Question: Previous interpretations of the variance plot of paired quadrat variance method (PQV) have been incomplete. The objective of this study was to clarify the interpretation of PQV, and to shed additional light on how different quadrat variance methods can be used, in concert, to measure scale in transect data. Methods: We used artificial and real data to examine how the PQV method elucid...

Dynamic scenes with many different objects and interrelations changing over time demand complex representations. The identification of frequent patterns and prediction rules in such scenes would be very valuable as associations in the data could be discovered or a system’s performance could even be improved by utilizing the new information in the behavior decision process. In this work, a novel...

* Department of Biology, Duke University, Phytotron Building, Science Drive, Box 90340, Durham, NC 27708-0340, USA, ‡ Área de Biodiversidad y Conservación, ESCET, Universidad Rey Juan Carlos, 28933 Móstoles, § Departamento de Agroquímica y Medio Ambiente, Universidad Miguel Hernández, 03202 Elche, and ¶ Departamento de Silvopascicultura, ETSI Montes, Universidad Politécnica de Madrid, 28040 Mad...

Spatiotemporal helixes constitute a novel method we developed for modeling changes in an object over time. Changes in both an object’s trajectory and its outline can be represented with these helixes. In addition, spatiotemporal helixes can be compared to determine whether multiple objects have undergone similar changes. In this paper, we present a method by which these helixes may be compared,...

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This paper analyzes the temporal pattern of prices for single-family housing. We estimate models of house price dynamics using a repeat sales framework, and we use the results to test for a random walk in asset prices. For eight large samples of housing transactions, representing essentially all house sales in Sweden during a 12-year period, we reject the hypothesis that house prices follow a r...

This article investigates the role of spatial pattern in residential outdoor water use and implications for the efficacy of non-price restrictions. Drawing on a spatially explicit dataset, the analysis characterizes latent neighborhood effects in households’ outdoor water use and how these effects vary during water restrictions. Results illustrate that spatial patterns in water use vary across ...

The management of spatial, temporal, and spatiotemporal data is becoming increasingly important in a wide range of applications. This ongoing Ph.D. project focuses on applications where spatial or temporal aspects of objects are continuously changing and there is a need for indexing techniques that ”track” the changing data, even in-between explicit updates. In spatiotemporal applications, ther...

This paper presents a Bayesian hierarchical spatiotemporal method of interpolation, termed as Markov Cube Kriging (MCK). The classical Kriging methods become computationally prohibitive, especially for large datasets due to the O(n3) matrix decomposition. MCK offers novel and computationally efficient solutions to address spatiotemporal misalignment, mismatch in the spatiotemporal scales and mi...

With the fast development of positioning technology, spatiotemporal data has become widely available nowadays. Mining patterns from spatiotemporal data has many important applications in human mobility understanding, smart transportation, urban planning and ecological studies. In this chapter, we provide an overview of spatiotemporal data mining methods. We classify the patterns into three cate...