LULC database updating from VHR images and LIDAR data using evidence theory
Borja Rodríguez-Cuenca, M. Concepción Alonso, Agustín Tamés-Noriega
Available Online June 2015.
- 10.2991/ifsa-eusflat-15.2015.139How to use a DOI?
- Evidence theory, VHR imagery, LIDAR, pattern recognition, segmentation.
Urban growth and the development of urban plans make cities grow and substantially alter, in relatively short time periods, their land covers and land uses (LULC). To take control of this urban growth, it is im-portant to create and update the LULC database. In this work, a method to automatically extract land covers from satellite VHR imagery and LIDAR data is pre-sented. This method is based on the Dempster-Shafer evidence theory. The efficiency of this method is tested in three test sites in the Spanish city of Gijón. The pro-vided results are compared with the SIOSE database in order to determine changes in the LULC.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Borja Rodríguez-Cuenca AU - M. Concepción Alonso AU - Agustín Tamés-Noriega PY - 2015/06 DA - 2015/06 TI - LULC database updating from VHR images and LIDAR data using evidence theory BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 987 EP - 993 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.139 DO - 10.2991/ifsa-eusflat-15.2015.139 ID - Rodríguez-Cuenca2015/06 ER -