Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs
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 ne...
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doaj-e6b797e88a704f36bfdad27e8619a9e32020-11-25T02:49:20ZengMDPI AGRemote Sensing2072-42922020-06-01122086208610.3390/rs12132086Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial PhotographsHimadri Biswas0Keqi Zhang1Michael S. Ross2Daniel Gann3Department of Earth and Environment, Florida International University, 11200 SW 8th Street, Miami, Florida, 33199, USADepartment of Earth and Environment, Florida International University, 11200 SW 8th Street, Miami, Florida, 33199, USADepartment of Earth and Environment, Florida International University, 11200 SW 8th Street, Miami, Florida, 33199, USAInstitute of Environment, Florida International University, 11200 SW 8th Street, OE 148, Miami, FL 33199, USAMangrove 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.https://www.mdpi.com/2072-4292/12/13/2086vegetation indexcolorRGBaccuracy assessmenttransgression |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Himadri Biswas Keqi Zhang Michael S. Ross Daniel Gann |
spellingShingle |
Himadri Biswas Keqi Zhang Michael S. Ross Daniel Gann Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs Remote Sensing vegetation index color RGB accuracy assessment transgression |
author_facet |
Himadri Biswas Keqi Zhang Michael S. Ross Daniel Gann |
author_sort |
Himadri Biswas |
title |
Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs |
title_short |
Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs |
title_full |
Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs |
title_fullStr |
Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs |
title_full_unstemmed |
Delineation of Tree Patches in a Mangrove-Marsh Transition Zone by Watershed Segmentation of Aerial Photographs |
title_sort |
delineation of tree patches in a mangrove-marsh transition zone by watershed segmentation of aerial photographs |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2020-06-01 |
description |
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. |
topic |
vegetation index color RGB accuracy assessment transgression |
url |
https://www.mdpi.com/2072-4292/12/13/2086 |
work_keys_str_mv |
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