25 Results Found

Task-oriented scene data in big data and cloud environments of a smart city that must be time-critically processed are dynamic and associated with increasing complexities and heterogeneities. Existing hybrid tree-based external indexing methods are i...

Temporal reasoning is an important part of the field of time geography and spatio-temporal data science. Recent advances in qualitative temporal reasoning have developed a set of 74 relations that apply between discretized time intervals of at least...

In massive Twitter datasets, tweets deriving from different domains, e.g., civil unrest, can be extracted to constitute spatio-temporal Twitter events for spatio-temporal distribution pattern detection. Existing algorithms generally employ scan stati...

Spatio-temporal indexing is a key technique in spatio-temporal data storage and management. Indexing methods based on spatial filling curves are popular in research on the spatio-temporal indexing of vector data in the Not Relational (NoSQL) database...

There is voluminous literature concerning the scope of topological relations that span various embedding spaces from ${\mathbb{R}}^1$ to ${\mathbb{R}}^2$, ${\mathbb{Z}}^2$ , ${\mathbb{S}}^1$ and ${\mathbb{S}}^2$ , and ${\mathbb{T}}^2$. In the case of the ${*}^1$ spaces, those relations have been considered as conceptualizations of both s...

In recent years, geographic knowledge graphs (GeoKGs) have shown great promise in representing spatio-temporal and event-driven knowledge. However, existing knowledge graph embedding approaches mainly focus on structural patterns and often overlook t...

In addition to traditional viewing media, metadata that record the physical space from multiple perspectives will become extremely important in realizing interactive applications such as Virtual Reality (VR) and Augmented Reality (AR). This paper pro...

The widespread availability of tools to collect and share spatial data enables us to produce a large amount of geographic information on a daily basis. This enormous production of spatial data requires scalable data management systems. Geospatial arc...

Mobile and wearable devices are capable of quantifying user behaviors based on their contextual sensor data. However, few indexing and annotation mechanisms are available, due to difficulties inherent in raw multivariate data types and the relative s...

Analyzing events in dynamic environments poses a fundamental challenge in the development of intelligent agents and robots capable of interacting with humans. Current approaches predominantly rely on visual–text models; however, these methods o...

Every day large quantities of spatio-temporal data are captured, whether by Web-based companies for social data mining or by other industries for a variety of applications ranging from disaster relief to marine data analysis. Making sense of all this...

Represention and modeling the dynamic landslide scenes is essential for gaining a comprehensive understanding and managing them effectively. Existing models, which focus on a single scale make it difficult to fully express the complex, multi-scale sp...

Recent advances in sensor technologies, in particular video-based human detection, object tracking and pose estimation, have opened new possibilities for the automatic or semi-automatic per-frame annotation of sport videos. In the case of racket spor...

Scientists in the marine domain process satellite images in order to extract information that can be used for monitoring, understanding, and forecasting of marine phenomena, such as turbidity, algal blooms and oil spills. The growing need for effecti...

With the widespread deployment of ground, air and space sensor sources (internet of things or IoT, social networks, sensor networks), the integrated applications of real-time geospatial data from ubiquitous sensors, especially in public security and...

Retinal neurogenesis is driven by concerted actions of transcription factors, some of which are expressed in a continuum and across several cell subtypes throughout development. While seemingly redundant, many factors diversify their regulatory outco...

This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standa...

Wildfire monitoring in tropical regions requires robust frameworks capable of transforming heterogeneous satellite detections into consistent, event-level information suitable for decision support. This study presents the DescrEVE Fogo (Descriç...

In order to perform topological queries on geographic data, it is necessary to first develop a topological access method (TOAM). Using the fact that any (incidence or other binary) relation produces a topology which includes the common usage of topol...

Due to the absence of a comprehensive knowledge system for modeling ocean circulation, there is ambiguity and diversity in the semantic expression of ocean circulation. This makes it difficult to organize and share relevant spatiotemporal data effect...

Video temporal grounding (VTG) aims to localize a semantically relevant temporal segment within an untrimmed video based on a natural language query. The task continues to face challenges arising from cross-modal semantic misalignment, which is large...

Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC) over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in e...

The European climate is changing displaying profound impacts on agriculture, thus strongly reaching the scientific community’s attention. In this review, the compilation of selected scientific research on the agroclimatic conditions’ chan...

The increasing number of unmanned aerial vehicles (UAVs) has led to challenges related to solving the collision problem to ensure air traffic safety. The traditional approaches employed for collision detection suffer from two main drawbacks: first, t...

In this paper, we propose sketch-based video object segmentation (SKVOS), a novel task that segments objects consistently across video frames using human-drawn sketches as queries. Traditional reference-based methods, such as photo masks and language...