There are several Global Climate Models (GCMs) reported by various countries to the Intergovernmental Panel on Climate Change (IPCC). Due to the varied nature of the GCM assumptions, the future projections of the GCMs show high variability which makes it difficult to come up with confident projections into the future. Climate scientists combine these multiple GCMs to minimize the variability an...

Spatial joins are one of the most important operations for combining spatial objects of several relations. In this paper, spatial join processing is studied in detail for extended spatial objects in two-dimensional data space. We present an approach for spatial join processing that is based on three steps. First, a spatial join is performed on the minimum bounding rectangles of the objects retu...

The spatial join combines spatial objects from a Cartesian product that satisfy certain geometric attributes. Unfortunately, to validate the operation the actual objects must be compared against each other. The authors discussed a new process for reducing the number of items that have to be retrieved from disk and compared through filtering and approximation. The three step pipeline started by ...

Estimation and forecasting of dynamic state are fundamental to the design of autonomous systems such as intelligent robots. State-ofthe-art algorithms, such as the particle filter, face computational limitations when needing to maintain beliefs over a hypothesis space that is made large by the dynamic nature of the environment. We propose an algorithm that utilises a hierarchy of such filters, ...

Selectivity estimation of queries not only provides useful information to the query processing optimization but also may give users a preview of processing results. In this paper, we investigate the problem of selectivity estimation in the context of a spatial dataset. Specifically, we focus on the calculation of four relations, contains, contained, overlap and disjoint, between data objects an...

The number of multi-sourced heterogeneous spatial datasets continues to grow and the fragmentation of organizational arrangements has caused much technical and non-technical heterogeneity. Spatial Data Infrastructures aim to facilitate spatial data use and sharing, and can be an effective platform to aid in data integration. This paper discusses the technical and non-technical heterogeneities o...

Smart antennas can improve spatial reuse in a wireless network through interference suppression. However, interference suppression requires support from clients in the form of channel estimation, which existing clients do not support. In this work, we explore practical solutions to obtain spatial reuse with smart antennas without requiring hardware changes to clients. To this end, we design a n...

In this article, we develop and investigate a new classifier based on features extracted using spatial depth. Our construction is based on fitting a generalized additive model to posterior probabilities of different competing classes. To cope with possible multi-modal as well as non-elliptic nature of the population distribution, we also develop a localized version of spatial depth and use that...

This paper proposes a multi-criteria based approach for the analysis of building layouts, from space quality and cost related perspectives. A computational prototype is developed to analyse a building layout from various accessibility related measures in order to evaluate the quality of the building special layout. A case study is used to demonstrate the assessment of a building layout based on...

Heterogeneous geographic databases contain multiple views of the same geographic objects at different levels of spatial resolution which must be consistent with each other. This paper develops a formal method of assessing consistency of topological relations in R at a high level of abstraction, over complexly structured spatial objects that form networks. Networks are a frequently used data typ...