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  • ISPRS-IJGI Special Issue: Mapping, Modeling and Prediction with VGI

    Dear Colleagues,

    Empowered by geospatial technologies, such as location-aware smartphones, many ordinary citizens are now acting as human sensors and voluntarily contributing geo-referenced ground observations regarding a broad array of geographic phenomena. Such geospatial data contributed by citizen volunteers are collectively referred to as volunteered geographic information (VGI), which broadly encompasses geographic information created through public participatory geographic information systems, citizen science, crowdsourcing, and social media, amongst other mechanisms. VGI has been revolutionizing the way geographic data, information, and knowledge are generated and disseminated. Moreover, VGI is an important source of geospatial big data that could potentially shift geographical research from traditional approaches toward a new “data-intensive” or “data-driven” paradigm.

    VGI has great potential to reveal the spatial and temporal dynamics of the physical and social geographic phenomena under observation. This potential is realized by using VGI observations for 1) mapping the spatial and temporal distributions of geographic phenomena, 2) modeling the underlying processes shaping the spatial and temporal patterns, and 3) model-based prediction of geographic phenomena in space and time. New theoretical perspectives and analytical methods are being developed to address challenges facing VGI (e.g., data quality issues, biases) and to facilitate VGI applications along these lines. Some examples of such VGI applications are geographic feature mapping, biodiversity mapping, land use and land cover mapping, disaster mapping, species distribution modeling and prediction, traffic congestion modeling, human mobility modeling, etc. Furthermore, we are still witnessing the continuing growth and expansion of VGI applications.

    We invite research articles and reviews broadly fitting in the general theme of “Mapping, Modeling, and Prediction with VGI” to be published in this Special Issue. Submissions to the Special Issue are open to all interested scholars.

    Assis. Prof. Guiming Zhang
    Prof. A-Xing Zhu
    Guest Editors

    For more information, please visit

This portfolio last updated: 26-Oct-2021 9:38 PM