Selective 4D modelling framework for spatial-temporal Land Information Management System

This paper introduces a predictive (selective) 4D modelling framework where only the spatial 3D differences are modelled at the forthcoming time instances, while regions of no significant spatial-temporal alterations remain intact. To accomplish this, initially spatial-temporal analysis is applied between 3D digital models captured at different time instances. So, the creation of dynamic change history maps is made. Change history maps indicate spatial probabilities of regions needed further 3D modelling at forthcoming instances. Thus, change history maps are good examples for a predictive assessment, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 4D Land Information Management System (LIMS) is implemented using open interoperable standards based on the CityGML framework. CityGML allows the description of the semantic metadata information and the rights of the land resources. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 4D LIMS digital parcels and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics. An application is made to detect the change through time of a 3D block of plots in an urban area of Athens, Greece. Starting with an accurate 3D model of the buildings in 1983, a change history map is created using automated dense image matching on aerial photos of 2010. For both time instances meshes are created and through their comparison the changes are detected.