Temporal Cluster Analysis for radar satellite data
Abstract
En
Clustering is a popular technique of data analysis and data mining. Since clustering problems are complex in nature, the larger is the size of the problem, the harder is to find the optimal solution and the longer it takes to reach reasonable results. Clustering techniques are conventionally divided in hierarchical and partitioning. In this paper I present a review of the clustering algorithms for large temporal databases and an application to radar satellite data in which I study different types of ground deformation trend by SAR images of the European Space Agency. The studied region is the area between the cities of Benevento and Avellino.
Clustering is a popular technique of data analysis and data mining. Since clustering problems are complex in nature, the larger is the size of the problem, the harder is to find the optimal solution and the longer it takes to reach reasonable results. Clustering techniques are conventionally divided in hierarchical and partitioning. In this paper I present a review of the clustering algorithms for large temporal databases and an application to radar satellite data in which I study different types of ground deformation trend by SAR images of the European Space Agency. The studied region is the area between the cities of Benevento and Avellino.
DOI Code:
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Keywords:
Temporal Clustering; Similarity; TDM; CLARA; Interferometry; PS-InSAR
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