Now showing 1 - 6 of 6
  • Publication
    Evaluation of Automatically Generated 2D Footprints from Urban LiDAR Data
    (International Society for Photogrammetry and Remote Sensing (ISPRS), 2015-10-03) ;
    Over the last decade, several automatic approaches have been proposed to extract and reconstruct 2D building footprints and 2D road profiles from ALS data, satellite images, and/or aerial imagery. Since these methods have to date been applied to various data sets and assessed through a variety of different quality indicators and ground truths, comparing the relative effectiveness of the techniques and identifying their strengths and short-comings has not been possible in a systematic way. This open contest was designed to overcoming this shortcoming. Specifically, participants were asked to submit 2D footprints (building outlines and road profiles) derived from ALS data from a highly dense data (approximately 225 points/m2) across a 1km2 of central Dublin, Ireland. The proposed evaluation strategies were designed to measure not only the capacity of each method to detect and reconstruct 2D buildings and roads but also the quality of the reconstructed building and road models in terms of shape similarity and positional accuracy. The evaluated methods will represent those submitted as part of IQPC15.
    Scopus© Citations 1  275
  • Publication
    Aerial laser scanning and imagery data fusion for road detection in city scale
    This paper presents a workflow including a novel algorithm for road detection from dense LiDAR fused with high-resolution aerial imagery data. Using a supervised machine learning approach point clouds are firstly classified into one of three groups: building, ground, or unassigned. Ground points are further processed by a novel algorithm to extract a road network. The algorithm exploits the high variance of slope and height of the point data in the direction orthogonal to the road boundaries. Applying the proposed approach on a 40 million point dataset successfully extracted a complex road network with an F-measure of 76.9%.
    Scopus© Citations 17  809
  • Publication
    Quantitative evaluation strategies for urban 3D model generation from remote sensing data
    Over the last decade, several automatic approaches have been proposed to reconstruct 3D building models from aerial laser scanning (ALS) data. Typically, they have been benchmarked with data sets having densities of less than 25 points/m2. However, these test data sets lack significant geometric points on vertical surfaces. With recent sensor improvements in airborne laser scanners and changes in flight path planning, the quality and density of ALS data have improved significantly. The paper presents quantitative evaluation strategies for building extraction and reconstruction when using dense data sets. The evaluation strategies measure not only the capacity of a method to detect and reconstruct individual buildings but also the quality of the reconstructed building models in terms of shape similarity and positional accuracy.
    Scopus© Citations 46  624
  • Publication
    A Big Data Approach for 3D Building Extraction from Aerial Laser Scanning
    (American Society of Civil Engineers, 2016-05) ; ;
    This paper proposes a Big Data approach to automatically identify and extract buildings from a digital surface model created from aerial laser scanning data. The approach consists of two steps. The first step is a MapReduce process where neighboring points in a digital surface model are mapped into cubes. The second step uses a non-MapReduce algorithm first to remove trees and other obstructions and then to extract adjacent cubes. According to this approach, all adjacent cubes belong to the same object and an object is a set of adjacent cubes that belong to one or more adjacent buildings. Finally, an evaluation study is presented for a section of Dublin, Ireland to demonstrate the applicability of the approach resulting in a 92% quality level for the extraction of 106 buildings over 1 km2 including buildings that had more than 10 adjacent components of different heights and complicated roof geometries. The proposed approach is notable not only for its Big Data context but its usage of vector data.
      516Scopus© Citations 29
  • Publication
    Planning Infrastructure Documentation with Aerial Laser Scanning
    (International Association for Bridge and Structural Engineering (IABSE), 2013-05-08)
    Worldwide there are millions of bridges and overpasses that need documentation, inspection, and maintenance. Aerial laser scanning has the potential to assist in this process not only through the initial documentation stage but through the automated creation of three-dimensional, computational models and a further integration of that data with the surrounding environment. This paper outlines the difficulties related to effective vertical data capture for major infrastructure elements and recommends specific approaches towards a geometric optimization of this problem. Results of the current level of viability using a test area in Dublin, Ireland are included based on the application of this optimization.
      438
  • Publication
    Aerial Flightpath Considerations for Documenting Urban Heritage Using Laser Scanning
    This paper provides guidance for the planning of urban heritage documentation using aerial laser scanning. The paper presents standard industrial considerations typically undertaken by commercial data providers and the additional factors that such be raised in the planning stage when urban heritage documentation is the goal.
      151