns and variation trends of traffic crashes has been carried out.However,the impact of built environment on traffic crash spatiotemporal trends has not received much attention.Moreover,the spatial non-stationarity between the variation trends of traffic crashes and their influencing factors is usually neglected.To make up for the lack of analysis of built environment factors influencing spatiotemporal hotspot trends in traffic crashes,this paper proposed a method of“ST-GWLR”for analyzing the influence of built environment factors on spatiotemporal hotspot trends of traffic crashes by combining the spatiotemporal hotspot trend analysis and Geographically Weighted Logistic Regression(GWLR)modeling methods.Firstly,the traffic crash spatiotemporal hotspot trends were explored using the space-time cube model,hotspot analysis,and Mann-Kendall trend test.Then,the GWLR was introduced to capture the spatial non-stationarity neglected by the classic Global Logistic Regression(GLR)model,to improve the accuracy of the model estimation.GWLR model is used for the first time to analyze the significant local correlation between the traffic crash spatiotemporal hotspot trends and the built environment factors,to accurately and effectively identify the built environment factors that have significant influences on the hotspot trends of traffic crashes.The performance of the GWLR models and GLR models was examined and compared sufficiently.The results showed that the proposed ST-GWLR,which captured spatial non-stationarity,performed better than the classic GLR combined with spatiotemporal analysis,and improved the prediction accuracy of the models by 14.9%,13.9%,and 15.1%,respectively.There were significant local correlations between intensifying hotspots and persistent hotspots of traffic crashes and the built environment factors.The findings of this paper have positive implications for traffic safety management and urban built environment planning.展开更多
Population growth leads to increased utilization of water resources.One of these resources is groundwater,which has steadily declined each year.The depletion of these resources brings about various environmental chall...Population growth leads to increased utilization of water resources.One of these resources is groundwater,which has steadily declined each year.The depletion of these resources brings about various environmental challenges.The present study aimed to explore the relationship between groundwater fluctuations and land subsidence in the Malayer Plain,Iran,focusing on quantifying subsidence resulting from groundwater extraction.Using Sentinel-1 satellite data(2014–2019)and monthly piezometric measurements(1996–2018),the analysis revealed an average deformation velocity of–6.3 cm yr–1,with accumulated subsidence of–32 cm over the 2014–2019 period.The maximum subsidence rate reached 10.3 cm yr–1 in areas of intensive agricultural activity.A wavelet-PCA spatiotemporal analysis of groundwater fluctuations identified critical multi-scale patterns strongly correlated with subsidence trends.Regression analysis between subsidence rates and groundwater fluctuations at various wavelet decomposition levels explained 75%of the variance(R2=0.75),indicating that intermediate-scale groundwater declines were the primary drivers of subsidence.Furthermore,land use analysis using Landsat data(1999–2021)revealed a 6230-ha increase in irrigated farmland,contributing to heightened groundwater extraction and subsidence rates.These findings highlight the critical need for sustainable groundwater management to mitigate the risks of continued subsidence in the region.展开更多
In the urbanizing world,the Yangtze Delta Region （YDR） as one of the most developed regions in China,has drawn a lot of the world＇s attention for the remarkable economic development achieved in the past decades.Nev...In the urbanizing world,the Yangtze Delta Region （YDR） as one of the most developed regions in China,has drawn a lot of the world＇s attention for the remarkable economic development achieved in the past decades.Nevertheless,the rapid economic development was certain to be accompanied by unprecedented consumption and loss of natural resources.Therefore,the analysis of the ecological situation and driving factors of environmental impact was of great significance to serve the local sustainable development decision-making and build a harmonious society.In this paper,the ecological footprint （EF） was taken as the index of the ecological environmental impact.With the help of Geographic Information System （GIS）,we studied the spatiotemporal change of ecological footprint at two scales （region and city） and assessed urban sustainable development ability in YDR.Then we discussed the driving factors that affected the change of ecological footprint by the Stochastic Impacts by Regression on Population,Affluence,and Technology （STIRPAT） model.The results showed that increasing trends of regional ecological footprint during 1998-2008 （1.70-2.53 ha/cap） were accompanied by decreasing ecological capacity （0.31-0.25 ha/cap） but expanding ecological deficit （1.39-2.28 ha/cap）.The distribution pattern of ecological footprint and the degree of sustainable development varied distinctly from city to city in YDR.In 2008,the highest values of ecological footprint （3.85 ha/cap） and the lowest one of sustainable development index （SDI=1） in YDR were both presented in Shanghai.GDP per capita （A） was the most dominant driving force of EF and the classical EKC hypothesis did not exist between A and EF in 1998-2008.Consequently,increasing in ecological supply and reducing in human demand due to technological advances or other factors were one of the most effective ways to promote sustainable development in YDR.Moreover,importance should be attached to change our definition and measurement of prosperity and success.展开更多
Increasing attention has been paid to the deterioration of air quality in China during the past decade.This study presents the spatiotemporal variations of aerosol concentration across China during 2000–2016 using ae...Increasing attention has been paid to the deterioration of air quality in China during the past decade.This study presents the spatiotemporal variations of aerosol concentration across China during 2000–2016 using aerosol optical depth(AOD)from the atmospheric product of Moderate Resolution Imaging Spectroradiometer.Percentile thresholds are applied to define AOD days with different loadings.Temporally,aerosol concentration has increased since 2000 and reached the highest level in 2011;then it has declined from 2011 to 2016.Seasonally,aerosol concentration is the highest in summer and the lowest in winter.Spatially,North China and Sichuan Basin are featured by high aerosol concentration with increasing trends in North China and decreasing trends in Sichuan Basin.North,Southeast and Southwest China have been through increasing days with low AOD loading;however,Northeast China has experienced increasing days with high AOD loading.It is likely that air quality influenced by aerosols has notably improved over North China in spring and summer,over Southwest and Southeast China in autumn,but has degraded over Northeast China in autumn.展开更多
The massive lockdown of human socioeconomic activities and vehicle movements due to the COVID-19 pandemic in 2020 has resulted in an unprecedented reduction in pollutant gases such as Nitrogen Dioxide(NO_(2))and Carbo...The massive lockdown of human socioeconomic activities and vehicle movements due to the COVID-19 pandemic in 2020 has resulted in an unprecedented reduction in pollutant gases such as Nitrogen Dioxide(NO_(2))and Carbon Monoxide(CO)as well as Land Surface Temperature(LST)in Amman as well as all countries around the globe.In this study,the spatial and temporal variability/stability of NO_(2),CO,and LST throughout the lockdown period over Amman city have been analyzed.The NO_(2) and CO column density values were acquired from Sentinel-5p while the LST data were obtained from MODIS satellite during the lockdown period from 20 March to 24 April in 2019,2020,and 2021.The statistical analysis showed an overall reduction in NO_(2) in 2020 by around 27% and 48% compared to 2019 and 2021,respectively.However,an increase of 7% in 2021 compared to 2019 was observed because almost all anthropogenic activities were allowed during the daytime.The temporal persistence showed almost constant NO2 values in 2020 over the study area throughout the lockdown period.In addition,a slight decrease in CO(around 1%)was recorded in 2020 and 2021 compared to the same period in 2019.Restrictions on human activities resulted in an evident drop in LST in 2020 by around 13%and 18% less than the 5-year average and 2021 respectively.The study concludes that due to the restrictions imposed on industrial activities and automobile movements in Amman city,an unprecedented reduction in NO_(2),CO,and LST was recorded.展开更多
Although accelerated urbanization has led to economic prosperity,it has also resulted in urban heat island effects.Therefore,identifying methods of using limited urban spaces to alleviate heat islands has become an ur...Although accelerated urbanization has led to economic prosperity,it has also resulted in urban heat island effects.Therefore,identifying methods of using limited urban spaces to alleviate heat islands has become an urgent issue.In this study,we assessed the spatiotemporal evolution of urban heat islands within the central urban area of Fuzhou City,China from 2010 to 2019.This assessment was based on a morphological spatial pattern analysis(MSPA)model and an urban thermal environment spatial network constructed us-ing the minimum cumulative resistance(MCR)model.Optimization measures for the spatial network were proposed to provide a theor-etical basis for alleviating urban heat islands.The results show that the heat island area within the study area gradually increased while that of urban cold island area gradually decreased.The core area was the largest of the urban heat island patch landscape elements with a significant impact on other landscape elements,and represented an important factor underlying urban heat island network stability.The thermal environment network revealed a total of 197 thermal environment corridors and 93 heat island sources.These locations were then optimized according to the current land use,which maximized the potential of 1599.83 ha.Optimization based on current land use led to an increase in climate resilience,with effective measures showing reduction in thermal environment spatial network structure and function,contributing to the mitigation of urban heat island.These findings support the use of current land use patterns during urban heat island mitigation measure planning,thus providing an important reference basis for alleviating urban heat island effects.展开更多
The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorolog...The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorological parameters during and before the COVID-19 pandemic. The outcomes of this study indicated that air pollutants, PM2.5, NO2, PM10, CO, and SO2 are likely to decrease during winter (25%, 50%, 30%, 40%, and 35%) to spring (30%, 55%, 38%, 50%, and 40%) and summer (40%, 58%, 60%, 55%, and 47%), respectively. However, the concentration of O3-8h increased by 40%, 55%, and 65% during winter, spring, and summer, respectively. The values of the air quality index decreased during the COVID-19 period. Furthermore, significant positive trends were reported in PM2.5, NO2, PM10, O3, and SO2, and no notable trends in CO during the COVID-19 pandemic. Both during and before the COVID-19 period, PM10, NO2, PM2.5, CO, and SO2 showed a negative correlation with the temperature and a moderately positive significant correlation between O3-8h and temperature. The findings of this study would help understand the air pollution circumstances in Xi’an before and during the COVID-19 period and offer helpful information regarding the implications of different air pollution control strategies.展开更多
Landslides pose a significant threat to both human society and environmental sustainability,yet,their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood....Landslides pose a significant threat to both human society and environmental sustainability,yet,their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood.In this study,we projected global landslide susceptibility under four shared socioeconomic pathways(SSPs)from 2021 to 2100,utilizing multiple machine learning models based on precipitation data from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs)and static metrics.Our results indicate an overall upward trend in global landslide susceptibility under the SSPs compared to the baseline period(2001–2020),with the most significant increase of about 1%in the very far future(2081–2100)under the high emissions scenario(SSP5-8.5).Currently,approximately 13%of the world’s land area is at very high risk of landslide,mainly in the Cordillera of the Americas and the Andes in South America,the Alps in Europe,the Ethiopian Highlands in Africa,the Himalayas in Asia,and the countries of East and South-East Asia.Notably,India is the country most adversely affected by climate change,particularly during 2081–2100 under SSP3-7.0,with approximately 590 million people—23 times the global average—living in areas categorized as having very high susceptibility.展开更多
Prior research indicated low genotypic resistance testing(GRT)for human immunodeficiency virus(HIV)utilization in China due to partial cost coverage under national antiretroviral therapy policies,limited testing acces...Prior research indicated low genotypic resistance testing(GRT)for human immunodeficiency virus(HIV)utilization in China due to partial cost coverage under national antiretroviral therapy policies,limited testing accessibility,and financial barriers.Temporal and spatial data on GRT trends were also scarce.We analyzed GRT patterns among 6,895 untreated individuals at a tertiary hospital using Joinpoint regression,multivariable logistic modeling,and spatial analysis(GeoDa/SatScan).GRT rates showed a significant two-phase upward trend,increasing from 5.36%in 2014 to 74.17%in 2023,with an average annual percentage change of 31.30%(P<0.001).Beijing residency(adjusted odds ratio[aOR]=2.596,95%confidence interval[CI]:2.307-2.921)and older age were associated with higher GRT uptake.Specifically,ages 35-44 years(aOR=1.207,95%CI:1.026-1.420),45-54 years(aOR=1.335,95%CI:1.104-1.613),and≥55 years(aOR=1.424,95%CI:1.126-1.802)had significantly higher odds of testing.Lower testing rates were observed in individuals with lower education attainment(high school or technical secondary:aOR=0.827;junior high school:aOR=0.835;primary school:aOR=0.695),unknown sexually transmitted diseases(STDs)history(aOR=0.415),and non-heterosexual transmission routes(homosexual:aOR=0.834).Spatial analysis identified GRT clustering across Beijing until 2021,with two space-time clusters identified in 2019-2023 and 2018-2022.This study demonstrates substantial increase in GRT uptake achieving more balanced district-level distribution since 2021.Age,educational attainment,STDs history,and transmission route influence GRT utilization.Improving access,reducing costs,and implementing targeted interventions are critical for optimizing testing and guiding antiretroviral therapy decisions.展开更多
Rapid urbanization and urban greening have caused great changes to urban forests in China. Understanding spatiotemporal patterns of urban forest leaf area index(LAI) under rapid urbanization and urban greening is impo...Rapid urbanization and urban greening have caused great changes to urban forests in China. Understanding spatiotemporal patterns of urban forest leaf area index(LAI) under rapid urbanization and urban greening is important for urban forest planning and management. We evaluated the potential for estimating urban forest LAI spatiotemporally by using Landsat TM imagery. We collected three scenes of Landsat TM(thematic mapper)images acquired in 1997, 2004 and 2010 and conducted a field survey to collect urban forest LAI. Finally, spatiotemporal maps of the urban forest LAI were created using a NDVI-based urban forest LAI predictive model.Our results show that normalized differential vegetation index(NDVI) could be used as a predictor for urban forest LAI similar to natural forests. Both rapid urbanization and urban greening contribute to the changing process of urban forest LAI. The urban forest has changed considerably from 1997 to 2010. Urban vegetated pixels decreased gradually from 1997 to 2010 due to intensive urbanization.Leaf area for the study area was 216.4, 145.2 and173.7 km~2 in the years 1997, 2004 and 2010, respectively.Urban forest LAI decreased sharply from 1997 to 2004 and increased slightly from 2004 to 2010 because of numerous greening policies. The urban forest LAI class distributions were skewed toward low values in 1997 and 2004. Moreover, the LAI presented a decreasing trend from suburban to downtown areas. We demonstrate the usefulness of TM remote-sensing in understanding spatiotemporal changing patterns of urban forest LAI under rapid urbanization and urban greening.展开更多
In this study,the interplay between ecosystem services and human well-being in Seni district,which is a pastoral region of Nagqu city on the Qinghai-Tibet Plateau,is investigated.Employing the improved InVEST model,CA...In this study,the interplay between ecosystem services and human well-being in Seni district,which is a pastoral region of Nagqu city on the Qinghai-Tibet Plateau,is investigated.Employing the improved InVEST model,CASA model,coupling coordination model,and hierarchical clustering method,we analyze the spatiotemporal patterns of ecosystem services,the levels of resident well-being levels,and the interrelationships between these factors over the period from 2000 to 2018.Our findings reveal significant changes in six ecosystem services,with water production decreasing by 7.1%and carbon sequestration and soil conservation services increasing by approximately 6.3%and 14.6%,respectively.Both the habitat quality and landscape recreation services remained stable.Spatially,the towns in the eastern and southern areas exhibited higher water production and soil conservation services,while those in the central area exhibited greater carbon sequestration services.The coupling and coordination relationship between ecosystem services and human well-being improved significantly over the study period,evolving from low-level coupling to coordinated coupling.Hierarchical clustering was used to classify the 12 town-level units into five categories.Low subjective well-being townships had lower livestock breeding services,while high subjective well-being townships had higher supply,regulation,and support ecosystem services.Good transportation conditions were associated with higher subjective well-being in townships with low supply services.We recommend addressing the identified transportation disparities and enhancing key regulatory and livestock breeding services to promote regional sustainability and improve the quality of life for Seni district residents,thus catering to the diverse needs of both herdsmen and citizens.展开更多
Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analy...Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analyze the popularity of certain research topics,well-adopted methodologies,influential authors,and the interrelationships among research disciplines.However,the visual exploration of the patterns of research topics with an emphasis on their spatial and temporal distribution remains challenging.This study combined a Space-Time Cube(STC)and a 3D glyph to represent the complex multivariate bibliographic data.We further implemented a visual design by developing an interactive interface.The effectiveness,understandability,and engagement of ST-Map are evaluated by seven experts in geovisualization.The results suggest that it is promising to use three-dimensional visualization to show the overview and on-demand details on a single screen.展开更多
Objective To analyze the epidemiological characteristics of measles,mumps,and rubella(MMR)between 2014 and 2021 and identify potential strategies and measures for the prevention and control of MMR in China.Methods Dat...Objective To analyze the epidemiological characteristics of measles,mumps,and rubella(MMR)between 2014 and 2021 and identify potential strategies and measures for the prevention and control of MMR in China.Methods Data on MMR was obtained from China’s National Notifiable Disease Reporting System for the period from 2014 to 2021.Spatiotemporal distributions were analyzed using SaTScan;temporal trends were analyzed using JoinPoint;and clusters were visualized using ArcGIS.Results A total of 1,808,067 cases of MMR were reported from 2014 to 2021 in China’s mainland,most of which were children and students under the age of 20.The incidence of measles declined during 2014-2021,whereas that of mumps and rubella peaked in 2019.MMR-reported cases generally peaked from March to July;however,high numbers of mumps cases were reported from September to November in 2020-2021.Measles and rubella clusters predominantly occurred in Western China,whereas clusters of mumps were generally found in the southern region.Conclusion The relatively heterogeneous epidemiological characteristics of MMR have highlighted the weaknesses and gaps in surveillance and timely control of MMR transmission in China’s mainland.Real-time and intelligent monitoring data should be collected for evidence-based early interventions。展开更多
Based on TM image data and other survey materials, this paper analyzed the spatiotemporal patterns of land use change in the Bohai Rim during 1985-2005. The findings of this study are summarized as follows： （1） Lan...Based on TM image data and other survey materials, this paper analyzed the spatiotemporal patterns of land use change in the Bohai Rim during 1985-2005. The findings of this study are summarized as follows： （1） Land use pattern changed dramatically during 1985-2005. Industrial and residential land in urban and rural areas increased by 643,946 hm2 of which urban construction land had the largest and fastest increase of 294,953 hm2 at an annual rate of 3.72%. （2） The outward migration of rural population did not prevent the expansion of residential land in rural areas by 184,869 hm2. This increase reveals that construction of rural residences makes seriously wasteful and inefficient use of land. （3） Arable land, woodland and grassland decreased at a rate of -0.02%, -0.12% and -1.32% annually, while unused land shrank by 157,444 hm^2 at an annual rate of -1.69%. （4） The change of land use types showed marked fluctuations over the two stages （1985-1995 and 1995-2005） In particular, arable land, woodland and unused land experienced an inversed trend of change. （5） There was a significant interaction between arable land and woodland, industrial construction land in urban and rural areas showed a net trend of increase during the earlier period, but only adjustment to its internal structure during the second period. The loss of arable land to the construction of factories, mines and residences took place mainly in the fringe areas of large and medium-sized cities, along the routes of major roads, as well as in the economically developed coastal areas in the east. Such changes are closely related to the spatial differentiation of the level of urbanization and industrialization in the region.展开更多
Humanities and Social Sciences(HSS) are undergoing the transformation of spatialization and quantification. Geo-computation, with geoinformatics(including RS: Remote Sensing;GIS: Geographical Information System;GNSS: ...Humanities and Social Sciences(HSS) are undergoing the transformation of spatialization and quantification. Geo-computation, with geoinformatics(including RS: Remote Sensing;GIS: Geographical Information System;GNSS: Global Navigation Satellite System), provides effective computational and spatialization methods and tools for HSS. Spatial Humanities and Geo-computation for Social Sciences(SH&GSS) is a field coupling geo-computation, and geoinformatics, with HSS. This special issue accepted a set of contributions highlighting recent advances in methodologies and applications of SH&GSS, which are related to sentiment spatial analysis from social media data, emotional change spatial analysis from news data, spatial analysis of social media related to COVID-19, crime spatiotemporal analysis, “double evaluation” for Land Use/Land Cover(LUCC), Specially Protected Natural Areas(SPNA) analysis, editing behavior analysis of Volunteered Geographic Information(VGI), electricity consumption anomaly detection, First and Last Mile Problem(FLMP) of public transport, and spatial interaction network analysis for crude oil trade network. Based on these related researches, we aim to present an overview of SH&GSS, and propose some future research directions for SH&HSS.展开更多
The spatial diffusion of information is a process governed by the flow of interpersonal communication.The emergence of the Internet and especially social media platforms has reshaped this process and previous research...The spatial diffusion of information is a process governed by the flow of interpersonal communication.The emergence of the Internet and especially social media platforms has reshaped this process and previous research has studied how online social networks contribute to the diffusion of information.Understanding such processes can help devise methods to maximize or control the reach of information or even identify upcoming events and social movements.Yet activities in cyberspace are still confined to physical locations and this geographic connection tends to be overlooked.In this research,we focus on geographic regions instead of individuals and study how the underlying hierarchical structure of regions relates to their response to the information.We examined the top 30 populated cities and metropolitan areas in the U.S.and retrieved Twitter data related to two selected topics from these regions,the 2015 Nepal Earthquake and the#JesuisCharlie hashtag in response to the Paris attacks on the Charlie Hebdo offices.We analyzed the similarity among regions of their response using multiple statistical methods and three urban classifications.Our results indicate that the diffusion of information is impacted by the hierarchy of urban regions and that the Twitter responses act more similar when the populated regions are positioned at the same level in the urban hierarchy.展开更多
Mapping spatiotemporal land cover changes offers opportunities to better understand trends and drivers of envi-ronmental change and helps to identify more sustainable land management strategies.This study investigates...Mapping spatiotemporal land cover changes offers opportunities to better understand trends and drivers of envi-ronmental change and helps to identify more sustainable land management strategies.This study investigates the spatiotemporal patterns of changes in land covers,forest harvest areas and soil erosion rates in Nordic countries,namely Norway,Sweden,Finland,and Denmark.This region is highly sensitive to environmental changes,as it is experiencing high levels of human pressure and among the highest rates of global warming.An analysis that uses consistent land cover dataset to quantify and compares the recent spatiotemporal changes in land cover in the Nordic countries is missing.The recent products issued by the European Space Agency and the Copernicus Climate Change Service framework provide the possibility to investigate the historical land cover changes from 1992 to 2018 at 300 m resolution.These maps are then integrated with time series of forest harvest areas be-tween 2004 and 2018 to study if and how forest management is represented in land cover products,and with soil erosion data to explore status and recent trends in agricultural land.Land cover changes typically involved from 4%to 9%of the total area in each country.Wetland showed the strongest reduction(11,003 km^(2),−11%of the wetland area in 1992),followed by forest(8,607 km^(2),−1%)and sparse vegetation(5,695 km^(2),−7%),while agriculture(15,884 km^(2),16%)and settlement(3,582 km^(2),84%)showed net increases.Wetland shrinkage dominated land cover changes in Norway(5,870 km^(2),−18%),followed by forest and grassland with a net gain of 3,441 km^(2)(3%)and 3,435 km^(2)(10%),respectively.In Sweden,forest areas decreased 13,008 km^(2)(−4%),mainly due to agriculture expansion(9,211 km^(2),29%).In Finland,agricultural areas increased by 5,982 km^(2)(24%),and wetland decreased by 6,698 km^(2)(−22%).Settlement had the largest net growth in Denmark(717 km^(2),70%),mainly from conversion of agriculture land.Soil erosion rates in Nordic countries are lower than the global average,but they are exacerbating in several locations(especially western Norway).The integration of the land cover datasets with maps of forest harvest areas shows that the majority of the losses in forest cover due to forestry operations are largely undetected,but a non-negligible share of the forest-to-agriculture(up to 19%)or forest-to-grassland(up to 51%)transitions overlap with the harvested sites.Forestry activity in the study region primarily involves small-scale harvest events that are difficult to be detected at the 300 m resolution of the land cover dataset.An accurate representation of forest management remains a challenge for global datasets of land cover time series,and more interdisciplinary international efforts are needed to address this gap.Overall,this analysis provides a detailed overview of recent changes in land cover and forest management in Nordic countries as represented by state-of-the-art global datasets,and offers insights to future studies aiming to improve these data or apply them in land surface models,climate models,landscape ecology,or other applications.展开更多
This data-driven work aims to analyze and classify the spatiotemporal distribution of all Brazilian states considering data so diverse as the number of Covid-19 cases,deaths,confirmed cases per 100 k inhabitants,morta...This data-driven work aims to analyze and classify the spatiotemporal distribution of all Brazilian states considering data so diverse as the number of Covid-19 cases,deaths,confirmed cases per 100 k inhabitants,mortality per 100 k inhabitants and case fatality rates as health indicators.We also considered population,area and population density as geographic indicators.Finally,GDP and HDI were taken into account as economic and social criteria.For this task data were collected from April 3rd until August 8th,2020,corresponding to epidemiological weeks 14e32,reaching three million cases and a hundred thousand deaths.With this data it was possible to classify Brazilian states using multivariate methods into possible groups by means of non-hierarchical(k-means)cluster as well as factor analysis.It was possible to group all states plus the Federal District into five clusters,taking into account these 10 variables over the first five months of the epidemic.Group changes between states were observed over time and clusters,and between three and four factors were found.However,even with great difference on health indicators during days,the number of clusters remains fixed.Also,S^ao Paulo and Rio de Janeiro states were ranked at top list taking into account all epidemiological weeks.Correlations were observed between variables,such as the number of Covid cases and deaths with GDP for most of epidemiological weeks.Some clusters were more critical due to specific variables,including cities that are main hotspots.These multivariate findings would provide a comprehensive description of the ongoing Covid-19 epidemic and may help to guide subsequent studies to understand and control virus transmission.展开更多
基金National Key Research and Development Program,No.2019YFB2103101GDAS Special Project of Science and Technology Development,No.2020GDASYL-20200301003Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou),No.GML2019ZD0301。
文摘Population migration,especially population inflow from epidemic areas,is a key source of the risk related to the coronavirus disease 2019(COVID-19)epidemic.This paper selects Guangdong Province,China,for a case study.It utilizes big data on population migration and the geospatial analysis technique to develop a model to achieve spatiotemporal analysis of COVID-19 risk.The model takes into consideration the risk differential between the source cities of population migration as well as the heterogeneity in the socioeconomic characteristics of the destination cities of population migration.It further incorporates a time-lag process based on the time distribution of the onset of the imported cases.In theory,the model will be able to predict the evolutional trend and spatial distribution of the COVID-19 risk for a certain time period in the future and provide support for advanced planning and targeted prevention measures.The research findings indicate the following:(1)The COVID-19 epidemic in Guangdong Province reached a turning point on January 29,2020,after which it showed a gradual decreasing trend.(2)Based on the time-lag analysis of the onset of the imported cases,it is common fora time interval to exist between case importation and illness onset,and the proportion of the cases with an interval of 1-14 days is relatively high.(3)There is evident spatial heterogeneity in the epidemic risk;the risk varies significantly between different areas based on their imported risk,susceptibility risk,and ability to prevent the spread.(4)The degree of connectedness and the scale of population migration between Guangdong’s prefecture-level cities and their counterparts in the source regions of the epidemic,as well as the transportation and location factors of the cities in Guangdong,have a significant impact on the risk classification of the cities in Guangdong.The first-tier cities-Shenzhen and Guangzhou-are high-risk regions.The cities in the Pearl River Delta that are adjacent to Shenzhen and Guangzhou,including Dongguan,Foshan,Huizhou,Zhuhai,Zhongshan,are medium-risk cities.The eastern,northern,and western parts of Guangdong,which are outside of the metropolitan areas of the Pearl River Delta,are considered to have low risks.Therefore,the government should develop prevention and control measures that are specific to different regions based on their risk classification to enable targeted prevention and ensure the smooth operation of society.
基金supported by the National Key Research and Development Program of China(Grant number:2019YFC1200700[No.32095])National Natural Science Foundation of China(L2124006,Institute internal number:90100)Central Government-Guided Local Science and Technology Development Funding Projects(Grant number:2024ZY0053)。
文摘Objective Human brucellosis is a serious public health concern in the Xilingol League,Inner Mongolia;however,the epidemic trends are unclear.Method In this study,Joinpoint regression analysis and spatiotemporal analysis were applied to investigate the epidemic evolution of human brucellosis.Result From 2004 to 2023,a total of 35,747 cases were reported,with an annual average of 1787.35cases and an annual average incidence rate of 176.04/100,000.The incidence increased from 173.96/100,000 in 2004 to 500.71/100,000 in 2009 and fluctuated to 61.43/100,000 in 2023.Three epidemic join points were observed in which the disease experienced an alternative rise and fall,peaking in 2009(APC=21.73,P>0.001)and 2020(APC=21.51,P>0.001).The disease showed a persistent decline trend in lentitude(AAPC=–5.30,P>0.001),suggesting challenges in disease control and a higher risk of rebound.The most cases were reported in Xilinhot City(n=4,777),followed by 4,391 in Sonid Left Banner,and 4,324 in Abaga Banner.Spatiotemporal analysis revealed two high clusters(CI and CII)from 2005 to 2012,the high cluster encompassing eight counties and shifting from north to south.Conclusion The present analysis highlights that human brucellosis has decreased significantly in the Xilingol League,but the epidemic is still severe;further implementation of a strict control program is necessary.
基金supported by the National Natural Science Foundation of China[grant numbers 42101449,42090012 and 61825103]the Natural Science Foundation of Hubei Province,China[grant numbers 2022CFB773 and 2020CFA001]+2 种基金the Key Research and Development Program of Hubei Province,China[grant number 2022BAA048]the Chutian Scholar Program of Hubei Provincethe Yellow Crane Talent Scheme.
文摘Road traffic crashes are becoming thorny issues being faced worldwide.Traffic crashes are spatiotemporal events and the research on the spatiotemporal patterns and variation trends of traffic crashes has been carried out.However,the impact of built environment on traffic crash spatiotemporal trends has not received much attention.Moreover,the spatial non-stationarity between the variation trends of traffic crashes and their influencing factors is usually neglected.To make up for the lack of analysis of built environment factors influencing spatiotemporal hotspot trends in traffic crashes,this paper proposed a method of“ST-GWLR”for analyzing the influence of built environment factors on spatiotemporal hotspot trends of traffic crashes by combining the spatiotemporal hotspot trend analysis and Geographically Weighted Logistic Regression(GWLR)modeling methods.Firstly,the traffic crash spatiotemporal hotspot trends were explored using the space-time cube model,hotspot analysis,and Mann-Kendall trend test.Then,the GWLR was introduced to capture the spatial non-stationarity neglected by the classic Global Logistic Regression(GLR)model,to improve the accuracy of the model estimation.GWLR model is used for the first time to analyze the significant local correlation between the traffic crash spatiotemporal hotspot trends and the built environment factors,to accurately and effectively identify the built environment factors that have significant influences on the hotspot trends of traffic crashes.The performance of the GWLR models and GLR models was examined and compared sufficiently.The results showed that the proposed ST-GWLR,which captured spatial non-stationarity,performed better than the classic GLR combined with spatiotemporal analysis,and improved the prediction accuracy of the models by 14.9%,13.9%,and 15.1%,respectively.There were significant local correlations between intensifying hotspots and persistent hotspots of traffic crashes and the built environment factors.The findings of this paper have positive implications for traffic safety management and urban built environment planning.
文摘Population growth leads to increased utilization of water resources.One of these resources is groundwater,which has steadily declined each year.The depletion of these resources brings about various environmental challenges.The present study aimed to explore the relationship between groundwater fluctuations and land subsidence in the Malayer Plain,Iran,focusing on quantifying subsidence resulting from groundwater extraction.Using Sentinel-1 satellite data(2014–2019)and monthly piezometric measurements(1996–2018),the analysis revealed an average deformation velocity of–6.3 cm yr–1,with accumulated subsidence of–32 cm over the 2014–2019 period.The maximum subsidence rate reached 10.3 cm yr–1 in areas of intensive agricultural activity.A wavelet-PCA spatiotemporal analysis of groundwater fluctuations identified critical multi-scale patterns strongly correlated with subsidence trends.Regression analysis between subsidence rates and groundwater fluctuations at various wavelet decomposition levels explained 75%of the variance(R2=0.75),indicating that intermediate-scale groundwater declines were the primary drivers of subsidence.Furthermore,land use analysis using Landsat data(1999–2021)revealed a 6230-ha increase in irrigated farmland,contributing to heightened groundwater extraction and subsidence rates.These findings highlight the critical need for sustainable groundwater management to mitigate the risks of continued subsidence in the region.
基金National Natural Science Foundation of China for Young Scholars, No.50808048 The Humanities and Social Science Research Projects of the Ministry of Education, No.07JA630036
文摘In the urbanizing world,the Yangtze Delta Region （YDR） as one of the most developed regions in China,has drawn a lot of the world＇s attention for the remarkable economic development achieved in the past decades.Nevertheless,the rapid economic development was certain to be accompanied by unprecedented consumption and loss of natural resources.Therefore,the analysis of the ecological situation and driving factors of environmental impact was of great significance to serve the local sustainable development decision-making and build a harmonious society.In this paper,the ecological footprint （EF） was taken as the index of the ecological environmental impact.With the help of Geographic Information System （GIS）,we studied the spatiotemporal change of ecological footprint at two scales （region and city） and assessed urban sustainable development ability in YDR.Then we discussed the driving factors that affected the change of ecological footprint by the Stochastic Impacts by Regression on Population,Affluence,and Technology （STIRPAT） model.The results showed that increasing trends of regional ecological footprint during 1998-2008 （1.70-2.53 ha/cap） were accompanied by decreasing ecological capacity （0.31-0.25 ha/cap） but expanding ecological deficit （1.39-2.28 ha/cap）.The distribution pattern of ecological footprint and the degree of sustainable development varied distinctly from city to city in YDR.In 2008,the highest values of ecological footprint （3.85 ha/cap） and the lowest one of sustainable development index （SDI=1） in YDR were both presented in Shanghai.GDP per capita （A） was the most dominant driving force of EF and the classical EKC hypothesis did not exist between A and EF in 1998-2008.Consequently,increasing in ecological supply and reducing in human demand due to technological advances or other factors were one of the most effective ways to promote sustainable development in YDR.Moreover,importance should be attached to change our definition and measurement of prosperity and success.
基金supported by a Natural Sciences and Engineering Research Council of Canada(NSERC)Discovery Grant and Ontario Trillium Scholarship.
文摘Increasing attention has been paid to the deterioration of air quality in China during the past decade.This study presents the spatiotemporal variations of aerosol concentration across China during 2000–2016 using aerosol optical depth(AOD)from the atmospheric product of Moderate Resolution Imaging Spectroradiometer.Percentile thresholds are applied to define AOD days with different loadings.Temporally,aerosol concentration has increased since 2000 and reached the highest level in 2011;then it has declined from 2011 to 2016.Seasonally,aerosol concentration is the highest in summer and the lowest in winter.Spatially,North China and Sichuan Basin are featured by high aerosol concentration with increasing trends in North China and decreasing trends in Sichuan Basin.North,Southeast and Southwest China have been through increasing days with low AOD loading;however,Northeast China has experienced increasing days with high AOD loading.It is likely that air quality influenced by aerosols has notably improved over North China in spring and summer,over Southwest and Southeast China in autumn,but has degraded over Northeast China in autumn.
文摘The massive lockdown of human socioeconomic activities and vehicle movements due to the COVID-19 pandemic in 2020 has resulted in an unprecedented reduction in pollutant gases such as Nitrogen Dioxide(NO_(2))and Carbon Monoxide(CO)as well as Land Surface Temperature(LST)in Amman as well as all countries around the globe.In this study,the spatial and temporal variability/stability of NO_(2),CO,and LST throughout the lockdown period over Amman city have been analyzed.The NO_(2) and CO column density values were acquired from Sentinel-5p while the LST data were obtained from MODIS satellite during the lockdown period from 20 March to 24 April in 2019,2020,and 2021.The statistical analysis showed an overall reduction in NO_(2) in 2020 by around 27% and 48% compared to 2019 and 2021,respectively.However,an increase of 7% in 2021 compared to 2019 was observed because almost all anthropogenic activities were allowed during the daytime.The temporal persistence showed almost constant NO2 values in 2020 over the study area throughout the lockdown period.In addition,a slight decrease in CO(around 1%)was recorded in 2020 and 2021 compared to the same period in 2019.Restrictions on human activities resulted in an evident drop in LST in 2020 by around 13%and 18% less than the 5-year average and 2021 respectively.The study concludes that due to the restrictions imposed on industrial activities and automobile movements in Amman city,an unprecedented reduction in NO_(2),CO,and LST was recorded.
基金Under the auspices of Special Funds for Education and Scientific Research of the Department of Finance(Min Cai Zhi[2022]No.840)Fujian Province Key Laboratory of Geographic Information Technology and Resource Optimization Construction Project(No.PTJH17014)。
文摘Although accelerated urbanization has led to economic prosperity,it has also resulted in urban heat island effects.Therefore,identifying methods of using limited urban spaces to alleviate heat islands has become an urgent issue.In this study,we assessed the spatiotemporal evolution of urban heat islands within the central urban area of Fuzhou City,China from 2010 to 2019.This assessment was based on a morphological spatial pattern analysis(MSPA)model and an urban thermal environment spatial network constructed us-ing the minimum cumulative resistance(MCR)model.Optimization measures for the spatial network were proposed to provide a theor-etical basis for alleviating urban heat islands.The results show that the heat island area within the study area gradually increased while that of urban cold island area gradually decreased.The core area was the largest of the urban heat island patch landscape elements with a significant impact on other landscape elements,and represented an important factor underlying urban heat island network stability.The thermal environment network revealed a total of 197 thermal environment corridors and 93 heat island sources.These locations were then optimized according to the current land use,which maximized the potential of 1599.83 ha.Optimization based on current land use led to an increase in climate resilience,with effective measures showing reduction in thermal environment spatial network structure and function,contributing to the mitigation of urban heat island.These findings support the use of current land use patterns during urban heat island mitigation measure planning,thus providing an important reference basis for alleviating urban heat island effects.
文摘The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorological parameters during and before the COVID-19 pandemic. The outcomes of this study indicated that air pollutants, PM2.5, NO2, PM10, CO, and SO2 are likely to decrease during winter (25%, 50%, 30%, 40%, and 35%) to spring (30%, 55%, 38%, 50%, and 40%) and summer (40%, 58%, 60%, 55%, and 47%), respectively. However, the concentration of O3-8h increased by 40%, 55%, and 65% during winter, spring, and summer, respectively. The values of the air quality index decreased during the COVID-19 period. Furthermore, significant positive trends were reported in PM2.5, NO2, PM10, O3, and SO2, and no notable trends in CO during the COVID-19 pandemic. Both during and before the COVID-19 period, PM10, NO2, PM2.5, CO, and SO2 showed a negative correlation with the temperature and a moderately positive significant correlation between O3-8h and temperature. The findings of this study would help understand the air pollution circumstances in Xi’an before and during the COVID-19 period and offer helpful information regarding the implications of different air pollution control strategies.
基金supported by the project of National Natural Science Foundation of China(Grant No.42371203 and U21A2032)the project of Sichuan Provincial Science and Technology Department Program Funding(Grant No.2025YFHZ0010)the project of the Science and Technology Program of Aba City(Grant NO.R24YYJSYJ0001).
文摘Landslides pose a significant threat to both human society and environmental sustainability,yet,their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood.In this study,we projected global landslide susceptibility under four shared socioeconomic pathways(SSPs)from 2021 to 2100,utilizing multiple machine learning models based on precipitation data from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs)and static metrics.Our results indicate an overall upward trend in global landslide susceptibility under the SSPs compared to the baseline period(2001–2020),with the most significant increase of about 1%in the very far future(2081–2100)under the high emissions scenario(SSP5-8.5).Currently,approximately 13%of the world’s land area is at very high risk of landslide,mainly in the Cordillera of the Americas and the Andes in South America,the Alps in Europe,the Ethiopian Highlands in Africa,the Himalayas in Asia,and the countries of East and South-East Asia.Notably,India is the country most adversely affected by climate change,particularly during 2081–2100 under SSP3-7.0,with approximately 590 million people—23 times the global average—living in areas categorized as having very high susceptibility.
基金supported by the National Key R&D Program of China(2023YFC2308300,2023YFC2308302,2023YFE0116000,2022YFC2305200,2022YFC2305202)Beijing Research Ward Excellence Program(BRWEP,2024W042180108)+2 种基金the High-Level Public Health Specialized Talents Project of Beijing Municipal Health Commission(2022-2-018,2022-1-007)the Beijing Key Laboratory for HIV/AIDS Research(BZ0089),the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0484)the SEU Innovation Capability Enhancement Plan for Doctoral Students(CXJH_SEU 24042).
文摘Prior research indicated low genotypic resistance testing(GRT)for human immunodeficiency virus(HIV)utilization in China due to partial cost coverage under national antiretroviral therapy policies,limited testing accessibility,and financial barriers.Temporal and spatial data on GRT trends were also scarce.We analyzed GRT patterns among 6,895 untreated individuals at a tertiary hospital using Joinpoint regression,multivariable logistic modeling,and spatial analysis(GeoDa/SatScan).GRT rates showed a significant two-phase upward trend,increasing from 5.36%in 2014 to 74.17%in 2023,with an average annual percentage change of 31.30%(P<0.001).Beijing residency(adjusted odds ratio[aOR]=2.596,95%confidence interval[CI]:2.307-2.921)and older age were associated with higher GRT uptake.Specifically,ages 35-44 years(aOR=1.207,95%CI:1.026-1.420),45-54 years(aOR=1.335,95%CI:1.104-1.613),and≥55 years(aOR=1.424,95%CI:1.126-1.802)had significantly higher odds of testing.Lower testing rates were observed in individuals with lower education attainment(high school or technical secondary:aOR=0.827;junior high school:aOR=0.835;primary school:aOR=0.695),unknown sexually transmitted diseases(STDs)history(aOR=0.415),and non-heterosexual transmission routes(homosexual:aOR=0.834).Spatial analysis identified GRT clustering across Beijing until 2021,with two space-time clusters identified in 2019-2023 and 2018-2022.This study demonstrates substantial increase in GRT uptake achieving more balanced district-level distribution since 2021.Age,educational attainment,STDs history,and transmission route influence GRT utilization.Improving access,reducing costs,and implementing targeted interventions are critical for optimizing testing and guiding antiretroviral therapy decisions.
基金supported by The CAS/SAFEA International Partnership Program for Creative Research Teams(KZZD-EW-TZ-07-09)Foundation for Excellent Young Scholars of Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences(DLSYQ13004)One Hundred Talents Program in Chinese Academy of Sciences(Grant No.Y3H1051001)
文摘Rapid urbanization and urban greening have caused great changes to urban forests in China. Understanding spatiotemporal patterns of urban forest leaf area index(LAI) under rapid urbanization and urban greening is important for urban forest planning and management. We evaluated the potential for estimating urban forest LAI spatiotemporally by using Landsat TM imagery. We collected three scenes of Landsat TM(thematic mapper)images acquired in 1997, 2004 and 2010 and conducted a field survey to collect urban forest LAI. Finally, spatiotemporal maps of the urban forest LAI were created using a NDVI-based urban forest LAI predictive model.Our results show that normalized differential vegetation index(NDVI) could be used as a predictor for urban forest LAI similar to natural forests. Both rapid urbanization and urban greening contribute to the changing process of urban forest LAI. The urban forest has changed considerably from 1997 to 2010. Urban vegetated pixels decreased gradually from 1997 to 2010 due to intensive urbanization.Leaf area for the study area was 216.4, 145.2 and173.7 km~2 in the years 1997, 2004 and 2010, respectively.Urban forest LAI decreased sharply from 1997 to 2004 and increased slightly from 2004 to 2010 because of numerous greening policies. The urban forest LAI class distributions were skewed toward low values in 1997 and 2004. Moreover, the LAI presented a decreasing trend from suburban to downtown areas. We demonstrate the usefulness of TM remote-sensing in understanding spatiotemporal changing patterns of urban forest LAI under rapid urbanization and urban greening.
基金The Second Tibetan Plateau Scientific Expedition and Research Program(STEP),No.2019QZKK0608。
文摘In this study,the interplay between ecosystem services and human well-being in Seni district,which is a pastoral region of Nagqu city on the Qinghai-Tibet Plateau,is investigated.Employing the improved InVEST model,CASA model,coupling coordination model,and hierarchical clustering method,we analyze the spatiotemporal patterns of ecosystem services,the levels of resident well-being levels,and the interrelationships between these factors over the period from 2000 to 2018.Our findings reveal significant changes in six ecosystem services,with water production decreasing by 7.1%and carbon sequestration and soil conservation services increasing by approximately 6.3%and 14.6%,respectively.Both the habitat quality and landscape recreation services remained stable.Spatially,the towns in the eastern and southern areas exhibited higher water production and soil conservation services,while those in the central area exhibited greater carbon sequestration services.The coupling and coordination relationship between ecosystem services and human well-being improved significantly over the study period,evolving from low-level coupling to coordinated coupling.Hierarchical clustering was used to classify the 12 town-level units into five categories.Low subjective well-being townships had lower livestock breeding services,while high subjective well-being townships had higher supply,regulation,and support ecosystem services.Good transportation conditions were associated with higher subjective well-being in townships with low supply services.We recommend addressing the identified transportation disparities and enhancing key regulatory and livestock breeding services to promote regional sustainability and improve the quality of life for Seni district residents,thus catering to the diverse needs of both herdsmen and citizens.
文摘Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analyze the popularity of certain research topics,well-adopted methodologies,influential authors,and the interrelationships among research disciplines.However,the visual exploration of the patterns of research topics with an emphasis on their spatial and temporal distribution remains challenging.This study combined a Space-Time Cube(STC)and a 3D glyph to represent the complex multivariate bibliographic data.We further implemented a visual design by developing an interactive interface.The effectiveness,understandability,and engagement of ST-Map are evaluated by seven experts in geovisualization.The results suggest that it is promising to use three-dimensional visualization to show the overview and on-demand details on a single screen.
文摘Objective To analyze the epidemiological characteristics of measles,mumps,and rubella(MMR)between 2014 and 2021 and identify potential strategies and measures for the prevention and control of MMR in China.Methods Data on MMR was obtained from China’s National Notifiable Disease Reporting System for the period from 2014 to 2021.Spatiotemporal distributions were analyzed using SaTScan;temporal trends were analyzed using JoinPoint;and clusters were visualized using ArcGIS.Results A total of 1,808,067 cases of MMR were reported from 2014 to 2021 in China’s mainland,most of which were children and students under the age of 20.The incidence of measles declined during 2014-2021,whereas that of mumps and rubella peaked in 2019.MMR-reported cases generally peaked from March to July;however,high numbers of mumps cases were reported from September to November in 2020-2021.Measles and rubella clusters predominantly occurred in Western China,whereas clusters of mumps were generally found in the southern region.Conclusion The relatively heterogeneous epidemiological characteristics of MMR have highlighted the weaknesses and gaps in surveillance and timely control of MMR transmission in China’s mainland.Real-time and intelligent monitoring data should be collected for evidence-based early interventions。
基金Non-profit Research Foundation for Agriculture, No.200803036National Natural Science Foundation of China, No.40635029
文摘Based on TM image data and other survey materials, this paper analyzed the spatiotemporal patterns of land use change in the Bohai Rim during 1985-2005. The findings of this study are summarized as follows： （1） Land use pattern changed dramatically during 1985-2005. Industrial and residential land in urban and rural areas increased by 643,946 hm2 of which urban construction land had the largest and fastest increase of 294,953 hm2 at an annual rate of 3.72%. （2） The outward migration of rural population did not prevent the expansion of residential land in rural areas by 184,869 hm2. This increase reveals that construction of rural residences makes seriously wasteful and inefficient use of land. （3） Arable land, woodland and grassland decreased at a rate of -0.02%, -0.12% and -1.32% annually, while unused land shrank by 157,444 hm^2 at an annual rate of -1.69%. （4） The change of land use types showed marked fluctuations over the two stages （1985-1995 and 1995-2005） In particular, arable land, woodland and unused land experienced an inversed trend of change. （5） There was a significant interaction between arable land and woodland, industrial construction land in urban and rural areas showed a net trend of increase during the earlier period, but only adjustment to its internal structure during the second period. The loss of arable land to the construction of factories, mines and residences took place mainly in the fringe areas of large and medium-sized cities, along the routes of major roads, as well as in the economically developed coastal areas in the east. Such changes are closely related to the spatial differentiation of the level of urbanization and industrialization in the region.
基金National Natural Science Foundation of China(No.42171448)。
文摘Humanities and Social Sciences(HSS) are undergoing the transformation of spatialization and quantification. Geo-computation, with geoinformatics(including RS: Remote Sensing;GIS: Geographical Information System;GNSS: Global Navigation Satellite System), provides effective computational and spatialization methods and tools for HSS. Spatial Humanities and Geo-computation for Social Sciences(SH&GSS) is a field coupling geo-computation, and geoinformatics, with HSS. This special issue accepted a set of contributions highlighting recent advances in methodologies and applications of SH&GSS, which are related to sentiment spatial analysis from social media data, emotional change spatial analysis from news data, spatial analysis of social media related to COVID-19, crime spatiotemporal analysis, “double evaluation” for Land Use/Land Cover(LUCC), Specially Protected Natural Areas(SPNA) analysis, editing behavior analysis of Volunteered Geographic Information(VGI), electricity consumption anomaly detection, First and Last Mile Problem(FLMP) of public transport, and spatial interaction network analysis for crude oil trade network. Based on these related researches, we aim to present an overview of SH&GSS, and propose some future research directions for SH&HSS.
文摘The spatial diffusion of information is a process governed by the flow of interpersonal communication.The emergence of the Internet and especially social media platforms has reshaped this process and previous research has studied how online social networks contribute to the diffusion of information.Understanding such processes can help devise methods to maximize or control the reach of information or even identify upcoming events and social movements.Yet activities in cyberspace are still confined to physical locations and this geographic connection tends to be overlooked.In this research,we focus on geographic regions instead of individuals and study how the underlying hierarchical structure of regions relates to their response to the information.We examined the top 30 populated cities and metropolitan areas in the U.S.and retrieved Twitter data related to two selected topics from these regions,the 2015 Nepal Earthquake and the#JesuisCharlie hashtag in response to the Paris attacks on the Charlie Hebdo offices.We analyzed the similarity among regions of their response using multiple statistical methods and three urban classifications.Our results indicate that the diffusion of information is impacted by the hierarchy of urban regions and that the Twitter responses act more similar when the populated regions are positioned at the same level in the urban hierarchy.
基金This research was funded by the Norwegian Research Council(Grant No.286773)the National Natural Science Foundation of China(Grant No.41861134038)through the CHINOR bilateral research project Mi-tiStress,China Scholarship Council(Grant No.201906410051)the Fundamental Research Funds for National Universities,China University of Geosciences(Wuhan)(Grant No.2201710266).Hu acknowledges the help from Dr.Ceccherini for the forest harvested maps.
文摘Mapping spatiotemporal land cover changes offers opportunities to better understand trends and drivers of envi-ronmental change and helps to identify more sustainable land management strategies.This study investigates the spatiotemporal patterns of changes in land covers,forest harvest areas and soil erosion rates in Nordic countries,namely Norway,Sweden,Finland,and Denmark.This region is highly sensitive to environmental changes,as it is experiencing high levels of human pressure and among the highest rates of global warming.An analysis that uses consistent land cover dataset to quantify and compares the recent spatiotemporal changes in land cover in the Nordic countries is missing.The recent products issued by the European Space Agency and the Copernicus Climate Change Service framework provide the possibility to investigate the historical land cover changes from 1992 to 2018 at 300 m resolution.These maps are then integrated with time series of forest harvest areas be-tween 2004 and 2018 to study if and how forest management is represented in land cover products,and with soil erosion data to explore status and recent trends in agricultural land.Land cover changes typically involved from 4%to 9%of the total area in each country.Wetland showed the strongest reduction(11,003 km^(2),−11%of the wetland area in 1992),followed by forest(8,607 km^(2),−1%)and sparse vegetation(5,695 km^(2),−7%),while agriculture(15,884 km^(2),16%)and settlement(3,582 km^(2),84%)showed net increases.Wetland shrinkage dominated land cover changes in Norway(5,870 km^(2),−18%),followed by forest and grassland with a net gain of 3,441 km^(2)(3%)and 3,435 km^(2)(10%),respectively.In Sweden,forest areas decreased 13,008 km^(2)(−4%),mainly due to agriculture expansion(9,211 km^(2),29%).In Finland,agricultural areas increased by 5,982 km^(2)(24%),and wetland decreased by 6,698 km^(2)(−22%).Settlement had the largest net growth in Denmark(717 km^(2),70%),mainly from conversion of agriculture land.Soil erosion rates in Nordic countries are lower than the global average,but they are exacerbating in several locations(especially western Norway).The integration of the land cover datasets with maps of forest harvest areas shows that the majority of the losses in forest cover due to forestry operations are largely undetected,but a non-negligible share of the forest-to-agriculture(up to 19%)or forest-to-grassland(up to 51%)transitions overlap with the harvested sites.Forestry activity in the study region primarily involves small-scale harvest events that are difficult to be detected at the 300 m resolution of the land cover dataset.An accurate representation of forest management remains a challenge for global datasets of land cover time series,and more interdisciplinary international efforts are needed to address this gap.Overall,this analysis provides a detailed overview of recent changes in land cover and forest management in Nordic countries as represented by state-of-the-art global datasets,and offers insights to future studies aiming to improve these data or apply them in land surface models,climate models,landscape ecology,or other applications.
基金The author thanks E.D.F.S.L.Santos for the development of Python code and A.P.Ricieri for his example on the partition of the numbers between 1 and 9 into two clusters.This work was supported by the National Council for Scientific and Technological Development(CNPq)[304705/2015e2,404004/2016e4 and 305331/2018e3].
文摘This data-driven work aims to analyze and classify the spatiotemporal distribution of all Brazilian states considering data so diverse as the number of Covid-19 cases,deaths,confirmed cases per 100 k inhabitants,mortality per 100 k inhabitants and case fatality rates as health indicators.We also considered population,area and population density as geographic indicators.Finally,GDP and HDI were taken into account as economic and social criteria.For this task data were collected from April 3rd until August 8th,2020,corresponding to epidemiological weeks 14e32,reaching three million cases and a hundred thousand deaths.With this data it was possible to classify Brazilian states using multivariate methods into possible groups by means of non-hierarchical(k-means)cluster as well as factor analysis.It was possible to group all states plus the Federal District into five clusters,taking into account these 10 variables over the first five months of the epidemic.Group changes between states were observed over time and clusters,and between three and four factors were found.However,even with great difference on health indicators during days,the number of clusters remains fixed.Also,S^ao Paulo and Rio de Janeiro states were ranked at top list taking into account all epidemiological weeks.Correlations were observed between variables,such as the number of Covid cases and deaths with GDP for most of epidemiological weeks.Some clusters were more critical due to specific variables,including cities that are main hotspots.These multivariate findings would provide a comprehensive description of the ongoing Covid-19 epidemic and may help to guide subsequent studies to understand and control virus transmission.
