Next Article in Journal
Estimating the Total Nitrogen Concentration of Reed Canopy with Hyperspectral Measurements Considering a Non-Uniform Vertical Nitrogen Distribution
Previous Article in Journal
Land Surface Temperature Differences within Local Climate Zones, Based on Two Central European Cities
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2016, 8(10), 787; doi:10.3390/rs8100787

Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping

Cartography and GIS Research Group, Vrije Universiteit Brussel, Brussel 1050, Belgium
*
Author to whom correspondence should be addressed.
Academic Editors: Bailang Yu, Soe W. Myint, Clement Atzberger and Prasad S. Thenkabail
Received: 7 June 2016 / Revised: 22 August 2016 / Accepted: 8 September 2016 / Published: 22 September 2016
View Full-Text   |   Download PDF [11889 KB, uploaded 24 September 2016]   |  

Abstract

Land cover mapping of the urban environment by means of remote sensing remains a distinct challenge due to the strong spectral heterogeneity and geometric complexity of urban scenes. Airborne imaging spectroscopy and laser altimetry have each made remarkable contributions to urban mapping but synergistic use of these relatively recent data sources in an urban context is still largely underexplored. In this study a synergistic workflow is presented to cope with the strong diversity of materials in urban areas, as well as with the presence of shadow. A high-resolution APEX hyperspectral image and a discrete waveform LiDAR dataset covering the Eastern part of Brussels were made available for this research. Firstly, a novel shadow detection method based on LiDAR intensity-APEX brightness thresholding is proposed and compared to commonly used approaches for shadow detection. A combination of intensity-brightness thresholding with DSM model-based shadow detection is shown to be an efficient approach for shadow mask delineation. To deal with spectral similarity of different types of urban materials and spectral distortion induced by shadow cover, supervised classification of shaded and sunlit areas is combined with iterative LiDAR post-classification correction. Results indicate that height, slope and roughness features contribute to improved classification accuracies in descending order of importance. Results of this study illustrate the potential of synergistic application of hyperspectral imagery and LiDAR for urban land cover mapping. View Full-Text
Keywords: urban; land cover; shadow detection; shadow compensation; support vector machines; hyperspectral remote sensing; APEX; LiDAR; post-classification urban; land cover; shadow detection; shadow compensation; support vector machines; hyperspectral remote sensing; APEX; LiDAR; post-classification
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Priem, F.; Canters, F. Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping. Remote Sens. 2016, 8, 787.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top