6 September 2017 Extraction of inland Nypa fruticans (Nipa Palm) using Support Vector Machine
Author Affiliations +
Proceedings Volume 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017); 1044406 (2017) https://doi.org/10.1117/12.2277522
Event: Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017), 2017, Paphos, Cyprus
Abstract
Mangroves are considered as one of the major habitats in coastal ecosystem, providing a lot of economic and ecological services in human society. Nypa fruticans (Nipa palm) is one of the important species of mangroves because of its versatility and uniqueness as halophytic palm. However, nipas are not only adaptable in saline areas, they can also managed to thrive away from the coastline depending on the favorable soil types available in the area. Because of this, mapping of this species are not limited alone in the near shore areas, but in areas where this species are present as well. The extraction process of Nypa fruticans were carried out using the available LiDAR data. Support Vector Machine (SVM) classification process was used to extract nipas in inland areas. The SVM classification process in mapping Nypa fruticans produced high accuracy of 95+%. The Support Vector Machine classification process to extract inland nipas was proven to be effective by utilizing different terrain derivatives from LiDAR data.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
R. T. Alberto, R. T. Alberto, S. C. Serrano, S. C. Serrano, G. B. Damian, G. B. Damian, E. E. Camaso, E. E. Camaso, A. R. Biagtan, A. R. Biagtan, N. Z. Panuyas, N. Z. Panuyas, J. S. Quibuyen, J. S. Quibuyen, } "Extraction of inland Nypa fruticans (Nipa Palm) using Support Vector Machine", Proc. SPIE 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017), 1044406 (6 September 2017); doi: 10.1117/12.2277522; https://doi.org/10.1117/12.2277522
PROCEEDINGS
8 PAGES


SHARE
KEYWORDS
Back to Top