The research work in the Environmental Crowdsourcing Lab (ECSL) focuses on topics and ideas dealing with the interpretation, mining, and integration of contributed spatio-temporal data (citizen science and participatory mapping), aimed at enriching and augmenting the existing environmental knowledge base and developing new location-based services. The research is mainly concerned with route optimization, environmental cognition, enrichment of environmental monitoring systems, location-based services and the identification of patterns and behavior of moving objects.
Crowdsourcing user-generated location data shows enormous potential to address sustainable problems and current social problems that traditional tools and technologies in the fields of mapping and geoinformation do not provide. The research in the lab includes examining and using location data from various sources created by users, including social networks, in order to analyze, retrieve and extract information and knowledge related to human knowledge, and mobility patterns and behavior. These are used to develop new location-based services, sustainable socio-technological tools for groups and communities in society, and to understand our behavior in the environment.