Fundamental Theories and Models for Spatial Big Data Analytics

Big data is meaningless without big analysis. A LSGI research group has made systematic studies on the theories and methods for modelling uncertainty and quality control of spatial data, modelling the uncertainty propagation in spatial analysis and surface reconstruction, measuring and computing the reliability in spatial analyses and spatial data mining, algorithms and models for spatial modelling, the multi-scale representation of spatial data and spatial analysis results.

The theoretical research on uncertainty in data quality and in spatial analysis has been widely applied in spatial data quality assessment and control in Hong Kong and the region; the data quality assessment standards of Macao Geographic Information System (GIS) data, for the Macao government; and the quality assessment for the 1st National Geographic State Survey of China. The work in digital terrain modelling has been the basis for establishment of the national accuracy specifications for digital elevation models and used for quality control in the establishment of national digital elevation models.

Highly recognized internationally, the work has honoured Prof. Wen-zhong Shi and Prof. Zhilin Li with the State Natural Science Award (the second class prize) from the Central Government of China in 2007 and in 2004 respectively. They also won prestigious awards from the International Society for Photogrammetry and Remote Sensing.