Eratosthene is an open source 4D server developed by Nils Hamel from 2015 to 2020 at DHLAB. It consists in a four dimensional indexation framework for large scale three-dimensional models. It enables efficient organisation, storage and dissemination of access to the network of large-scale models referenced in space and time. The server can manage very large objects of several hundred Gio, such as the SRTM or dense LIDAR models. It manages cloud points, volumetric polygonal objects and vector models. It can also perform logical operations to detect changes in urban and territorial environments.
View of the city of Venice in 2010 – Data : photogrammetric model computed at the DHLAB using IUAV University aerial images, openMVG and openMVS open source solutions
View of the AND logical operator applied on the LIDAR models of Geneva in 2005 and 2009. Data : aerial LIDAR campaigns conducted by the Geneva SITG in 2005 and 2009
View of a volumetric polygonal of the city of Geneva in 2018. Data : SITG building model
View the land register of the city of Chaux-de-Fonds in 2004. Data : SITN land register
View of a mixed model of the city of Chaux-de-Fonds : 2004 land register and 2018 volumetric model. Data : SITN
View of mixed models of the city of Chaux-de-Fonds : 2004 land register and 2016 colored lidar model. Data : SITN
View of the city of Venice in 2010 – Data : photogrammetric model computed at the DHLAB using IUAV University aerial images, openMVG and openMVS open source solutionsView of the AND logical operator applied on the LIDAR models of Geneva in 2005 and 2009. Data : aerial LIDAR campaigns conducted by the Geneva SITG in 2005 and 2009
View of a volumetric polygonal of the city of Geneva in 2018. Data : SITG building modelView the land register of the city of Chaux-de-Fonds in 2004. Data : SITN land register
View of a mixed model of the city of Chaux-de-Fonds : 2004 land register and 2018 volumetric model. Data : SITN
View of mixed models of the city of Chaux-de-Fonds : 2004 land register and 2016 colored lidar model. Data : SITN
