On 3D Topological Relationships

This paper presents an integrated study on possible topological relationship between multidimensional simple objects in 0,1,2 and 3 D space. The formal categorisation of spatial relationships is completed upon the 9intersections model. The focus is on the definition of a unified set of conditions for eliminating relationships that cannot be realised in reality. The negative conditions are formulated on the basis of dimension and co-dimension of objects, and connectivity of boundaries. The set of 25 conditions is sufficient for deriving all the possible relationships mentioned currently in the literature and for specifying the relationships between surface and surface in 3D space. Drawings of example configurations verify the obtained results in 3D space. 1 Introduction The topological spatial relationships gain an increasing attention in the last decade. The topic of research has shifted from issues related to the definition of a particular formalism to represent topological relation..

Research and capacity building

GIS TechnologyOTB Research Institut

Enabling obstacle avoidance for Google maps' navigation service

City infrastructures are sensitive to disasters. To aid rescue workers and citizens, a system is needed which determines the shortest route to a certain location, taking the damages of the infrastructure into account. The biggest disadvantage of current navigation systems is that they are “closed” i.e. they are built on top of commercial software packages and as such are only usable by rescue organizations which own licenses for these software packages. Modern web-technologies provide tools to ease information collection and to facilitate the dissemination of data. Recent successes of crowdsourced platforms such as OpenStreetMap, Ushahidi and Wikipedia, suggest the deployment of the crowdsourcing phenomenon to disaster management. The idea is to let the “crowd” in a disaster area collect information about the state of the infrastructure. People on the street form a highly dispersed network of sensors which is able to provide information in real-time at no cost to the rescue workers. This paper proposes and implements a method for performing shortest path calculations taking crowdsourced information, in the form of constraints and obstacles, into account. The method is built on top of Google Maps (GM) and uses its routing service to calculate the shortest distance between two locations. Users provide the constraints and obstacles in the form of polygons which identify impassable areas in the real world. The A* pathfinding algorithm is used to guide Google's Directions Service around obstacles.OTB ResearchOTB Research Institute for the Built Environmen

Formal modelling of processes and tasks to support use and search of geo-information in emergency response

Many Command& Control or Early warning systems have been developed providing access to large amounts of data (and metadata) via geo-portals, or by accessing predefined data sets relaying on Spatial Data Infrastructure. However, the users involved in emergency response are usually not geoinformation specialists and they lack deep understanding about the spatial data structures and corresponding terminology. Semantic web and knowledge engineering approaches applied to geo-data can bring significant improvements in these directions. This paper presents a formal modeling for the emergency management as performed in the Netherlands. Having the tasks of the actors well specified, it is possible to define the geo-information needed for completing the task.Department of GIS TechnologyOTB Research Institut

Google maps for crowdsourced emergency routing

Gathering infrastructure data in emergency situations is challenging. The affected by a disaster areas are often large and the needed observations numerous. Spaceborne remote sensing techniques cover large areas but they are of limited use as their field of view may be blocked by clouds, smoke, buildings, highways, etc. Remote sensing products furthermore require specialists to collect and analyze the data. This contrasts the nature of the damage detection problem: almost everyone is capable of observing whether a street is usable or not. The crowd is fit for solving these challenges as its members are numerous, they are willing to help and are often in the vicinity of the disaster thereby forming a highly dispersed sensor network. This paper proposes and implements a small WebGIS application for performing shortest path calculations based on crowdsourced information about the infrastructure health. The application is built on top of Google Maps and uses its routing service to calculate the shortest distance between two locations. Impassable areas are indicated on a map by people performing in-situ observations on a mobile device, and by users on a desktop machine who consult a multitude of information sources.OTB ResearchOTB Research Institute for the Built Environmen

Spatial subdivision of complex indoor environments for 3D indoor navigation

As we realize that we spend most of our time in increasingly complex indoor environments, applications to assist indoor activities (e.g. guidance) have gained a lot of attention in the recent years. The advances in ubiquitous computing made possible the development of several spatial models intending to support context-aware and fine-grained indoor navigation systems. However, the available models often rely on simplified representations (e.g. 2D plans) and ignore the indoor features (e.g. furniture), thereby missing to reflect the complexity of the indoor environment. In this paper, we introduce the Flexible Space Subdivision framework (FSS) that allows to automatically identify the spaces that can be used for indoor navigation purpose. We propose a classification of indoor objects based on their ability to autonomously change location and we define a spatial subdivision of the indoor environment based on the classified objects and their functions. The framework can consider any 3D indoor configuration, the static and dynamic activities it hosts and it enables the possibility to consider all types of locomotion (e.g. walking, flying, etc.). It relies on input 3D models with geometric, semantic and topological information and identifies a set of subspaces with dedicated properties. We assess the framework against criteria defined in previous researches and we provide an example.Urban Data Scienc