A Scale-Space Information Flux Approach to Natural Irregular Patterns: Methods and Applications

Abstract

The paper addresses problems related to information management when a multiscale approach is applied to environmental patterns, whether in space or in time. To support the decision-making process concerning the information to be handled on each scale, it introduces the concepts of spatial and temporal informational backbone, and defines the scale space information flux as a quantity that reflects the resolution dependence of the size of the informational backbone. Establishing the scale space information flux helps in the identification of self-affinity properties and the quantitative, scale-range-sensitive pattern evaluation: the information flux is constant on the scale ranges of self-affinity. Pattern change can thereby reliably be recognized and characterized. The introduced procedures support storage-saving data selection and provide a measure of data storage requirements as a function of scale, flexibly adapting the calculation algorithm to the scale ranges of interest to the user. The paper also specifies rules that can be used by geographic information management software for a fast assessment of changes in map connectivity as a function of changes in scale.Practical application examples include synthetic data (Levy flight, Brownian walk, cellular automata output) and real-world patterns (desiccation fracture sets, atmospheric temperature time series). The presented concepts and methods can be applied in environmental science, e.g. to spatial and temporal patterns of pollution, natural resources (spatial distribution of minerals, drainage basins, forests), natural hazards (airborne gamma ray spectrometry maps, earthquake patterns), etc., as well as in other disciplines, such as material science and medical imaging.

A quality-aware spatial data warehouse for querying hydroecological data

“…Due to the cost, time and human input required for the sampling campaigns, these imperfect collected data are the only available data. These are general problems for environmental data integrating spatial and temporal aspects from several sources with a different spatiotemporal accuracy (Suteanul, 2010).…”

A Discretization-Hierarchization Approach to Information Management -- Implications for Digital Earth

“…Since a key feature of information is related to novelty and transformation, one can distinguish "information flux" or "i-flux" as an aspect of information defined as the specification of processes, or "change" (Suteanu 2010b). "Change" may refer to different moments in time, different portions of space, or even different scales (Suteanu 2010a). In this context, a transition between similar configurations involves a lower information flux density than one involving states that are very different from each other.…”