Assessing Spatial Uncertainty of Lidar-derived Building Model

Autor: May Yuan, Mang Lung Cheuk
Rok vydání: 2009
Předmět:
Zdroj: Photogrammetric Engineering & Remote Sensing. 75:257-269
ISSN: 0099-1112
DOI: 10.14358/pers.75.3.257
Popis: Light Detection and Ranging (lidar) technology enables costeffective rapid production of digital models that capture topography and vertical structures of surface features at a fine spatial resolution. The capability has promoted lidar applications for mapping terrain, buildings, forest stands, and coastal features that cannot be adequately captured by other remote sensing means over a large area. However, in complex terrain, lidar data and lidar-derived products may contain significant uncertainty. This research provides a simple method to assess the spatial uncertainty of lidar-derived building model, using downtown Oklahoma City, Oklahoma as an example. Results indicate that significant uncertainty could be found in urban environment where: (a) building structures are complex, (b) buildings are constructed with reflective materials, and (c) vegetation grows near-by. In addition, cities under rapid development also challenge the accuracy assessment of 3D building models. To conclude, we suggest: (a) careful pre-flight planning before data collection, (b) improve the feature extraction algorithm if possible, (c) use of other remote sensing data, and (d) accuracy assessment on suggested urban environments to reduce the spatial uncertainty of lidar data and lidar-derived products.
Databáze: OpenAIRE