Although we live in an era of unprecedented quantities and access to data,deriving actionable information from raw data is a hard problem.Earth observation systems(EOS)have experienced rapid growth and uptake in recen...Although we live in an era of unprecedented quantities and access to data,deriving actionable information from raw data is a hard problem.Earth observation systems(EOS)have experienced rapid growth and uptake in recent decades,and the rate at which we obtain remotely sensed images is increasing.While significant effort and attention has been devoted to designing systems that deliver analytics ready imagery faster,less attention has been devoted to developing analytical frameworks that enable EOS to be seamlessly integrated with other data for quantitative analysis.Discrete global grid systems(DGGS)have been proposed as one potential solution that addresses the challenge of geospatial data integration and interoperability.Here,we propose the systematic extension of EASE-Grid in order to provide DGGS-like characteristics for EOS data sets.We describe the extensions as well as present implementation as an application programming interface(API),which forms part of the University of Minnesota’s GEMS(Genetic x Environment x Management x Socioeconomic)Informatics Center’s API portfolio.展开更多
全球离散格网(Discrete Global Grid,DGG)模型是数字地球及空间信息格网的基础,不同的建模方法不但影响空间数据的存储和管理效率,而且影响全球GIS的操作功能。该文介绍了DGG的评价标准,将DGG的建模方法归纳为3种类型:经纬度格网模型、...全球离散格网(Discrete Global Grid,DGG)模型是数字地球及空间信息格网的基础,不同的建模方法不但影响空间数据的存储和管理效率,而且影响全球GIS的操作功能。该文介绍了DGG的评价标准,将DGG的建模方法归纳为3种类型:经纬度格网模型、自适应格网模型和正多面体格网模型,重点分析了不同类型球面离散格网模型的几何结构、单元特征和应用模式。最后,提出了DGG在Global GIS中亟待解决的基本问题,包括编码、精度、应用、误差、整合和定位问题。展开更多
In this paper, we provide analytical results on average Symbol Error Probability(SEP) of a Free Space Optics(FSO) link employing M-ary Pulse Position Modulation(PPM), subjected to turbulent atmosphere modeled with Dou...In this paper, we provide analytical results on average Symbol Error Probability(SEP) of a Free Space Optics(FSO) link employing M-ary Pulse Position Modulation(PPM), subjected to turbulent atmosphere modeled with Double Generalized Gamma(DGG) distribution. FSO link is generally impaired by turbulent atmosphere and pointing errors. As far as we know, results are presented in previous works by considering the atmosphere turbulence modeled with a Gamma-Gamma distribution. In our work, we also give asymptotic results on average SEP in order to approximate its evolution at high Signal-to-Noise-Ratio(SNR). Numerical results showed that FSO link performance is enhanced when PPM-modulation index is increased, for both strong and moderate turbulence regimes, and for both strong and weak pointing error jitter. Monte-Carlo simulations were presented to corroborate our analytical expressions.展开更多
Increasing data resources are available for documenting and detecting changes in environmental,ecological,and socioeconomic processes.Currently,data are distributed across a wide variety of sources(e.g.data silos)and ...Increasing data resources are available for documenting and detecting changes in environmental,ecological,and socioeconomic processes.Currently,data are distributed across a wide variety of sources(e.g.data silos)and published in a variety of formats,scales,and semantic representations.A key issue,therefore,in building systems that can realize a vision of earth system monitoring remains data integration.Discrete global grid systems(DGGSs)have emerged as a key technology that can provide a common multi-resolution spatial fabric in support of Digital Earth monitoring.However,DGGSs remain in their infancy with many technical,conceptual,and operational challenges.With renewed interest in DGGS brought on by a recently proposed standard,the demands of big data,and growing needs for monitoring environmental changes across a variety of scales,we seek to highlight current challenges that we see as central to moving the field(s)and technologies of DGGS forward.For each of the identified challenges,we illustrate the issue and provide a potential solution using a reference DGGS implementation.Through articulation of these challenges,we hope to identify a clear research agenda,expand the DGGS research footprint,and provide some ideas for moving forward towards a scaleable Digital Earth vision.Addressing such challenges helps the GIScience research community to achieve the real benefits of DGGS and provides DGGS an opportunity to play a role in the next generation of GIS.展开更多
A Discrete Global Grid System(DGGS)is a type of spatial reference system that tessellates the globe into many individual,evenly spaced,and well-aligned cells to encode location and,thus,can serve as a basis for data c...A Discrete Global Grid System(DGGS)is a type of spatial reference system that tessellates the globe into many individual,evenly spaced,and well-aligned cells to encode location and,thus,can serve as a basis for data cube construction.This facilitates integration and aggregation of multi-resolution data from various sources to rapidly calculate spatial statistics.We calculated normalized area and compactness for cell geometries from 5 open-source DGGS implementations-Uber H3,Google S2,RiskAware OpenEAGGR,rHEALPix by Landcare Research New Zealand,and DGGRID by Southern Oregon University-to evaluate their suitability for a global-level statistical data cube.We conclude that the rHEALPix and OpenEAGGR and DGGRID ISEA-based DGGS definitions are most suitable for global statistics because they have the strongest guarantee of equal area preservation-where each cell covers almost exactly the same area on the globe.Uber H3 has the smallest shape distortions,but Uber H3 and Google S2 have the largest variations in cell area.However,they provide more mature software library functionalities.DGGRID provides excellent functionality to construct grids with desired geometric properties but as the only implementation does not provide functions for traversal and navigation within a grid after its construction.展开更多
文摘Although we live in an era of unprecedented quantities and access to data,deriving actionable information from raw data is a hard problem.Earth observation systems(EOS)have experienced rapid growth and uptake in recent decades,and the rate at which we obtain remotely sensed images is increasing.While significant effort and attention has been devoted to designing systems that deliver analytics ready imagery faster,less attention has been devoted to developing analytical frameworks that enable EOS to be seamlessly integrated with other data for quantitative analysis.Discrete global grid systems(DGGS)have been proposed as one potential solution that addresses the challenge of geospatial data integration and interoperability.Here,we propose the systematic extension of EASE-Grid in order to provide DGGS-like characteristics for EOS data sets.We describe the extensions as well as present implementation as an application programming interface(API),which forms part of the University of Minnesota’s GEMS(Genetic x Environment x Management x Socioeconomic)Informatics Center’s API portfolio.
文摘全球离散格网(Discrete Global Grid,DGG)模型是数字地球及空间信息格网的基础,不同的建模方法不但影响空间数据的存储和管理效率,而且影响全球GIS的操作功能。该文介绍了DGG的评价标准,将DGG的建模方法归纳为3种类型:经纬度格网模型、自适应格网模型和正多面体格网模型,重点分析了不同类型球面离散格网模型的几何结构、单元特征和应用模式。最后,提出了DGG在Global GIS中亟待解决的基本问题,包括编码、精度、应用、误差、整合和定位问题。
文摘In this paper, we provide analytical results on average Symbol Error Probability(SEP) of a Free Space Optics(FSO) link employing M-ary Pulse Position Modulation(PPM), subjected to turbulent atmosphere modeled with Double Generalized Gamma(DGG) distribution. FSO link is generally impaired by turbulent atmosphere and pointing errors. As far as we know, results are presented in previous works by considering the atmosphere turbulence modeled with a Gamma-Gamma distribution. In our work, we also give asymptotic results on average SEP in order to approximate its evolution at high Signal-to-Noise-Ratio(SNR). Numerical results showed that FSO link performance is enhanced when PPM-modulation index is increased, for both strong and moderate turbulence regimes, and for both strong and weak pointing error jitter. Monte-Carlo simulations were presented to corroborate our analytical expressions.
文摘Increasing data resources are available for documenting and detecting changes in environmental,ecological,and socioeconomic processes.Currently,data are distributed across a wide variety of sources(e.g.data silos)and published in a variety of formats,scales,and semantic representations.A key issue,therefore,in building systems that can realize a vision of earth system monitoring remains data integration.Discrete global grid systems(DGGSs)have emerged as a key technology that can provide a common multi-resolution spatial fabric in support of Digital Earth monitoring.However,DGGSs remain in their infancy with many technical,conceptual,and operational challenges.With renewed interest in DGGS brought on by a recently proposed standard,the demands of big data,and growing needs for monitoring environmental changes across a variety of scales,we seek to highlight current challenges that we see as central to moving the field(s)and technologies of DGGS forward.For each of the identified challenges,we illustrate the issue and provide a potential solution using a reference DGGS implementation.Through articulation of these challenges,we hope to identify a clear research agenda,expand the DGGS research footprint,and provide some ideas for moving forward towards a scaleable Digital Earth vision.Addressing such challenges helps the GIScience research community to achieve the real benefits of DGGS and provides DGGS an opportunity to play a role in the next generation of GIS.
基金This research has been supported by the Marie Skłodowska-Curie Actions individual fellowship under the Horizon 2020 Programme grant agreement number 795625,grant number MOBERC34 of the Estonian Research Council(ETAG),and the NUTIKAS programme of the Archimedes foundation.The authors are also thankful for technical support from the High Performance Computing Center of the University of Tartu.
文摘A Discrete Global Grid System(DGGS)is a type of spatial reference system that tessellates the globe into many individual,evenly spaced,and well-aligned cells to encode location and,thus,can serve as a basis for data cube construction.This facilitates integration and aggregation of multi-resolution data from various sources to rapidly calculate spatial statistics.We calculated normalized area and compactness for cell geometries from 5 open-source DGGS implementations-Uber H3,Google S2,RiskAware OpenEAGGR,rHEALPix by Landcare Research New Zealand,and DGGRID by Southern Oregon University-to evaluate their suitability for a global-level statistical data cube.We conclude that the rHEALPix and OpenEAGGR and DGGRID ISEA-based DGGS definitions are most suitable for global statistics because they have the strongest guarantee of equal area preservation-where each cell covers almost exactly the same area on the globe.Uber H3 has the smallest shape distortions,but Uber H3 and Google S2 have the largest variations in cell area.However,they provide more mature software library functionalities.DGGRID provides excellent functionality to construct grids with desired geometric properties but as the only implementation does not provide functions for traversal and navigation within a grid after its construction.
