Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-Analysis
In spite of their importance, mangroves are still threatened by a significant reduction in global forest cover due to conversion to non-forest land uses. To implement robust policies and actions in mangrove conservation, quantitative methods in monitoring mangrove attributes are vital. This study in...
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Format: | Article |
Language: | English |
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MDPI AG
2023-05-01
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Series: | Forests |
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Online Access: | https://www.mdpi.com/1999-4907/14/6/1080 |
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author | Fejaycris Pillodar Peter Suson Maricar Aguilos Ruben Amparado |
author_facet | Fejaycris Pillodar Peter Suson Maricar Aguilos Ruben Amparado |
author_sort | Fejaycris Pillodar |
collection | DOAJ |
description | In spite of their importance, mangroves are still threatened by a significant reduction in global forest cover due to conversion to non-forest land uses. To implement robust policies and actions in mangrove conservation, quantitative methods in monitoring mangrove attributes are vital. This study intends to study the trend in mangrove resource mapping using remote sensing (RS) to determine the appropriate methods and datasets to be used in monitoring the distribution, aboveground biomass (AGB), and carbon stock (CS) in mangroves. A meta-analysis of several research publications related to mangrove resource mapping using RS in the Philippines has been conducted. A database was constructed containing 59 peer-reviewed articles selected using the protocol search, appraisal, synthesis, analysis, report (PSALSAR) framework and preferred reporting items for systematic reviews and meta-analysis (PRISMA). The study clarified that support vector machine (SVM) has shown to be more effective (99%) in discriminating mangroves from other land cover. Light detection and ranging (LiDAR) data also has proven to give a promising result in overall accuracy in mangrove-extent mapping (99%), AGB, and CS estimates (99%), and even species-level mapping (77%). Medium to low-resolution datasets can still achieve high overall accuracy by using appropriate algorithms or predictive models such as the mangrove vegetation index (MVI). The study has also found out that there are still few reports on the usage of high-spatial-resolution datasets, most probably due to their commercial restrictions. |
first_indexed | 2024-03-11T02:28:07Z |
format | Article |
id | doaj.art-e0dc18a37347417db1d01308aaa4fa9a |
institution | Directory Open Access Journal |
issn | 1999-4907 |
language | English |
last_indexed | 2024-03-11T02:28:07Z |
publishDate | 2023-05-01 |
publisher | MDPI AG |
record_format | Article |
series | Forests |
spelling | doaj.art-e0dc18a37347417db1d01308aaa4fa9a2023-11-18T10:26:06ZengMDPI AGForests1999-49072023-05-01146108010.3390/f14061080Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-AnalysisFejaycris Pillodar0Peter Suson1Maricar Aguilos2Ruben Amparado3Environmental Science Graduate Program, Department of Biological Sciences, College of Science and Mathematics, Mindanao State University-Iligan Institute of Technology, Iligan City 9200, PhilippinesEnvironmental Science Graduate Program, Department of Biological Sciences, College of Science and Mathematics, Mindanao State University-Iligan Institute of Technology, Iligan City 9200, PhilippinesDepartment of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USAEnvironmental Science Graduate Program, Department of Biological Sciences, College of Science and Mathematics, Mindanao State University-Iligan Institute of Technology, Iligan City 9200, PhilippinesIn spite of their importance, mangroves are still threatened by a significant reduction in global forest cover due to conversion to non-forest land uses. To implement robust policies and actions in mangrove conservation, quantitative methods in monitoring mangrove attributes are vital. This study intends to study the trend in mangrove resource mapping using remote sensing (RS) to determine the appropriate methods and datasets to be used in monitoring the distribution, aboveground biomass (AGB), and carbon stock (CS) in mangroves. A meta-analysis of several research publications related to mangrove resource mapping using RS in the Philippines has been conducted. A database was constructed containing 59 peer-reviewed articles selected using the protocol search, appraisal, synthesis, analysis, report (PSALSAR) framework and preferred reporting items for systematic reviews and meta-analysis (PRISMA). The study clarified that support vector machine (SVM) has shown to be more effective (99%) in discriminating mangroves from other land cover. Light detection and ranging (LiDAR) data also has proven to give a promising result in overall accuracy in mangrove-extent mapping (99%), AGB, and CS estimates (99%), and even species-level mapping (77%). Medium to low-resolution datasets can still achieve high overall accuracy by using appropriate algorithms or predictive models such as the mangrove vegetation index (MVI). The study has also found out that there are still few reports on the usage of high-spatial-resolution datasets, most probably due to their commercial restrictions.https://www.mdpi.com/1999-4907/14/6/1080mangrovesmeta-analysisremote sensingPhilippines |
spellingShingle | Fejaycris Pillodar Peter Suson Maricar Aguilos Ruben Amparado Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-Analysis Forests mangroves meta-analysis remote sensing Philippines |
title | Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-Analysis |
title_full | Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-Analysis |
title_fullStr | Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-Analysis |
title_full_unstemmed | Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-Analysis |
title_short | Mangrove Resource Mapping Using Remote Sensing in the Philippines: A Systematic Review and Meta-Analysis |
title_sort | mangrove resource mapping using remote sensing in the philippines a systematic review and meta analysis |
topic | mangroves meta-analysis remote sensing Philippines |
url | https://www.mdpi.com/1999-4907/14/6/1080 |
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