Global warming is exacerbating weather, and climate extremes events and is projected to
aggravate multi-sectorial risks. A multiplicity of climate hazards will be involved, triggering …

Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay
between space and time. Several available surveys capture STDM advances and report a …

Dynamical systems that contain moving objects generate multi-attribute data, including
static, time-series, and spatiotemporal formats. The diversity of the data formats creates …

Nowadays, the high availability of data gathered from wireless sensor networks and
telecommunication systems has drawn the attention of researchers on the problem of …

This chapter surveys the field of Big Data analysis from a machine learning perspective. In
particular, it contrasts Big Data analysis with data mining, which is based on machine …

Inland recreational fishing, defined as primarily leisure‐driven fishing in freshwaters, is a
popular pastime in the USA. State natural resource agencies endeavor to provide high …

In the past decades, ubiquitous learning (u-learning) has been the focus of attention in
educational research across the world. Majority of u-learning systems have been …

Indexing and query processing is an emerging research field in spatio-temporal data. Most
of the real-time applications such as location based services, fleet management, traffic …

With the wide application of spatiotemporal data, more and more data need to be modeled.
Fuzziness is one of the important characteristics of spatiotemporal data, but most of the …

Many previous studies have shown that open-source technologies help democratize
information and foster collaborations to enable addressing global physical and societal …