Autonomous cars are expected to dramatically redefine the future of transportation. When fully realized, this technology promises to unlock a myriad societal, environmental, and economic benefits. From a technical standpoint, autonomous cars pose ...

Information, not just data, is key to today's global challenges. To solve these challenges requires not only advancing geospatial and big data analytics but requires new analysis and decision-making environments that enable reliable decisions from ...

Congested traffic wastes billions of liters of fuel and is a significant contributor to Green House Gas (GHG) emissions. Although convenient, ride sharing services such as Uber and Lyft are becoming a significant contributor to these emissions not only ...

We present a weighted sampling strategy for distributing a system of taxi agents on a road network. We consider a setting, in which each agent operates independently, following a prescribed strategy based on historical data. Furthermore, customer ...

Three-dimensional models of buildings have a variety of applications, e.g., in urban planning, for making decision where to locate power lines, solar panels, cellular antennas, etc. Often, 3D models are created from a LiDAR point cloud, however, this ...

The increasingly massive volumes of vehicle trajectory data that are becoming available hold the potential to enable more accurate vehicle travel-time estimation than hitherto possible. To enable such uses, we present a multi-threaded, in-memory ...

Standard spatial cluster detection methods used in public health surveillance assign each disease case to a single location (typically, the patient's home address), aggregate locations to small areas, and monitor the number of cases in each area over ...

Spatio-temporal data on the evolution of real-world phenomena are normally acquired as snapshots in discrete time. The continuous evolution of a phenomenon between observations can be approximated using interpolation methods capable of generating ...

Libraries are digitizing their collections of maps from all eras, generating increasingly large online collections of historical cartographic resources. Aligning such maps to a modern geographic coordinate system greatly increases their utility. This ...

One of the greatest challenges in automated driving is the ability to acquire, access and query the data pertaining to high resolution 3D objects from multiple heterogeneous sources. Specifically, the information extraction needs to be done by fusing ...

Automatic Extraction of road network from satellite images is a goal that can benefit and even enable new technologies. Methods that combine machine learning (ML) and computer vision have been proposed in recent years which make the task semi-automatic ...

Rich human mobility datasets are fundamental for evaluating algorithms pertaining to geographic information systems. Unfortunately, existing mobility datasets--that are available to the research community--are restricted to location data captured ...

The amount of available geospatial data grows at an ever faster pace. This leads to a constantly increasing demand for processing power and storage in order to provide data analysis in a timely manner. At the same time, a lot of geospatial processing is ...

In this paper, we present the insights drawn from a comprehensive survey of human-mobility modeling research based on 1680 articles that can serve as a roadmap for research and practice in this area. Mobility modeling research has accelerated the ...

GPS-based services (e.g. Google Maps) are very popular in our daily life, while there are still many GPS-denied environments (e.g. indoor and underground scenarios) in which they cannot be used. In these situations, localization and navigation are still ...

Representation learning is a technique that is used to capture the underlying latent features of complex data. Representation learning on networks has been widely implemented for learning network structure and embedding it in a low dimensional vector ...

Given a transportation network with node and edge capacity constraints, initial node occupancy, destination locations, and the conflict resolution parameter k, the Conflict-Free Evacuation Route Planner (CF-ERP) problem finds evacuation routes that can ...

The interactive exploration of data requires data structures that can be repeatedly queried to obtain simple visualizations of parts of the data. We consider the scenario that the data is a set of points each associated with a time stamp and that the ...

The prediction of flight delays plays a significantly important role for airlines and travellers because flight delays cause not only tremendous economic loss but also potential security risks. In this work, we aim to integrate multiple data sources to ...

The unprecedented rise of social media platforms, combined with location-aware technologies, has led to continuously producing a significant amount of geo-social data that flows as a user-generated data stream. This data has been exploited in several ...