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Sensors 2011, 11(3), 2972-2981; doi:10.3390/s110302972

Mapping the Philippines’ Mangrove Forests Using Landsat Imagery

1
US Geological Survey, Earth Resources Observation and Science Center (EROS), Sioux Falls, SD 57198, USA
2
ARSC Research and Technology Solutions, contractor to U.S. Geological Survey (USGS) Earth Resources Observation and Science Center, Sioux Falls, SD 57198, USA
*
Author to whom correspondence should be addressed.
Received: 6 February 2011 / Accepted: 25 February 2011 / Published: 7 March 2011
(This article belongs to the Special Issue 10 Years Sensors - A Decade of Publishing)
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Abstract

Current, accurate, and reliable information on the areal extent and spatial distribution of mangrove forests in the Philippines is limited. Previous estimates of mangrove extent do not illustrate the spatial distribution for the entire country. This study, part of a global assessment of mangrove dynamics, mapped the spatial distribution and areal extent of the Philippines’ mangroves circa 2000. We used publicly available Landsat data acquired primarily from the Global Land Survey to map the total extent and spatial distribution. ISODATA clustering, an unsupervised classification technique, was applied to 61 Landsat images. Statistical analysis indicates the total area of mangrove forest cover was approximately 256,185 hectares circa 2000 with overall classification accuracy of 96.6% and a kappa coefficient of 0.926. These results differ substantially from most recent estimates of mangrove area in the Philippines. The results of this study may assist the decision making processes for rehabilitation and conservation efforts that are currently needed to protect and restore the Philippines’ degraded mangrove forests. View Full-Text
Keywords: mangrove; Landsat; mapping; unsupervised classification mangrove; Landsat; mapping; unsupervised classification
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Long, J.B.; Giri, C. Mapping the Philippines’ Mangrove Forests Using Landsat Imagery. Sensors 2011, 11, 2972-2981.

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