The current research projects fall into one or more of the following topics:

Extracting Traffic Events and Human Mobility Patterns in Geosocial Media Data for Assessing Realtime Road Traffic

Large urban centers and emerging city regions, as well as others in the world, face a series of complex challenges such as traffic congestions as they continue to grow at a rapid pace. Many largest cities around the world, including Canadian cities such as Vancouver and Toronto, are known among top worst for traffic congestion. With increasing traffic congestion causing delays and health problems for motorists and producing extra air pollutions, reliable traffic information is key for travelers all over the world. This proposed research will develop new traffic event detection methods for providing such real-time information using massive social media data, and also will build extra tools for integrating human mobility patterns into short-term traffic congestion prediction that will help predict traveler’s road traffic conditions in next 15-60 minutes ahead. The results (models, methods and tools) of this research can be of great use by a new generation of urban planners, city traffic managers and researchers.

Geospatial Collaboration: Theory, Systems and Applications

Urban, utility, and transportation developments, as well as emergency and disaster management, depend largely on innovative information technologies required for supporting their design/planning/decision-making processes in order to achieve beneficial economic, social and environmental outcomes. In contrast to traditional planning/decision-making processes which involve a relatively small group of experts, a democratic process has emerged requiring input from a large group of diverse stakeholders including the public. Geospatial collaboration, incorporating the principles of computer supported cooperative work (CSCW), provides methods and tools to facilitate this process to maximize the above benefits, minimize potential impact on the environment or make informed decisions by supporting geographically dispersed people in collaborating on a common decision task by sharing the same geographic representations and exploring alternatives in various “time-place” scenarios. (more on current projects)

Event-driven Geospatial Infrastructure

Recent developments in physical and virtual sensor, sensor network, other data collection and information technologies have resulted in a huge amount of a continuous and ever-expanding stream of real-time information (or events), which is far beyond human’s capacity to process. In recent years, event-driven architecture (EDA) and the resurgence of complex event processing have formed a new technology paradigm for event-based applications. Event-driven architecture, along with service-oriented architecture and open source, represents another web trend for geospatial applications, and has been rated as one of the technologies having particularly high impact in the next 10 years. Shifted from the current “request/response” based system to a “sense/respond” or “publish/subscribe” environment, the event-driven design allows the system to “sense” things that are happening and actively “respond” to them. Systems and applications developed based on event-driven architecture are able to detect incoming events, process (identify and correlate) these events to find patterns based on the defined business/application rules, and ultimately respond to the events and/or take intelligent actions appropriately and expeditiously.  (more on current projects)

Geospatial Data Extractions and Knowledge Discovery based on Crowdsourceing

Global positioning system (GPS) data crowdsourced through GPS-enabled mobile devices, such as smart phones and in-car navigation systems, is an emerging source of inexpensive data that can be used to provide real-time traffic information, identify traffic patterns, and predict traffic congestions, as well as extracting road network data. Algorithms and techniques are needed for extracting traffic information (e.g., traffic volume, patterns, etc.) and road network data (e.g., road centerlines, # of lanes, etc.). The current study focuses on the development of methods and software tools for extracting road networks from GPS data collected by smart phones. The results will provide an cost-effective way of updating existing road networks in a timely manner. This can supplement, if not replace, the current practices of acquiring road network data using either traditional survey or remote sensing approaches, which are expensive and time consuming.  (more on current projects)

Spatiotemporal Database Modeling and Sea Ice Data Services

Sea ice data has significant scientific value for climate, environmental impact and engineering studies leading to the construction of facilities in Arctic waters, as well as to support tourism and fishing planning. Large collections of such data are acquired, compiled, produced and maintained by national and international agencies. Aiming at developing a Canadian sea ice information infrastructure that manages historical, ongoing and in‐situ sea ice data for research and decision‐making, the cuurent focus is on spatiotemporal sea ice database and open web APIs for accessing sea ice information and web-based, user‐defined functions to support query and manipulation of sea ice data for basic data manipulation functions, and standard analytical and statistical tools.  (more on current projects)

Urban Solar Energy Modeling and Mapping

Solar energy potential in complex urban environments depends on available irradiance, geographic location, local environment, technology efficiency and social and economic factors. Factors such as terrain, size and orientation of building rooftops and facades, shading from buildings, trees and other structures, and snow covers also affect the actual solar irradiance received. 3D modeling of buildings and their rooftop geometries as well tree coverage allows for more accurate estimation of solar energy potential on certain facades and rooftops to predict for example hourly generation of electricity by solar panels. The research aims to develop innovative solar energy mapping and assessment system and methodologies for real-time, easy, reliable and accurate assessment and prediction of solar energy potential in relation to energy consumption in urban areas.  (more on current projects)