Voronoi diagrams—a survey of a fundamental geometric data structure
ACM Computing Surveys (CSUR)
Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
Primitives for the manipulation of general subdivisions and the computation of Voronoi
ACM Transactions on Graphics (TOG)
Functional specification and prototyping with oriented combinatorial maps
Computational Geometry: Theory and Applications
Moving Objects Databases: Issues and Solutions
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Delete and insert operations in Voronoi/Delaunay methods and applications
Computers & Geosciences
Integrated coverage and connectivity configuration in wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Report from the first workshop on geo sensor networks
ACM SIGMOD Record
Supporting spatial aggregation in sensor network databases
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Beyond average: toward sophisticated sensing with queries
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Detecting Topological Change Using a Wireless Sensor Network
GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
Effect of Neighborhood on In-Network Processing in Sensor Networks
GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
Decentralized Movement Pattern Detection amongst Mobile Geosensor Nodes
GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
Queries for historic events in geosensor networks
Journal of Location Based Services
Building Efficient Aggregation Trees for Sensor Network Event-Monitoring Queries
GSN '09 Proceedings of the 3rd International Conference on GeoSensor Networks
Decentralized area computation for spatial regions
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Decentralized time geography for ad-hoc collaborative planning
COSIT'09 Proceedings of the 9th international conference on Spatial information theory
A boundary approximation algorithm for distributed sensor networks
International Journal of Sensor Networks
Modeling and prediction of moving region trajectories
Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming
An object-field perspective data model for moving geographic phenomena
DASFAA'10 Proceedings of the 15th international conference on Database systems for advanced applications
Efficient data collection and event boundary detection in wireless sensor networks using tiny models
GIScience'10 Proceedings of the 6th international conference on Geographic information science
Detecting change in snapshot sequences
GIScience'10 Proceedings of the 6th international conference on Geographic information science
Qualitative change to 3-valued regions
GIScience'10 Proceedings of the 6th international conference on Geographic information science
Collection trees for event-monitoring queries
Information Systems
Efficient tracking of 2D objects with spatiotemporal properties in wireless sensor networks
Distributed and Parallel Databases
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Information about dynamic spatial fields, such as temperature, windspeed, or the concentration of gas pollutant in the air, is important for many environmental applications. At the same time, the development of geosensor networks (wirelessly communicating, sensor-enabled, small computing devices distributed throughout a geographic environment) present new opportunities for monitoring dynamic spatial fields in much greater detail than ever before. This paper develops a new model for querying information about dynamic spatial fields using geosensor networks. In order to manage the inherent complexity of dynamic geographic phenomena, our approach is to focus on the qualitative representation of spatial entities, like regions, boundaries, and holes, and of events, like splitting, merging, appearance, and disappearance. Based on combinatorial maps, we present a qualitative model as the underlying data management paradigm for geosensor networks. This model is capable of tracking salient changes in the network in an energy-efficient way. Further, our model enables reconfiguration of the geosensor network in response to changes in the environment. We present an algorithm capable of adapting sensor network granularity according to dynamic monitoring requirements. Regions of high variability can trigger increases in the geosensor network granularity, leading to more detailed information about the dynamic field. Conversely, regions of stability can trigger a coarsening of the sensor network, leading to efficiency increases in particular with respect to power consumption and longevity of the sensor nodes. Querying of this responsive geosensor network is also considered, and the paper concludes with a review of future research directions.