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We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first laye...
A generic probabilistic model, under fundamental Bayes’ rule and Markov assumption, is introduced to integrate the process of mobile platform localization with optical sensors. And based on it, three ...
Canopy Height Model (CHM) is a standard LiDAR-derived product for deriving relevant forest inventory information, among which individual tree identification is a crucial task. The watershed algorithm ...
Cleaning laser scanner point clouds from erroneous measurements (outliers) is one of the most time consuming tasks that has to be done before modeling. There are algorithms for outlier detection in di...
Multiple Representation Databases are structures that link different data sets based on common geometry and/or semantics. They offer the possibility to realize an efficient updating process in case of...
Traditional single-lens vertical photogrammetry can obtain object images from the air with rare lateral information of tall buildings. Multi-view airborne photogrammetry can get rich lateral texture o...
To ensure a resilient Healthcare Critical Infrastructure, understanding the vulnerabilities and analysing the interdependency on other critical infrastructures is important. To model this critical inf...
In existing construction experience of Spatial Data Infrastructure (SDI), GeoNetwork, as the geographical information integrated solution, is an effective way of building SDI. During GeoNetwork serv...
This paper presents a comprehensive approach to effectively extract cartographic urban data from high resolution satellite imagery. It consists of a sequence of image processing techniques, for image ...
In Portugal, updating municipal plans (1:10 000) isrequired every ten years. High spatial resolution imagery has shown its potential for detailed urban land cover mapping at large scales. However, sha...

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