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Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of Global Positioning System (GPS)–equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ...

This report presents the development and finalization of the 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2022), which was held in Seattle, Washington, USA, November 1--4, 2022.

This paper demonstrates GeoTorchAI, a spatiotemporal deep learning framework. In recent years, many neural network models have been proposed focusing on the applications of raster imagery and spatiotemporal non-imagery datasets. Implementing these models ...

Deep learning frameworks, such as PyTorch and TensorFlow, support the implementation of various state-of-the-art machine learning models such as neural networks, hidden Markov models, and support vector machines. In recent years, many extensions of ...

The conference started as a series of workshops and symposia back in 1993 with the aim of promoting interdisciplinary discussions among researchers, developers, users, and practitioners and fostering research in all aspects of geographic information ...

Identifying various mentions of the same real-world locations is known as spatial entity matching. GEM is an end-to-end Geospatial EM framework that matches polygon geometry entities in addition to point geometry type. Blocking, feature vector creation, ...

With the ubiquity of spatial data, vertexes or edges in graphs can possess spatial location attributes side by side with other non-spatial attributes. For instance, as of June 2018, the Wikidata knowledge graph contains 48,547,142 data items (i.e., ...

Prediction of the next SQL query from the user, given her sequence of queries until the current timestep, during an ongoing interaction session of the user with the database, can help in speculative query processing and increased interactivity. While ...

In the last decade, geospatial data which is extracted from GPS traces and satellites image has become ubiquitous. GeoVisual analytics, abbr. GeoViz, is the science of analytical reasoning assisted by geospatial map interfaces. GeoViz involves two ...

Researchers and practitioners have widely studied road network traffic data in different areas such as urban planning, traffic prediction and spatial-temporal databases. For instance, researchers use such data to evaluate the impact of road ...

The Internet of Things (IoT) has recently received significant attention. An IoT device may possess an array of sensors that for example monitors the air temperature, carbon monoxide level, wifi signals, and sound intensity. IoT data is initially ...

In this paper, we demonstrate Tabula, a middleware that sits between the data system and the geospatial visualization dashboard to increase user interactivity. The proposed system adopts a sampling cube approach that stores prematerialized spatial ...

The aim of the GeoRich workshop is to provide a unique forum for discussing in depth the challenges, opportunities, novel techniques and applications on modeling, managing, searching and mining rich geo-spatial data, in order to fuel scientific research ...

Entity Matching (EM) is a core data cleaning task, aiming to identify different mentions of the same real-world entity. Active learning is one way to address the challenge of scarce labeled data in practice, by dynamically collecting the necessary ...

This tutorial is expected to deliver a comprehensive study and hands-on tutorial of how GeoSpark incorporates Spark to uphold massive-scale spatial data. We also want this tutorial to serve as an introductory course that teaches the audience the basic ...

Road network traffic data has been widely studied by researchers and practitioners in different areas such as urban planning, traffic prediction and spatial-temporal databases. The existing urban traffic simulators suffer from two critical issues (1) ...

This volume contains the proceedings of the 16th International Symposium on Spatial and Temporal Databases (SSTD 2019). Included are the research contributions that were presented at SSTD 2019 in Vienna, Austria. The symposium brought together, for ...

Graphs are widely used to model data in many application domains. Thanks to the wide spread use of GPS-enabled devices, many applications assign spatial attributes to graph vertexes (e.g., geographic knowledge bases, geo-tagged social media). Graph ...

The paper presents the details of designing and developing GeoSpark, which extends the core engine of Apache Spark and SparkSQL to support spatial data types, indexes, and geometrical operations at scale. The paper also gives a detailed analysis of the ...

The paper proposes Riso-Tree, a generic indexing framework for geographic knowledge graphs. Riso-Tree enables fast execution of graph queries that involve spatial predicates (aka. GraSp). The proposed framework augments the classic R-Tree structure with ...