Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
Detecting graph-based spatial outliers: algorithms and applications (a summary of results)
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Spatio-Temporal Data Mining for Typhoon Image Collection
Journal of Intelligent Information Systems
OPTICS-OF: Identifying Local Outliers
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Time-Expanded Graphs for Flow-Dependent Transit Times
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
A Unified Approach to Detecting Spatial Outliers
Geoinformatica
Algorithms for Spatial Outlier Detection
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Detecting Spatial Outliers with Multiple Attributes
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
Neighborhood based detection of anomalies in high dimensional spatio-temporal sensor datasets
Proceedings of the 2004 ACM symposium on Applied computing
Indexing spatio-temporal trajectories with Chebyshev polynomials
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
On Change Diagnosis in Evolving Data Streams
IEEE Transactions on Knowledge and Data Engineering
A generalized framework for mining spatio-temporal patterns in scientific data
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Finding Spatio-Temporal Patterns in Climate Data Using Clustering
CW '05 Proceedings of the 2005 International Conference on Cyberworlds
Spatial scan statistics: approximations and performance study
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
MONIC: modeling and monitoring cluster transitions
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Mixed-Drove Spatio-Temporal Co-occurence Pattern Mining: A Summary of Results
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
On Trajectory Representation for Scientific Features
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Detecting and tracking regional outliers in meteorological data
Information Sciences: an International Journal
Discovering and Summarising Regions of Correlated Spatio-Temporal Change in Evolving Graphs
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Spatial Outlier Detection: A Graph-Based Approach
ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 01
A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets
IEEE Transactions on Knowledge and Data Engineering
A clustering-based approach for discovering interesting places in trajectories
Proceedings of the 2008 ACM symposium on Applied computing
Discovering correlated spatio-temporal changes in evolving graphs
Knowledge and Information Systems
Random Walks to Identify Anomalous Free-Form Spatial Scan Windows
IEEE Transactions on Knowledge and Data Engineering
Depth-first search and linear grajh algorithms
SWAT '71 Proceedings of the 12th Annual Symposium on Switching and Automata Theory (swat 1971)
Detecting and Tracking Spatio-temporal Clusters with Adaptive History Filtering
ICDMW '08 Proceedings of the 2008 IEEE International Conference on Data Mining Workshops
Spatio-Temporal Sensor Graphs (STSG): A data model for the discovery of spatio-temporal patterns
Intelligent Data Analysis - Knowledge Discovery from Data Streams
WhereNext: a location predictor on trajectory pattern mining
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Anomaly detection and spatio-temporal analysis of global climate system
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data
A Novel Spatio-temporal Clustering Approach by Process Similarity
FSKD '09 Proceedings of the 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 05
Spatial neighborhood based anomaly detection in sensor datasets
Data Mining and Knowledge Discovery
Meteorology and hydrology in Yosemite national park: a sensor network application
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Time-Aggregated graphs for modeling spatio-temporal networks
CoMoGIS'06 Proceedings of the 2006 international conference on Advances in Conceptual Modeling: theory and practice
Characterizing sensor datasets with multi-granular spatio-temporal intervals
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Mining outliers in spatial networks
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
Tracing Evolving Subspace Clusters in Temporal Climate Data
Data Mining and Knowledge Discovery
Bipartite graphs for monitoring clusters transitions
IDA'10 Proceedings of the 9th international conference on Advances in Intelligent Data Analysis
Spatio-temporal outlier detection in precipitation data
Sensor-KDD'08 Proceedings of the Second international conference on Knowledge Discovery from Sensor Data
Spatiotemporal neighborhood discovery for sensor data
Sensor-KDD'08 Proceedings of the Second international conference on Knowledge Discovery from Sensor Data
Exploring multivariate spatio-temporal change in climate data using image analysis techniques
Proceedings of the 3rd International Conference on Computing for Geospatial Research and Applications
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When mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. These dynamic regions can be characterized by a location or set of locations that exhibit different behaviors from their neighbors and the time periods where these differences are most pronounced. Examples include locally intense areas of precipitation, anomalous sea surface temperature (SST) readings, and locally high levels of water pollution, to name a few. The focus of this paper is to find and analyze the pattern of moving dynamic spatio-temporal regions in large sensor datasets. The approach presented in this paper uses a measure of local spatial autocorrelation over time to determine how pronounced the difference in measurements taken at a spatial location is with those taken at neighboring locations. Dynamic regions are analyzed both globally, in the form of spatial locations and time periods that have the largest difference in local spatial autocorrelation, and locally, in the form of dynamic spatial locations for a particular time period or dynamic time periods for a particular spatial node. Then, moving dynamic regions are identified by determining the spatio-temporal connectivity, extent, and trajectory for groups of locally dynamic spatial locations whose position has shifted from one time period to the next. The efficacy of the approach is demonstrated on two real-world spatio-temporal datasets (a) NEXRAD precipitation and (b) SST. Promising results were found in discovering highly dynamic regions in these datasets depicting several real environmental phenomenon which are validated as actual events of interest.