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Integration of GF2 Optical, GF3 SAR, and UAV Data for Estimating Aboveground Biomass of China’s Largest Artificially Planted Mangroves
Open AccessArticle

Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs

by Himadri Biswas 1,2,*, Keqi Zhang 1,3, Michael S. Ross 1,2 and Daniel Gann 2,4,5
1
Department of Earth and Environment, Florida International University, 11200 SW 8th Street, Miami, Florida, 33199, USA
2
Institute of Environment, Florida International University, 11200 SW 8th Street, OE 148, Miami, FL 33199, USA
3
Extreme Events Institute, Florida International University, 11200 SW 8th Street, AHC5 220, Miami, FL 33199, USA
4
Department of Biological Sciences, Florida International University, 11200 SW 8th Street, Miami, FL 33199, USA
5
GIS Center, Florida International University, 11200 SW 8th Street, GL 275, Miami, FL 33199, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(13), 2086; https://doi.org/10.3390/rs12132086
Received: 29 May 2020 / Revised: 23 June 2020 / Accepted: 23 June 2020 / Published: 29 June 2020
(This article belongs to the Special Issue Remote Sensing in Mangroves)
Mangrove migration, or transgression in response to global climatic changes or sea-level rise, is a slow process; to capture it, understanding both the present distribution of mangroves at individual patch (single- or clumped trees) scale, and their rates of change are essential. In this study, a new method was developed to delineate individual patches and to estimate mangrove cover from very high-resolution (0.08 m spatial resolution) true color (Red (R), Green (G), and Blue (B) spectral channels) aerial photography. The method utilizes marker-based watershed segmentation, where markers are detected using a vegetation index and Otsu’s automatic thresholding. Fourteen commonly used vegetation indices were tested, and shadows were removed from the segmented images to determine their effect on the accuracy of tree detection, cover estimation, and patch delineation. According to point-based accuracy analysis, we obtained adjusted overall accuracies >90% in tree detection using seven vegetation indices. Likewise, using an object-based approach, the highest overlap accuracy between predicted and reference data was 95%. The vegetation index Excess Green (ExG) without shadow removal produced the most accurate mangrove maps by separating tree patches from shadows and background marsh vegetation and detecting more individual trees. The method provides high precision delineation of mangrove trees and patches, and the opportunity to analyze mangrove migration patterns at the scale of isolated individuals and patches. View Full-Text
Keywords: vegetation index; color; RGB; accuracy assessment; transgression vegetation index; color; RGB; accuracy assessment; transgression
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Biswas, H.; Zhang, K.; Ross, M.S.; Gann, D. Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs. Remote Sens. 2020, 12, 2086.

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