Agricultural drought,characterized by insufficient soil moisture crucial for crop growth,poses significant chal lenges to food security and economic sustainability,particularly in water-scarce regions like Senegal.Thi...Agricultural drought,characterized by insufficient soil moisture crucial for crop growth,poses significant chal lenges to food security and economic sustainability,particularly in water-scarce regions like Senegal.This study addresses this issue by developing a comprehensive geospatial monitoring system for agricultural drought using the Regional Hydrologic Extremes Assessment System(RHEAS).This system,with a high-resolution of 0.05°,effectively simulates daily soil moisture and generates the Soil Moisture Deficit Index(SMDI)-based agricultural drought monitoring.The SMDI derived from the RHEAS has effectively captured historical droughts in Senegal over the recent 30 years period from 1993 to 2022.The SMDI,also provides a comprehensive understanding of regional variations in drought severity(S),duration(D),and frequency(F),through S-D-F analysis to identify key drought hotspots across Senegal.Findings reveal a distinct north-south gradient in drought conditions,with the northern and central Senegal experiencing more frequent and severe droughts.The study highlights that Senegal experiences frequent short-duration droughts with high severity,resulting in extensive spatial impact.Addition ally,increasing trends in drought severity and duration suggest evolving climate change effects.These findings emphasize the urgent need for sustainable interventions to mitigate drought impacts on agricultural productiv ity.Specifically,the study identifies recurrent and intense drought hotspots affecting yields of staple crops like maize and rice,as well as cash crops like peanuts.The developed high-resolution drought monitoring system for Senegal not only identifies hotspots but also enables prioritizing sustainable approaches and adaptive strategies,ultimately sustaining agricultural productivity and resilience in Senegal’s drought-prone regions.展开更多
Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information ...Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information and providing navigation services.展开更多
A geospatial cyberinfrastructure is needed to support advanced GIScience research and education activities.However,the heterogeneous and distributed nature of geospatial resources creates enormous obstacles for buildi...A geospatial cyberinfrastructure is needed to support advanced GIScience research and education activities.However,the heterogeneous and distributed nature of geospatial resources creates enormous obstacles for building a unified and interoperable geospatial cyberinfrastructure.In this paper,we propose the Geospatial Service Web(GSW)to underpin the development of a future geospatial cyberinfrastructure.The GSW excels over the traditional spatial data infrastructure by providing a highly intelligent geospatial middleware to integrate various geospatial resources through the Internet based on interoperable Web service technologies.The development of the GSW focuses on the establishment of a platform where data,information,and knowledge can be shared and exchanged in an interoperable manner.Theoretically,we describe the conceptual framework and research challenges for GSW,and then introduce our recent research toward building a GSW.A research agenda for building a GSW is also presented in the paper.展开更多
With the increase of different sensors,applications and customers,the demand from data providers and users is for a new geospatial data service model,which supports low cost,high dexterity,and which would provide a co...With the increase of different sensors,applications and customers,the demand from data providers and users is for a new geospatial data service model,which supports low cost,high dexterity,and which would provide a comprehensive service.Based on such requirements and demands,the 21AT TripleSat constellation terminal and data delivery and management system has been developed by a Beijing based high-tech enterprise,Twenty First Century Aerospace Technology Co.,Ltd.(21AT).The company is the first commercial Earth observation satellite operator and service provider in China.This new geospatial data service model allows the user to directly access multi-source satellite data,manage the data order,and carry out automatic massive data production and delivery.The solution also implements safe and hierarchical user management,statistical data analysis,and automatic information reports.In addition,a mobile application is also available for users to easily access system functions.This new geospatial solution has already been successfully applied and installed in many customer sites in China,and is now available globally for international clients interested in fast geospatial solutions.It enables the success of customers’operational services.Besides providing TripleSat Constellation images,the multi-source data access system also allows the users to access other satellite data sources,based on customized agreement.This paper describes and discusses this new geospatial data service model.展开更多
This study investigated the integration of geospatial technologies within smart city frameworks to achieve the European Union’s climate neutrality goals by 2050. Focusing on rapid urbanization and escalating climate ...This study investigated the integration of geospatial technologies within smart city frameworks to achieve the European Union’s climate neutrality goals by 2050. Focusing on rapid urbanization and escalating climate challenges, the research analyzed how smart city frameworks, aligned with climate neutrality objectives, leverage geospatial technologies for urban planning and climate action. The study included case studies from three leading European cities, extracting lessons and best practices in implementing Climate City Contracts across sectors like energy, transport, and waste management. These insights highlighted the essential role of EU and national authorities in providing technical, regulatory, and financial support. Additionally, the paper presented the application of a WEBGIS platform in Limassol Municipality, Cyprus, demonstrating citizen engagement and acceptance of the proposed geospatial framework. Concluding with recommendations for future research, the study contributed significant insights into the advancement of urban sustainability and the effectiveness of geospatial technologies in smart city initiatives for combating climate change.展开更多
The 2030 Agenda for Sustainable Development provides a new global policy to guide the way countries collectively manage and transform the social,economic,and environmental dimensions of people and the planet over the ...The 2030 Agenda for Sustainable Development provides a new global policy to guide the way countries collectively manage and transform the social,economic,and environmental dimensions of people and the planet over the next 15 years.Achieving sustainable development presents all countries and the global policy community with a set of significant development challenges that are almost entirely geographic in nature.Many of the issues impacting sustainable development can be analyzed,modeled,and mapped within a geographic context,which in turn can provide the integrative framework necessary for global collaboration,consensus and evidence-based decision-making.However,and despite significant advances in geospatial information technologies,there is a lack of awareness,understanding and uptake,particular at the policy and decision-making level,of the vital and integrative role of geospatial information and related enabling architectures such as National Spatial Data Infrastructures.This paper reasons that the role of geospatial information in contributing to sustainable development has not adequately been described by either the sustainable development policy practice or by the geospatial professional community.This lack of policy and guidance,with commensurate critical gaps and connection points with national geospatial frameworks,is a visible impediment to developing countries and those most affected by the challenges and need to achieve sustainable development.The global geospatial community now has a unique opportunity to integrate and connect geospatial information into the global development agenda in a more holistic and sustainable manner,specifically in contributing their data resources toward measuring and monitoring the 17 Sustainable Development Goals,and their 169 associated targets,through the global indicator framework that anchors the 2030 Agenda for Sustainable Development.This paper introduces and discusses a new strategic framework for linking a global policy to national geospatial capabilities.展开更多
Aiming at the integrative management and comprehensive applications of large-scale 3D geospatial information covering the full 3D space of a city, this paper briefly introduces the design and implementation of a full ...Aiming at the integrative management and comprehensive applications of large-scale 3D geospatial information covering the full 3D space of a city, this paper briefly introduces the design and implementation of a full 3D GIS platform： GeoScope, which provides a professional solution for the massive full three-dimensional geospatial data integration, management, analysis, visualization, and applications. GeoScope is characterized by： （1） extendible software architecture based on the hierarchical message bus, facilitates multimodal integrative applications of 2D GIS and 3D GIS; （2） unified 3D city models, support multiscale se- mantic representation of outdoor ＆ indoor and aboveground ＆ underground 3D objects; （3） high-efficient 3D geospatial database engine, supports integrated management of massive 3D geospatial data for real-time applications; and （4） high-performance visualization engine exploiting the massively parallel computation architecture of modem GPUs, supports real-time realistic rendering of large-scale complicated 3D geospatial environments. The successful pilot application of GeoScope is also illustrated with the 3D city models of 8494 knl2 of the whole Wuhan City, the largest city in middle China.展开更多
For centuries,humans’capacity to capture and depict physical space has played a central role in industrial and societal development.However,the digital revolution and the emergence of networked devices and services a...For centuries,humans’capacity to capture and depict physical space has played a central role in industrial and societal development.However,the digital revolution and the emergence of networked devices and services accelerate geospatial capture,coordination,and intelligence in unprecedented ways.Underlying the digital transformation of industry and society is the fusion of the physical and digital worlds-‘perceptality’-where geospatial perception and reality merge.This paper analyzes the myriad forces that are driving perceptality and the future of geospatial intelligence and presents real-world implications and examples of its industrial application.Applications of sensors,robotics,cameras,machine learning,encryption,cloud computing and other software,and hardware intelligence are converging,enabling new ways for organizations and their equipment to perceive and capture reality.Meanwhile,demands for performance,reliability,and security are pushing compute‘to the edge’where real-time processing and coordination are vital.Big data place new restraints on economics,as pressures abound to actually use these data,both in real-time and for longer term strategic analysis and decision-making.These challenges require orchestration between information technology(IT)and operational technology(OT)and synchronization of diverse systems,data-sets,devices,environments,workflows,and people.展开更多
This paper presents a brief overview of the geospatial technologies developed and applied in Chang’e-3 and Chang’e-4 lunar rover missions.Photogrammetric mapping techniques were used to produce topographic products ...This paper presents a brief overview of the geospatial technologies developed and applied in Chang’e-3 and Chang’e-4 lunar rover missions.Photogrammetric mapping techniques were used to produce topographic products of the landing site with meter level resolution using orbital images before landing,and to produce centimeter-resolution topographic products in near real-time after landing.Visual positioning techniques were used to determine the locations of the two landers using descent images and orbital basemaps immediately after landing.During surface operations,visual-positioning-based rover localization was performed routinely at each waypoint using Navcam images.The topographic analysis and rover localization results directly supported waypoint-to-waypoint path planning,science target selection and scientific investigations.A GIS-based digital cartography system was also developed to support rover teleoperation.展开更多
Although big data are widely used in various fields,its application is still rare in the study of mining subsidence prediction(MSP)caused by underground mining.Traditional research in MSP has the problem of oversimpli...Although big data are widely used in various fields,its application is still rare in the study of mining subsidence prediction(MSP)caused by underground mining.Traditional research in MSP has the problem of oversimplifying geological mining conditions,ignoring the fluctuation of rock layers with space.In the context of geospatial big data,a data-intensive FLAC3D(Fast Lagrangian Analysis of a Continua in 3 Dimensions)model is proposed in this paper based on borehole logs.In the modeling process,we developed a method to handle geospatial big data and were able to make full use of borehole logs.The effectiveness of the proposed method was verified by comparing the results of the traditional method,proposed method,and field observation.The findings show that the proposed method has obvious advantages over the traditional prediction results.The relative error of the maximum surface subsidence predicted by the proposed method decreased by 93.7%and the standard deviation of the prediction results(which was 70 points)decreased by 39.4%,on average.The data-intensive modeling method is of great significance for improving the accuracy of mining subsidence predictions.展开更多
Earthquake prediction is currently the most crucial task required for the probability,hazard,risk mapping,and mitigation purposes.Earthquake prediction attracts the researchers'attention from both academia and ind...Earthquake prediction is currently the most crucial task required for the probability,hazard,risk mapping,and mitigation purposes.Earthquake prediction attracts the researchers'attention from both academia and industries.Traditionally,the risk assessment approaches have used various traditional and machine learning models.However,deep learning techniques have been rarely tested for earthquake probability mapping.Therefore,this study develops a convolutional neural network(CNN)model for earthquake probability assessment in NE India.Then conducts vulnerability using analytical hierarchy process(AHP),Venn's intersection theory for hazard,and integrated model for risk mapping.A prediction of classification task was performed in which the model predicts magnitudes more than 4 Mw that considers nine indicators.Prediction classification results and intensity variation were then used for probability and hazard mapping,respectively.Finally,earthquake risk map was produced by multiplying hazard,vulnerability,and coping capacity.The vulnerability was prepared by using six vulnerable factors,and the coping capacity was estimated by using the number of hospitals and associated variables,including budget available for disaster management.The CNN model for a probability distribution is a robust technique that provides good accuracy.Results show that CNN is superior to the other algorithms,which completed the classification prediction task with an accuracy of 0.94,precision of 0.98,recall of 0.85,and F1 score of 0.91.These indicators were used for probability mapping,and the total area of hazard(21,412.94 km^(2)),vulnerability(480.98 km^(2)),and risk(34,586.10 km^(2))was estimated.展开更多
t LBS （location-based service） is a remarkable outcome of the development from GIS to geospatial information service. Faced by the requirements of geospatial information from the masses and the opportunity provided ...t LBS （location-based service） is a remarkable outcome of the development from GIS to geospatial information service. Faced by the requirements of geospatial information from the masses and the opportunity provided by the next generation lnternet and Web 2.0, a new model of geospatial information service based on DMI （digital measurable image） is presented. First, the con- cept of LBS and the opportunities of Web 2.0 are introduced, then the characteristic of DMI is discussed. Taking the Image City.Wuhan as an example, the function ofgeospatial information service based on DM! is introduced. Finally, the feasibility for its industrialization is discussed.展开更多
Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes.Health and education are critical domains of the Unites Nations’...Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes.Health and education are critical domains of the Unites Nations’Sus-tainable Development Goals(SDGs),yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale studies.This means that such studies lack accessibility metrics for large-scale quantitative evaluations.To address this deficiency,we evaluated the accessibility of health and education ser-vices in China's Mainland in 2021 using point-of-interest data,OpenStreetMap road data,land cover data,and WorldPop spatial demographic data.The accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 h.On the basis of the road network and land cover information,the overall average time costs of reaching hospital and school were 20 and 22 min,respectively.In terms of population coverage,94.7%and 92.5%of the population in China has a time cost of less than 1 h in obtaining hospital and school services,respectively.Counties with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions,with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological areas.Furthermore,the cumulative time cost incurred by the bottom 20%of counties(by GDP)from access to hospital and school services reached approximately 80%of the national total.Low-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP counties.The accessibil-ity metrics proposed in this study are highly related to SDGs 3 and 4,and they can serve as auxiliary data that can be used to enhance the evaluation of SDG outcomes.The analysis of the uneven distribution of health and education services in China can help identify areas with backward public services and may contribute to targeted and efficient policy interventions.展开更多
Based on the developing tendency of present China’s basic GIS,this paper discusses the designing idea for scales of 1∶10 000,1∶50 000, 1∶250 000 and 1∶1 000 000 pyramid_like multi_layer and multi_resolution of th...Based on the developing tendency of present China’s basic GIS,this paper discusses the designing idea for scales of 1∶10 000,1∶50 000, 1∶250 000 and 1∶1 000 000 pyramid_like multi_layer and multi_resolution of the basic GIS.A technical line for the construction of basic GIS of the whole country and various provinces for sustainable development is put forward.And some important theoretical GIS issues touched by the technical process are discussed.展开更多
This paper examines the current state of three of the key areas of geospatial science in Australia:positioning;earth observation(EO);and spatial infrastructures.The paper discusses the limitations and challenges that ...This paper examines the current state of three of the key areas of geospatial science in Australia:positioning;earth observation(EO);and spatial infrastructures.The paper discusses the limitations and challenges that will shape the development of these three areas of geospatial science over the next decade and then profiles what each may look like in about 2026.Australia’s national positioning infrastructure plan is guiding the development of a nation-wide,sub decimeter,real-time,outdoor positioning capability based on multi-GNSS and in particular the emerging precise point positioning−real-time kinematic(PPP-RTK)capability.Additional positioning systems including the ground-based Locata system,location-based indoor systems,and beacons,among others are also discussed.The importance of the underpinning role of a next generation dynamic datum is considered.The development of Australia’s first EO strategy is described along with the key national needs of the products of remote sensing.The development of massive on-line multi-decadal geospatial imagery data stores and processing engines for co-registered stacks of continuous base-line satellite imagery are explored.Finally,perspectives on the evolution of a future spatial knowledge infrastructure(SKI)emerging from today’s traditional spatial data infrastructures(SDIs)are provided together with discussion of the growing importance of geospatial analytics for transforming whole supply chains.展开更多
In light of growing urban traffic,car parking becomes increasingly critical for cities to manage.As a result,the prediction of parking occupancy has sparked significant research interest in recent years.While many ext...In light of growing urban traffic,car parking becomes increasingly critical for cities to manage.As a result,the prediction of parking occupancy has sparked significant research interest in recent years.While many external data sources have been considered in the prediction models,the underlying geographic context has mostly been ignored.Thus,in order to study the contribution of geospatial information to parking occupancy prediction models,road network centrality,land use,and Point of Interest(POI)data were incorporated in Random Forest(RF)and Artificial Neural Network(ANN,specifically Feedforward Neural Network FFNN)prediction models in this work.Model performances were compared to a baseline,which only considers historical and temporal input data.Moreover,the influence of the amount of training data,the prediction horizon,and the spatial variation of the prediction were explored.The results show that the inclusion of geospatial information led to a performance improvement of up to 25%compared to the baseline.Besides,as the prediction horizon expanded,predictions became less reliable,while the relevance of geospatial data increased.In general,land use and POI data proved to be more beneficial than road network centrality.The amount of training data did not have a significant influence on the performance of the RF model.The ANN model,conversely,achieved optimal results on a training input of 5 days.Likely attributable to varying occupancy patterns,prediction performance disparities could be identified for different parking districts and street segments.Generally,the RF model outperformed the ANN model on all predictions.展开更多
It is common knowledge that Yarmouk River Basin(YRB)is shared between Jordan and Syria.Management of YRB trans-boundary water resources is attracting increasing interest because it is a strategic water resource for th...It is common knowledge that Yarmouk River Basin(YRB)is shared between Jordan and Syria.Management of YRB trans-boundary water resources is attracting increasing interest because it is a strategic water resource for the riparian countries.Actually,lack of sharing information regarding hydrological flows and basin’s water management between partners’countries makes it difficult to distinguish between natural and man-made factors affecting the water body.Therefore,this study seeks to address and assess the main on-site changes that exert on YRB.Geospatial technique and arithmetic equations were combined to carry out an assessment of the changes on water resources in YRB.Data,information and field measurements of the basin were aggregated,compiled and presented to determine the extent of changes during the period 1980-2020.Remarkable findings showed that precipitation amount in the basin significantly declined during the period 1980-2020 in particularly after the year 1992.Pumping rate of groundwater was 550 x 103 m3/a,exceeding the basin’s safe yield.Draw down of static groundwater level over time approached the value of-3.2 m/a due to the over abstraction in the aquifer body.Additionally,the evaporation rate reached more than 99%in some regions in the basin.Moreover,the number of private wells has increased from 98 wells in 1980 to 126 wells in 2020,showing the excessive extraction of groundwater.These findings indicate that the study area is subjected to a considerable groundwater depletion in the near future due to extensive abstraction,continuous drilling of illegal wells and decreased annual precipitation under the shadow of the rapid population growth and continuous influx of refugees.Therefore,decision makers-informed scenarios are suggested in the development of water resource portfolios,which involves the combination of management and infrastructural actions that enhance the water productivity of the basin.Further studies are recommended to evaluate the on-site changes on water resources in YRB in collaboration with riparian countries and to establish monitoring system for continuous and accurate measurements of the basin.展开更多
Since the introduction of geographic information systems(GIS)in the 1960s,it has evolved tremendously to an extent that it permeates our daily lives.Initially,GIS usage started in the developed countries and now incre...Since the introduction of geographic information systems(GIS)in the 1960s,it has evolved tremendously to an extent that it permeates our daily lives.Initially,GIS usage started in the developed countries and now increasingly filtered to developing countries.The town planning profession was one of the early adopters of GIS.Geospatial information is a useful source of data that is needed in urban planning.In these days of the New Urban Agenda 2030,smart cities are even more required from planners in using geospatial information to face urban challenges such as sustainable urban development and climate change.Although GIS has promised a lot for urban planning,it has not reached its full potential.Moreover,many studies have focused on developed countries with limited studies on geospatial information application in municipalities and GIS education from a perspective of developing countries.In this study,a survey on the usage of geospatial information science(GSIS)in two cities,namely Bulawayo in Zimbabwe and Ekurhuleni in South Africa,was conducted,and an overview of the state of GIS curricula in planning schools is discussed.The results indicate that considerable progress has been made in the application of geospatial information in municipal planning;however,there are impediments limiting the full utilization of geospatial information in local municipalities.These impediments include:inadequate GIS curricula in planning schools,lack of resources,and lack of political will.These challenges manifest differently in well-resourced municipalities and those with limited resources.The study proposes planning-relevant GIS curricula to improve the level of GIS use in planning practice.展开更多
Inserting Groundwater quality variability and sources potentially contributing to aquifer recharge was evaluated in metropolitan Karachi. Selected sampling sites were characterized by large waste dumping sites, indust...Inserting Groundwater quality variability and sources potentially contributing to aquifer recharge was evaluated in metropolitan Karachi. Selected sampling sites were characterized by large waste dumping sites, industrial zones, and the presence of open streams receiving heavy loads of industrial and domestic wastes. Levels of pH, electrical conductivity (EC), fluoride (F-), chloride (Cl-), bromide (Br-), nitrate-N (NO-3-N), sulfate (SO2-4), sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), and ammonium (NH+4) were determined and compared with the WHO permissible limits. Concentrations of the measured ions were in the order of Cl- > Na+ > SO2-4 > Mg2+ > Ca2+ > NO-3-N > K+ > F- > Br-. EC values were above the WHO guidelines, representing the presence of high ionic concentration in the groundwater. The health risk index (HRI) for indicated that inhabitants of Karachi are at risk of high exposure. Ingestion of high concentrations of NO-3-N in water can cause methemoglobinemia and birth defects. Results of multivariate statistical analysis, principal component analysis (PCA), cluster analysis (CA), and geographic information system (GIS) map analysis revealed that human activities are leading to adverse effects on the existing groundwater quality in Karachi.展开更多
Most cities around the world, including Abuja Municipal are being faced with an undesirable increased in air temperature. This is indicated by an increase in non-porous, non-evaporating, highly thermal conductive surf...Most cities around the world, including Abuja Municipal are being faced with an undesirable increased in air temperature. This is indicated by an increase in non-porous, non-evaporating, highly thermal conductive surfaces such as concrete and asphalt, which has replaced the vegetation biomass resulting to the formation of urban heat island. There is an increasing need for studies on the changing trend of UHI intensity in cities. This research employed geospatial techniques to determine the urban heat island intensity in Abuja Municipal. Temperature characteristics over twenty selected rural and urban locations in Abuja, FCT were derived from the satellite image of 1986, 2001 and 2016 using the “Extract Multi Values to Point” tool in ArcGIS 10.4. These transects pass over various landscapes with different environmental settings, with the aim of understanding the factors shaping the city’s thermal landscape. The intervals of +15 years were deliberately chosen to ensure uniformity between the datasets. The results of this analysis indicate that UHII has been increasing, from 1986-2016, giving credence to the results of the spatial and temporal analysis of the land surface temperature, indicating the development phases had hit full stride. The different periods under study (1986, 2001 and 2016) were also tested using the student “t” test to determine the significant difference in the land surface temperature values to acknowledge the presence of a substantial urban heat island within the study area. The result reveals the calculated “t” values of 2.50, 3.34, 5.57 of 1986, 2001 and 2016 respectively, are higher than the critical value of “t” at 0.05 being 1.73, thus, revealing the temperature differences between the urban and rural stations to be highly significant, indicating the presence of a strong urban heat island. Also, a slide difference in the temperature was observed with the Rubuchi and Karmajiji rural areas having higher temperature readings than their counterparts in the urban areas, Asokoro and Garki, with readings of <span style="white-space:nowrap;">−</span>0.4<span style="white-space:nowrap;">°</span>C and <span style="white-space:nowrap;">−</span>1.3<span style="white-space:nowrap;">°</span>C. Since effectiveness of a surface in reducing daytime urban air temperatures depends strongly on the amount of heating avoided, the study recommends preserving and replicating greenery, light coloured facades as measures to reduce the effects of urban heat island.展开更多
基金supported by the NASA(Grant No.80NSSC21K0403)USAID Kansas State University subcontract KSU-A20-0163-S035 with Michigan State University.
文摘Agricultural drought,characterized by insufficient soil moisture crucial for crop growth,poses significant chal lenges to food security and economic sustainability,particularly in water-scarce regions like Senegal.This study addresses this issue by developing a comprehensive geospatial monitoring system for agricultural drought using the Regional Hydrologic Extremes Assessment System(RHEAS).This system,with a high-resolution of 0.05°,effectively simulates daily soil moisture and generates the Soil Moisture Deficit Index(SMDI)-based agricultural drought monitoring.The SMDI derived from the RHEAS has effectively captured historical droughts in Senegal over the recent 30 years period from 1993 to 2022.The SMDI,also provides a comprehensive understanding of regional variations in drought severity(S),duration(D),and frequency(F),through S-D-F analysis to identify key drought hotspots across Senegal.Findings reveal a distinct north-south gradient in drought conditions,with the northern and central Senegal experiencing more frequent and severe droughts.The study highlights that Senegal experiences frequent short-duration droughts with high severity,resulting in extensive spatial impact.Addition ally,increasing trends in drought severity and duration suggest evolving climate change effects.These findings emphasize the urgent need for sustainable interventions to mitigate drought impacts on agricultural productiv ity.Specifically,the study identifies recurrent and intense drought hotspots affecting yields of staple crops like maize and rice,as well as cash crops like peanuts.The developed high-resolution drought monitoring system for Senegal not only identifies hotspots but also enables prioritizing sustainable approaches and adaptive strategies,ultimately sustaining agricultural productivity and resilience in Senegal’s drought-prone regions.
文摘Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information and providing navigation services.
基金This work is jointly supported by National Basic Research Program of China(Nos.2012CB719906 and 2011CB707105)National Natural Science Foundation of China(Nos.41023001,40801153 and 40901190).
文摘A geospatial cyberinfrastructure is needed to support advanced GIScience research and education activities.However,the heterogeneous and distributed nature of geospatial resources creates enormous obstacles for building a unified and interoperable geospatial cyberinfrastructure.In this paper,we propose the Geospatial Service Web(GSW)to underpin the development of a future geospatial cyberinfrastructure.The GSW excels over the traditional spatial data infrastructure by providing a highly intelligent geospatial middleware to integrate various geospatial resources through the Internet based on interoperable Web service technologies.The development of the GSW focuses on the establishment of a platform where data,information,and knowledge can be shared and exchanged in an interoperable manner.Theoretically,we describe the conceptual framework and research challenges for GSW,and then introduce our recent research toward building a GSW.A research agenda for building a GSW is also presented in the paper.
基金supported by the project of Beijing Municipal Science and Technology Commission and Science and Technology Innovation Base of Cultivating and Developing Engineering[grant number Z161100005016069]the National High Technology Research and Development Program[grant number 2013AA12A303].
文摘With the increase of different sensors,applications and customers,the demand from data providers and users is for a new geospatial data service model,which supports low cost,high dexterity,and which would provide a comprehensive service.Based on such requirements and demands,the 21AT TripleSat constellation terminal and data delivery and management system has been developed by a Beijing based high-tech enterprise,Twenty First Century Aerospace Technology Co.,Ltd.(21AT).The company is the first commercial Earth observation satellite operator and service provider in China.This new geospatial data service model allows the user to directly access multi-source satellite data,manage the data order,and carry out automatic massive data production and delivery.The solution also implements safe and hierarchical user management,statistical data analysis,and automatic information reports.In addition,a mobile application is also available for users to easily access system functions.This new geospatial solution has already been successfully applied and installed in many customer sites in China,and is now available globally for international clients interested in fast geospatial solutions.It enables the success of customers’operational services.Besides providing TripleSat Constellation images,the multi-source data access system also allows the users to access other satellite data sources,based on customized agreement.This paper describes and discusses this new geospatial data service model.
文摘This study investigated the integration of geospatial technologies within smart city frameworks to achieve the European Union’s climate neutrality goals by 2050. Focusing on rapid urbanization and escalating climate challenges, the research analyzed how smart city frameworks, aligned with climate neutrality objectives, leverage geospatial technologies for urban planning and climate action. The study included case studies from three leading European cities, extracting lessons and best practices in implementing Climate City Contracts across sectors like energy, transport, and waste management. These insights highlighted the essential role of EU and national authorities in providing technical, regulatory, and financial support. Additionally, the paper presented the application of a WEBGIS platform in Limassol Municipality, Cyprus, demonstrating citizen engagement and acceptance of the proposed geospatial framework. Concluding with recommendations for future research, the study contributed significant insights into the advancement of urban sustainability and the effectiveness of geospatial technologies in smart city initiatives for combating climate change.
文摘The 2030 Agenda for Sustainable Development provides a new global policy to guide the way countries collectively manage and transform the social,economic,and environmental dimensions of people and the planet over the next 15 years.Achieving sustainable development presents all countries and the global policy community with a set of significant development challenges that are almost entirely geographic in nature.Many of the issues impacting sustainable development can be analyzed,modeled,and mapped within a geographic context,which in turn can provide the integrative framework necessary for global collaboration,consensus and evidence-based decision-making.However,and despite significant advances in geospatial information technologies,there is a lack of awareness,understanding and uptake,particular at the policy and decision-making level,of the vital and integrative role of geospatial information and related enabling architectures such as National Spatial Data Infrastructures.This paper reasons that the role of geospatial information in contributing to sustainable development has not adequately been described by either the sustainable development policy practice or by the geospatial professional community.This lack of policy and guidance,with commensurate critical gaps and connection points with national geospatial frameworks,is a visible impediment to developing countries and those most affected by the challenges and need to achieve sustainable development.The global geospatial community now has a unique opportunity to integrate and connect geospatial information into the global development agenda in a more holistic and sustainable manner,specifically in contributing their data resources toward measuring and monitoring the 17 Sustainable Development Goals,and their 169 associated targets,through the global indicator framework that anchors the 2030 Agenda for Sustainable Development.This paper introduces and discusses a new strategic framework for linking a global policy to national geospatial capabilities.
基金the National High Technology Research and Development Program of China (863 Program) (No. 2008AA121600)the National BasicResearch Program of China (973 Program)(No. 2010CB731801)the National Natural Science Foundation of China (No. 40871212)
文摘Aiming at the integrative management and comprehensive applications of large-scale 3D geospatial information covering the full 3D space of a city, this paper briefly introduces the design and implementation of a full 3D GIS platform： GeoScope, which provides a professional solution for the massive full three-dimensional geospatial data integration, management, analysis, visualization, and applications. GeoScope is characterized by： （1） extendible software architecture based on the hierarchical message bus, facilitates multimodal integrative applications of 2D GIS and 3D GIS; （2） unified 3D city models, support multiscale se- mantic representation of outdoor ＆ indoor and aboveground ＆ underground 3D objects; （3） high-efficient 3D geospatial database engine, supports integrated management of massive 3D geospatial data for real-time applications; and （4） high-performance visualization engine exploiting the massively parallel computation architecture of modem GPUs, supports real-time realistic rendering of large-scale complicated 3D geospatial environments. The successful pilot application of GeoScope is also illustrated with the 3D city models of 8494 knl2 of the whole Wuhan City, the largest city in middle China.
基金supported by Hexagon AB,a global provider of information technologies for geospatial and industrial enterprises.
文摘For centuries,humans’capacity to capture and depict physical space has played a central role in industrial and societal development.However,the digital revolution and the emergence of networked devices and services accelerate geospatial capture,coordination,and intelligence in unprecedented ways.Underlying the digital transformation of industry and society is the fusion of the physical and digital worlds-‘perceptality’-where geospatial perception and reality merge.This paper analyzes the myriad forces that are driving perceptality and the future of geospatial intelligence and presents real-world implications and examples of its industrial application.Applications of sensors,robotics,cameras,machine learning,encryption,cloud computing and other software,and hardware intelligence are converging,enabling new ways for organizations and their equipment to perceive and capture reality.Meanwhile,demands for performance,reliability,and security are pushing compute‘to the edge’where real-time processing and coordination are vital.Big data place new restraints on economics,as pressures abound to actually use these data,both in real-time and for longer term strategic analysis and decision-making.These challenges require orchestration between information technology(IT)and operational technology(OT)and synchronization of diverse systems,data-sets,devices,environments,workflows,and people.
基金This work was supported by the National Natural Science Foundation of China[grant number 41671458,41590851,41941003,and 41771488].
文摘This paper presents a brief overview of the geospatial technologies developed and applied in Chang’e-3 and Chang’e-4 lunar rover missions.Photogrammetric mapping techniques were used to produce topographic products of the landing site with meter level resolution using orbital images before landing,and to produce centimeter-resolution topographic products in near real-time after landing.Visual positioning techniques were used to determine the locations of the two landers using descent images and orbital basemaps immediately after landing.During surface operations,visual-positioning-based rover localization was performed routinely at each waypoint using Navcam images.The topographic analysis and rover localization results directly supported waypoint-to-waypoint path planning,science target selection and scientific investigations.A GIS-based digital cartography system was also developed to support rover teleoperation.
文摘Although big data are widely used in various fields,its application is still rare in the study of mining subsidence prediction(MSP)caused by underground mining.Traditional research in MSP has the problem of oversimplifying geological mining conditions,ignoring the fluctuation of rock layers with space.In the context of geospatial big data,a data-intensive FLAC3D(Fast Lagrangian Analysis of a Continua in 3 Dimensions)model is proposed in this paper based on borehole logs.In the modeling process,we developed a method to handle geospatial big data and were able to make full use of borehole logs.The effectiveness of the proposed method was verified by comparing the results of the traditional method,proposed method,and field observation.The findings show that the proposed method has obvious advantages over the traditional prediction results.The relative error of the maximum surface subsidence predicted by the proposed method decreased by 93.7%and the standard deviation of the prediction results(which was 70 points)decreased by 39.4%,on average.The data-intensive modeling method is of great significance for improving the accuracy of mining subsidence predictions.
基金fully funded by the Center for Advanced Modeling and Geospatial Information Systems(CAMGIS),Faculty of Engineering and IT,University of Technology Sydneysupported by Researchers Supporting Project number RSP-2020/14,King Saud University,Riyadh,Saudi Arabia。
文摘Earthquake prediction is currently the most crucial task required for the probability,hazard,risk mapping,and mitigation purposes.Earthquake prediction attracts the researchers'attention from both academia and industries.Traditionally,the risk assessment approaches have used various traditional and machine learning models.However,deep learning techniques have been rarely tested for earthquake probability mapping.Therefore,this study develops a convolutional neural network(CNN)model for earthquake probability assessment in NE India.Then conducts vulnerability using analytical hierarchy process(AHP),Venn's intersection theory for hazard,and integrated model for risk mapping.A prediction of classification task was performed in which the model predicts magnitudes more than 4 Mw that considers nine indicators.Prediction classification results and intensity variation were then used for probability and hazard mapping,respectively.Finally,earthquake risk map was produced by multiplying hazard,vulnerability,and coping capacity.The vulnerability was prepared by using six vulnerable factors,and the coping capacity was estimated by using the number of hospitals and associated variables,including budget available for disaster management.The CNN model for a probability distribution is a robust technique that provides good accuracy.Results show that CNN is superior to the other algorithms,which completed the classification prediction task with an accuracy of 0.94,precision of 0.98,recall of 0.85,and F1 score of 0.91.These indicators were used for probability mapping,and the total area of hazard(21,412.94 km^(2)),vulnerability(480.98 km^(2)),and risk(34,586.10 km^(2))was estimated.
文摘t LBS （location-based service） is a remarkable outcome of the development from GIS to geospatial information service. Faced by the requirements of geospatial information from the masses and the opportunity provided by the next generation lnternet and Web 2.0, a new model of geospatial information service based on DMI （digital measurable image） is presented. First, the con- cept of LBS and the opportunities of Web 2.0 are introduced, then the characteristic of DMI is discussed. Taking the Image City.Wuhan as an example, the function ofgeospatial information service based on DM! is introduced. Finally, the feasibility for its industrialization is discussed.
基金This work was supported by the National Natural Science Foundation for Distinguished Young Scholars of China(Grant No.41725006).
文摘Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes.Health and education are critical domains of the Unites Nations’Sus-tainable Development Goals(SDGs),yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale studies.This means that such studies lack accessibility metrics for large-scale quantitative evaluations.To address this deficiency,we evaluated the accessibility of health and education ser-vices in China's Mainland in 2021 using point-of-interest data,OpenStreetMap road data,land cover data,and WorldPop spatial demographic data.The accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 h.On the basis of the road network and land cover information,the overall average time costs of reaching hospital and school were 20 and 22 min,respectively.In terms of population coverage,94.7%and 92.5%of the population in China has a time cost of less than 1 h in obtaining hospital and school services,respectively.Counties with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions,with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological areas.Furthermore,the cumulative time cost incurred by the bottom 20%of counties(by GDP)from access to hospital and school services reached approximately 80%of the national total.Low-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP counties.The accessibil-ity metrics proposed in this study are highly related to SDGs 3 and 4,and they can serve as auxiliary data that can be used to enhance the evaluation of SDG outcomes.The analysis of the uneven distribution of health and education services in China can help identify areas with backward public services and may contribute to targeted and efficient policy interventions.
文摘Based on the developing tendency of present China’s basic GIS,this paper discusses the designing idea for scales of 1∶10 000,1∶50 000, 1∶250 000 and 1∶1 000 000 pyramid_like multi_layer and multi_resolution of the basic GIS.A technical line for the construction of basic GIS of the whole country and various provinces for sustainable development is put forward.And some important theoretical GIS issues touched by the technical process are discussed.
文摘This paper examines the current state of three of the key areas of geospatial science in Australia:positioning;earth observation(EO);and spatial infrastructures.The paper discusses the limitations and challenges that will shape the development of these three areas of geospatial science over the next decade and then profiles what each may look like in about 2026.Australia’s national positioning infrastructure plan is guiding the development of a nation-wide,sub decimeter,real-time,outdoor positioning capability based on multi-GNSS and in particular the emerging precise point positioning−real-time kinematic(PPP-RTK)capability.Additional positioning systems including the ground-based Locata system,location-based indoor systems,and beacons,among others are also discussed.The importance of the underpinning role of a next generation dynamic datum is considered.The development of Australia’s first EO strategy is described along with the key national needs of the products of remote sensing.The development of massive on-line multi-decadal geospatial imagery data stores and processing engines for co-registered stacks of continuous base-line satellite imagery are explored.Finally,perspectives on the evolution of a future spatial knowledge infrastructure(SKI)emerging from today’s traditional spatial data infrastructures(SDIs)are provided together with discussion of the growing importance of geospatial analytics for transforming whole supply chains.
文摘In light of growing urban traffic,car parking becomes increasingly critical for cities to manage.As a result,the prediction of parking occupancy has sparked significant research interest in recent years.While many external data sources have been considered in the prediction models,the underlying geographic context has mostly been ignored.Thus,in order to study the contribution of geospatial information to parking occupancy prediction models,road network centrality,land use,and Point of Interest(POI)data were incorporated in Random Forest(RF)and Artificial Neural Network(ANN,specifically Feedforward Neural Network FFNN)prediction models in this work.Model performances were compared to a baseline,which only considers historical and temporal input data.Moreover,the influence of the amount of training data,the prediction horizon,and the spatial variation of the prediction were explored.The results show that the inclusion of geospatial information led to a performance improvement of up to 25%compared to the baseline.Besides,as the prediction horizon expanded,predictions became less reliable,while the relevance of geospatial data increased.In general,land use and POI data proved to be more beneficial than road network centrality.The amount of training data did not have a significant influence on the performance of the RF model.The ANN model,conversely,achieved optimal results on a training input of 5 days.Likely attributable to varying occupancy patterns,prediction performance disparities could be identified for different parking districts and street segments.Generally,the RF model outperformed the ANN model on all predictions.
文摘It is common knowledge that Yarmouk River Basin(YRB)is shared between Jordan and Syria.Management of YRB trans-boundary water resources is attracting increasing interest because it is a strategic water resource for the riparian countries.Actually,lack of sharing information regarding hydrological flows and basin’s water management between partners’countries makes it difficult to distinguish between natural and man-made factors affecting the water body.Therefore,this study seeks to address and assess the main on-site changes that exert on YRB.Geospatial technique and arithmetic equations were combined to carry out an assessment of the changes on water resources in YRB.Data,information and field measurements of the basin were aggregated,compiled and presented to determine the extent of changes during the period 1980-2020.Remarkable findings showed that precipitation amount in the basin significantly declined during the period 1980-2020 in particularly after the year 1992.Pumping rate of groundwater was 550 x 103 m3/a,exceeding the basin’s safe yield.Draw down of static groundwater level over time approached the value of-3.2 m/a due to the over abstraction in the aquifer body.Additionally,the evaporation rate reached more than 99%in some regions in the basin.Moreover,the number of private wells has increased from 98 wells in 1980 to 126 wells in 2020,showing the excessive extraction of groundwater.These findings indicate that the study area is subjected to a considerable groundwater depletion in the near future due to extensive abstraction,continuous drilling of illegal wells and decreased annual precipitation under the shadow of the rapid population growth and continuous influx of refugees.Therefore,decision makers-informed scenarios are suggested in the development of water resource portfolios,which involves the combination of management and infrastructural actions that enhance the water productivity of the basin.Further studies are recommended to evaluate the on-site changes on water resources in YRB in collaboration with riparian countries and to establish monitoring system for continuous and accurate measurements of the basin.
文摘Since the introduction of geographic information systems(GIS)in the 1960s,it has evolved tremendously to an extent that it permeates our daily lives.Initially,GIS usage started in the developed countries and now increasingly filtered to developing countries.The town planning profession was one of the early adopters of GIS.Geospatial information is a useful source of data that is needed in urban planning.In these days of the New Urban Agenda 2030,smart cities are even more required from planners in using geospatial information to face urban challenges such as sustainable urban development and climate change.Although GIS has promised a lot for urban planning,it has not reached its full potential.Moreover,many studies have focused on developed countries with limited studies on geospatial information application in municipalities and GIS education from a perspective of developing countries.In this study,a survey on the usage of geospatial information science(GSIS)in two cities,namely Bulawayo in Zimbabwe and Ekurhuleni in South Africa,was conducted,and an overview of the state of GIS curricula in planning schools is discussed.The results indicate that considerable progress has been made in the application of geospatial information in municipal planning;however,there are impediments limiting the full utilization of geospatial information in local municipalities.These impediments include:inadequate GIS curricula in planning schools,lack of resources,and lack of political will.These challenges manifest differently in well-resourced municipalities and those with limited resources.The study proposes planning-relevant GIS curricula to improve the level of GIS use in planning practice.
文摘Inserting Groundwater quality variability and sources potentially contributing to aquifer recharge was evaluated in metropolitan Karachi. Selected sampling sites were characterized by large waste dumping sites, industrial zones, and the presence of open streams receiving heavy loads of industrial and domestic wastes. Levels of pH, electrical conductivity (EC), fluoride (F-), chloride (Cl-), bromide (Br-), nitrate-N (NO-3-N), sulfate (SO2-4), sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), and ammonium (NH+4) were determined and compared with the WHO permissible limits. Concentrations of the measured ions were in the order of Cl- > Na+ > SO2-4 > Mg2+ > Ca2+ > NO-3-N > K+ > F- > Br-. EC values were above the WHO guidelines, representing the presence of high ionic concentration in the groundwater. The health risk index (HRI) for indicated that inhabitants of Karachi are at risk of high exposure. Ingestion of high concentrations of NO-3-N in water can cause methemoglobinemia and birth defects. Results of multivariate statistical analysis, principal component analysis (PCA), cluster analysis (CA), and geographic information system (GIS) map analysis revealed that human activities are leading to adverse effects on the existing groundwater quality in Karachi.
文摘Most cities around the world, including Abuja Municipal are being faced with an undesirable increased in air temperature. This is indicated by an increase in non-porous, non-evaporating, highly thermal conductive surfaces such as concrete and asphalt, which has replaced the vegetation biomass resulting to the formation of urban heat island. There is an increasing need for studies on the changing trend of UHI intensity in cities. This research employed geospatial techniques to determine the urban heat island intensity in Abuja Municipal. Temperature characteristics over twenty selected rural and urban locations in Abuja, FCT were derived from the satellite image of 1986, 2001 and 2016 using the “Extract Multi Values to Point” tool in ArcGIS 10.4. These transects pass over various landscapes with different environmental settings, with the aim of understanding the factors shaping the city’s thermal landscape. The intervals of +15 years were deliberately chosen to ensure uniformity between the datasets. The results of this analysis indicate that UHII has been increasing, from 1986-2016, giving credence to the results of the spatial and temporal analysis of the land surface temperature, indicating the development phases had hit full stride. The different periods under study (1986, 2001 and 2016) were also tested using the student “t” test to determine the significant difference in the land surface temperature values to acknowledge the presence of a substantial urban heat island within the study area. The result reveals the calculated “t” values of 2.50, 3.34, 5.57 of 1986, 2001 and 2016 respectively, are higher than the critical value of “t” at 0.05 being 1.73, thus, revealing the temperature differences between the urban and rural stations to be highly significant, indicating the presence of a strong urban heat island. Also, a slide difference in the temperature was observed with the Rubuchi and Karmajiji rural areas having higher temperature readings than their counterparts in the urban areas, Asokoro and Garki, with readings of <span style="white-space:nowrap;">−</span>0.4<span style="white-space:nowrap;">°</span>C and <span style="white-space:nowrap;">−</span>1.3<span style="white-space:nowrap;">°</span>C. Since effectiveness of a surface in reducing daytime urban air temperatures depends strongly on the amount of heating avoided, the study recommends preserving and replicating greenery, light coloured facades as measures to reduce the effects of urban heat island.
