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
The quality, quantity, and consistency of the knowledge used in GO-playing programs often determine their strengths, and automatic acquisition of large amounts of high-quality and consistent GO knowledge is crucial fo...The quality, quantity, and consistency of the knowledge used in GO-playing programs often determine their strengths, and automatic acquisition of large amounts of high-quality and consistent GO knowledge is crucial for successful GO playing. In a previous article of this subject, we have presented an algorithm for efficient and automatic acquisition of spatial patterns of GO as well as their frequency of occurrence from game records. In this article, we present two algorithms, one for efficient and automatic acquisition of pairs of spatial patterns that appear jointly in a local context, and the other for deter- mining whether the joint pattern appearances are of certain significance statistically and not just a coincidence. Results of the two algorithms include 1 779 966 pairs of spatial patterns acquired automatically from 16 067 game records of professsional GO players, of which about 99.8% are qualified as pattern collocations with a statistical confidence of 99.5% or higher.展开更多
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The quality, quantity, and consistency of the knowledge used in GO-playing programs often determine their strengths, and automatic acquisition of large amounts of high-quality and consistent GO knowledge is crucial for successful GO playing. In a previous article of this subject, we have presented an algorithm for efficient and automatic acquisition of spatial patterns of GO as well as their frequency of occurrence from game records. In this article, we present two algorithms, one for efficient and automatic acquisition of pairs of spatial patterns that appear jointly in a local context, and the other for deter- mining whether the joint pattern appearances are of certain significance statistically and not just a coincidence. Results of the two algorithms include 1 779 966 pairs of spatial patterns acquired automatically from 16 067 game records of professsional GO players, of which about 99.8% are qualified as pattern collocations with a statistical confidence of 99.5% or higher.
