Josue Salazar

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Large amounts of remotely sensed data calls for data mining techniques to fully utilize their rich information content. In this paper, we study new means of discovery and sum-marization of knowledge contained in the spatial patterns of remote sensing datasets. Several geospatial feature variables are fused together, and the vector of their values at each(More)
Association analysis provides a natural, data-centric framework for the discovery of patterns of explanatory variables that are linked to a certain outcome. In this paper we demonstrate how such a framework can be applied for political analysis, using an expository example of discovering different spatio-social motifs of support for Barack Obama in the 2008(More)
We propose an association analysis-based strategy for exploration of multi-attribute spatial datasets possessing naturally arising classification. Proposed strategy, ESTATE (Exploring Spatial daTa Association patTErns), inverts such classification by interpreting different classes found in the dataset in terms of sets of discriminative patterns of its(More)
The technique of Hotspot Mapping is widely used in analysing the spatial characteristics of crimes. The spatial distribution of crime is considered to be related with a variety of socio-economic and crime opportunity factors. But existing methods usually focus on the target crime density as input without utilizing these related factors. In this study, we(More)
Crime tends to cluster geographically. This has led to the wide usage of hotspot analysis to identify and visualize crime. Accurately identified crime hotspots can greatly benefit the public by creating accurate threat visualizations, more efficiently allocating police resources, and predicting crime. Yet existing mapping methods usually identify hotspots(More)
Criminal activities are unevenly distributed over space. The concept of hotspots is widely used to analyze the spatial characters of crimes. But existing methods usually identify hotspots based on an arbitrary user-defined threshold with respect to the number of a target crime without considering underlying controlling factors. In this study we introduce a(More)
1.1 Diagram—overall design of our proposed method for auto-generating an empirical model of class variable dependence on explanatory variables. 1.2 Experimental Results of the vegetation-cover dataset. (a) Original boundary between high vegetation cover and not-high vegetation cover. (b) Optimal boundary of high vegetation cover. (c) Optimal boundary vs.(More)
We use an association analysis-based strategy for exploration of multi-attribute spatial datasets possessing naturally arising classification. In this demonstration, we present a prototype system, ESTATE (Exploring Spatial daTa Association patTErns), inverting such classification by interpreting different classes found in the dataset in terms of sets of(More)
We use an association analysis-based strategy for exploration of multi-attribute spatial datasets possessing naturally arising classification. In this demonstration, we present a prototype system, ESTATE (Exploring Spatial daTa Association patTErns), inverting such classification by interpreting different classes found in the dataset in terms of sets of(More)
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