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Proceedings Paper

Mapping species distribution of Canarian Monteverde forest by field spectroradiometry and satellite imagery
Author(s): Antonio Martín-Luis; Manuel Arbelo; Pedro Hernández-Leal; Manuel Arbelo-Bayó
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Paper Abstract

Reliable and updated maps of vegetation in protected natural areas are essential for a proper management and conservation. Remote sensing is a valid tool for this purpose. In this study, a methodology based on a WorldView-2 (WV-2) satellite image and in situ spectral signatures measurements was applied to map the Canarian Monteverde ecosystem located in the north of the Tenerife Island (Canary Islands, Spain). Due to the high spectral similarity of vegetation species in the study zone, a Multiple Endmember Spectral Mixture Analysis (MESMA) was performed. MESMA determines the fractional cover of different components within one pixel and it allows for a pixel-by-pixel variation of endmembers. Two libraries of endmembers were collected for the most abundant species in the test area. The first library was collected from in situ spectral signatures measured with an ASD spectroradiometer during a field campaign in June 2015. The second library was obtained from pure pixels identified in the satellite image for the same species. The accuracy of the mapping process was assessed from a set of independent validation plots. The overall accuracy for the ASD-based method was 60.51 % compared to the 86.67 % reached for the WV-2 based mapping. The results suggest the possibility of using WV-2 images for monitoring and regularly updating the maps of the Monteverde forest on the island of Tenerife.

Paper Details

Date Published: 25 October 2016
PDF: 8 pages
Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99981M (25 October 2016); doi: 10.1117/12.2241993
Show Author Affiliations
Antonio Martín-Luis, Univ. de La Laguna (Spain)
Manuel Arbelo, Univ. de La Laguna (Spain)
Pedro Hernández-Leal, Univ. de La Laguna (Spain)
Manuel Arbelo-Bayó, Univ. de La Laguna (Spain)

Published in SPIE Proceedings Vol. 9998:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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