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Published in 2022 at "International Journal of Geographical Information Science"
DOI: 10.1080/13658816.2022.2053980
Abstract: Abstract Spatial clustering has been widely used for spatial data mining and knowledge discovery. An ideal multivariate spatial clustering should consider both spatial contiguity and aspatial attributes. Existing spatial clustering approaches may face challenges for…
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Keywords:
spatial clustering;
method;
spatial contiguity;
multivariate spatial ... See more keywords
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Published in 2021 at "IEEE Transactions on Parallel and Distributed Systems"
DOI: 10.1109/tpds.2021.3071423
Abstract: Modeling and inferring spatial relationships and predicting missing values of environmental data are some of the main tasks of geospatial statisticians. These routine tasks are accomplished using multivariate geospatial models and the cokriging technique. The…
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Keywords:
performance;
multivariate spatial;
multivariate geospatial;
geospatial statistics ... See more keywords
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Published in 2024 at "Sains Malaysiana"
DOI: 10.17576/jsm-2024-5306-18
Abstract: Multivariate spatial functional data consists of multiple functions of time-dependent attributes observed at each spatial point. This study focuses on detecting spatial outliers in spatial functional data. Firstly, we develop a new method called Mahalanobis…
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Keywords:
functional outliers;
multivariate spatial;
functional data;
spatial functional ... See more keywords
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Published in 2024 at "Mathematics"
DOI: 10.3390/math12172746
Abstract: Moran’s I is a spatial autocorrelation measure of univariate spatial data. Therefore, even if p spatial data exist, we can only obtain p values for Moran’s I. In other words, Moran’s I cannot measure the…
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Keywords:
moran multivariate;
spatial data;
spatial autocorrelation;
multivariate spatial ... See more keywords