Clustering is a widespread method to explore patterns in large spatio-temporal datasets. Most clustering studies are, however, performed either from a spatial or from a temporal point of view. This is sub-optimal because patterns explored from a spatial perspective cannot describe the time-varying behavior present in the dataset and vice versa. Here we illustrate a co-clustering-based analysis ...

The spatial distribution of very large trees in primary Amazon forest is extracted from a digital model of interferometric forest height by an approach of local maximum filtering. The spatial point patterns of very large trees are modeled by a series of Markov point process models. Spatial distribution is regular, and interaction decreases with distance; very large trees are shown to exert repu...

Discretization of a geographical region is quite common in spatial analysis. There have been few studies into the impact of different geographical scales on the outcome of spatial models for different spatial patterns. This study aims to investigate the impact of spatial scales and spatial smoothing on the outcomes of modelling spatial point-based data. Given a spatial point-based dataset (such...

Recently, a very attractive logistic regression inference method for exponential family Gibbs spatial point processes was introduced. We combined it with the technique of quadratic tangential variational approximation and derived a new Bayesian technique for analysing spatial point patterns. The technique is described in detail, and demonstrated on numerical examples.

Quantifying spatial patterns of bird nests and nest fate provides insights into processes influencing a species' distribution. At Cape Churchill, Manitoba, Canada, recent declines in breeding Eastern Prairie Population Canada geese (Branta canadensis interior) has coincided with increasing populations of nesting lesser snow geese (Chen caerulescens caerulescens) and Ross's geese (Chen rossii). ...

The spatial distribution of very large trees in primary Amazon forest is extracted from a digital model of interferometric forest height by an approach of local maximum filtering. The spatial point patterns of very large trees are modeled by a series of Markov point process models. Spatial distribution is regular, and interaction decreases with distance; very large trees are shown to exert repu...

in recent decades, as a result of population growth, industrial developments, scarcity of sources, etc. more attention has been paid to spatial planning. spatial planning needs the consideration of different goals, scenarios, criterions and constraints, which leads us to the usage of spatial multi-criteria decision analysis (mcda) methods. the mail goal of this research is to develop a novel mo...