Remote sensing-based mangrove blue carbon assessment in the Asia-Pacific: A systematic review.

Above-ground mangrove biomass Coastal ecosystems Indo-Pacific Machine learning Mangrove carbon Multispectral sensors

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
19 May 2024
Historique:
received: 18 12 2023
revised: 28 03 2024
accepted: 13 05 2024
medline: 22 5 2024
pubmed: 22 5 2024
entrez: 21 5 2024
Statut: aheadofprint

Résumé

Accurate measuring, mapping, and monitoring of mangrove forests support the sustainable management of mangrove blue carbon in the Asia-Pacific. Remote sensing coupled with modeling can efficiently and accurately estimate mangrove blue carbon stocks at larger spatiotemporal extents. This study aimed to identify trends in remote sensing/modeling employed in estimating mangrove blue carbon, attributes/variations in mangrove carbon sequestration estimated using remote sensing, and to compile research gaps and opportunities, followed by providing recommendations for future research. Using a systematic literature review approach, we reviewed 105 remote sensing-based peer-reviewed articles (1990 - June 2023). Despite their high mangrove extent, there was a paucity of studies from Myanmar, Bangladesh, and Papua New Guinea. The most frequently used sensor was Sentinel-2 MSI, accounting for 14.5 % of overall usage, followed by Landsat 8 OLI (11.5 %), ALOS-2 PALSAR-2 (7.3 %), ALOS PALSAR (7.2 %), Landsat 7 ETM+ (6.1 %), Sentinel-1 (6.7 %), Landsat 5 TM (5.5 %), SRTM DEM (5.5 %), and UAV-LiDAR (4.8 %). Although parametric methods like linear regression remain the most widely used, machine learning regression models such as Random Forest (RF) and eXtreme Gradient Boost (XGB) have become popular in recent years and have shown good accuracy. Among a variety of attributes estimated, below-ground mangrove blue carbon and the valuation of carbon stock were less studied. The variation in carbon sequestration potential as a result of location, species, and forest type was widely studied. To improve the accuracy of blue carbon measurements, standardized/coordinated and innovative methodologies accompanied by credible information and actionable data should be carried out. Technical monitoring (every 2-5 years) enhanced by remote sensing can provide accurate and precise data for sustainable mangrove management while opening ventures for voluntary carbon markets to benefit the environment and local livelihood in developing countries in the Asia-Pacific region.

Identifiants

pubmed: 38772491
pii: S0048-9697(24)03417-X
doi: 10.1016/j.scitotenv.2024.173270
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

173270

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Auteurs

Abhilash Dutta Roy (AD)

Ecoresolve, San Francisco, CA, United States; Mediterranean Forestry and Natural Resources Management, School of Agriculture, University of Lisbon, Portugal; Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea; School of Agrifood and Forestry Engineering and Veterinary Medicine, University of Lleida, Lleida, Spain.

Pavithra S Pitumpe Arachchige (PS)

Ecoresolve, San Francisco, CA, United States; Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea.

Michael S Watt (MS)

Scion, Christchurch, New Zealand.

Apoorwa Kale (A)

Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea.

Mollie Davies (M)

Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea.

Joe Eu Heng (JE)

Ecoresolve, San Francisco, CA, United States; Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea.

Redeat Daneil (R)

Ecoresolve, San Francisco, CA, United States; Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea.

G A Pabodha Galgamuwa (GAP)

Ecoresolve, San Francisco, CA, United States; Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea; The Nature Conservancy, Maryland/DC Chapter, Cumberland, MD, United States.

Lara G Moussa (LG)

Ecoresolve, San Francisco, CA, United States; Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea.

Kausila Timsina (K)

Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea.

Ewane Basil Ewane (EB)

Ecoresolve, San Francisco, CA, United States; Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea; BlueForests, San Francisco, CA, United States; Department of Geography, Faculty of Social and Management Sciences, University of Buea, Buea, Cameroon.

Kerrylee Rogers (K)

Faculty of Science, Medicine and Health, School of Earth, Atmospheric and Life Sciences (SEALS), Wollongong, NSW, Australia.

Ian Hendy (I)

Institute of Marine Sciences, University of Portsmouth, Portsmouth, United Kingdom.

Andrew Edwards-Jones (A)

Plymouth Marine Laboratory, Plymouth, United Kingdom.

Sergio de Miguel (S)

Department of Agricultural and Forest Sciences and Engineering, University of Lleida, Lleida, Spain; Forest Science and Technology Centre of Catalonia (CTFC), Solsona, Spain.

John A Burt (JA)

Center for Interacting Urban Networks (CITIES) and Mubadala Arabian Center for Climate and Environmental Sciences (Mubadala ACCESS), New York University Abu Dhabi, 129188, Abu Dhabi, United Arab Emirates.

Tarig Ali (T)

Department of Civil Engineering, College of Engineering, American University of Sharjah (AUS), Sharjah, United Arab Emirates.

Frida Sidik (F)

Research Centre for Oceanography, National Research and Innovation Agency, Jakarta, Indonesia.

Meshal Abdullah (M)

Ecoresolve, San Francisco, CA, United States; Department of Geography, College of Arts and Social Sciences, Sultan Qaboos University, Muscat, Oman; Department of Ecology and Conservation Biology, Texas A&M University, College Station, TX, United States.

P Pandi Selvam (P)

GAIT Global, Singapore.

Wan Shafrina Wan Mohd Jaafar (WSWM)

Ecoresolve, San Francisco, CA, United States; Earth Observation Center, Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.

Isuru Alawatte (I)

Department of Forest Conservation, Ministry of Wildlife and Forest Resources Conservation, Sri Lanka.

Willie Doaemo (W)

Department of Civil Engineering, Papua New Guinea University of Technology, Lae, Papua New Guinea.

Adrián Cardil (A)

Department of Agricultural and Forest Sciences and Engineering, University of Lleida, Lleida, Spain; Forest Science and Technology Centre of Catalonia (CTFC), Solsona, Spain; Tecnosylva, León, Spain.

Midhun Mohan (M)

Ecoresolve, San Francisco, CA, United States; Morobe Development Foundation (via United Nations Volunteering Program), Lae, Papua New Guinea; BlueForests, San Francisco, CA, United States; Department of Geography, Faculty of Social and Management Sciences, University of Buea, Buea, Cameroon; Department of Civil Engineering, College of Engineering, American University of Sharjah (AUS), Sharjah, United Arab Emirates; Department of Geography, University of California - Berkeley, Berkeley, CA, United States. Electronic address: mikey@ecoresolve.eco.

Classifications MeSH