Airborne photogrammetry and LIDAR for DSM extraction and 3D change detection over an urban area : a comparative study

A digital surface model (DSM) extracted from stereoscopic aerial images, acquired in March 2000, is compared with a DSM derived from airborne light detection and ranging (lidar) data collected in July 2009. Three densely built-up study areas in the city centre of Ghent, Belgium, are selected, each covering approximately 0.4 km(2). The surface models, generated from the two different 3D acquisition methods, are compared qualitatively and quantitatively as to what extent they are suitable in modelling an urban environment, in particular for the 3D reconstruction of buildings. Then the data sets, which are acquired at two different epochs t(1) and t(2), are investigated as to what extent 3D (building) changes can be detected and modelled over the time interval. A difference model, generated by pixel-wise subtracting of both DSMs, indicates changes in elevation. Filters are proposed to differentiate 'real' building changes from false alarms provoked by model noise, outliers, vegetation, etc. A final 3D building change model maps all destructed and newly constructed buildings within the time interval t(2) - t(1). Based on the change model, the surface and volume of the building changes can be quantified

Can building footprint extraction from LiDAR be used productively in a topographic mapping context?

Chapter 3Light Detection and Ranging (LiDAR) is a quick and economical method for obtaining cloud-point data that can be used in various disciplines and a diversity of applications. LiDAR is a technique that is based on laser technology. The process looks at the two-way travel time of laser beams and measures the time and distance travelled between the laser sensor and the ground (Shan & Sampath, 2005). National Mapping Agencies (NMAs) have traditionally relied on manual methods, such as photogrammetric capture, to collect topographic detail. These methods are laborious, work-intensive, lengthy and hence, costly. In addition because photogrammetric capture methods are often time-consuming, by the time the capture has been carried out, the information source, that is the aerial photography, is out of date (Jenson and Cowen, 1999). Hence NMAs aspire to exploit methods of data capture that are efficient, quick, and cost-effective while producing high quality outputs, which is why the application of LiDAR within NMAs has been increasing. One application that has seen significant advances in the last decade is building footprint extraction (Shirowzhan and Lim, 2013). The buildings layer is a key reference dataset and having up-to-date, current and complete building information is of paramount importance, as can be witnessed with government agencies and the private sectors spending millions each year on aerial photography as a source for collecting building footprint information (Jenson and Cowen, 1999). In the last decade automatic extraction of building footprints from LiDAR data has improved sufficiently to be of an acceptable accuracy for urban planning (Shirowzhan and Lim, 2013).peer-reviewe

Point cloud segmentation using hierarchical tree for architectural models

Recent developments in the 3D scanning technologies have made the generation of highly accurate 3D point clouds relatively easy but the segmentation of these point clouds remains a challenging area. A number of techniques have set precedent of either planar or primitive based segmentation in literature. In this work, we present a novel and an effective primitive based point cloud segmentation algorithm. The primary focus, i.e. the main technical contribution of our method is a hierarchical tree which iteratively divides the point cloud into segments. This tree uses an exclusive energy function and a 3D convolutional neural network, HollowNets to classify the segments. We test the efficacy of our proposed approach using both real and synthetic data obtaining an accuracy greater than 90% for domes and minarets.Comment: 9 pages. 10 figures. Submitted in EuroGraphics 201

Integration of LIDAR and IFSAR for mapping

LiDAR and IfSAR data is now widely used for a number of applications, particularly those needing a digital elevation model. The data is often complementary to other data such as aerial imagery and high resolution satellite data. This paper will review the current data sources and the products and then look at the ways in which the data can be integrated for particular applications. The main platforms for LiDAR are either helicopter or fixed wing aircraft, often operating at low altitudes, a digital camera is frequently included on the platform, there is an interest in using other sensors such as 3 line cameras of hyperspectral scanners. IfSAR is used from satellite platforms, or from aircraft, the latter are more compatible with LiDAR for integration. The paper will examine the advantages and disadvantages of LiDAR and IfSAR for DEM generation and discuss the issues which still need to be dealt with. Examples of applications will be given and particularly those involving the integration of different types of data. Examples will be given from various sources and future trends examined