A review of spectral indices for mangrove remote sensing

TV Tran, R Reef, X Zhu - Remote Sensing, 2022 - mdpi.com
Mangrove ecosystems provide critical goods and ecosystem services to coastal
communities and contribute to climate change mitigation. Over four decades, remote …

Land use/land cover in view of earth observation: Data sources, input dimensions, and classifiers—A review of the state of the art

PC Pandey, N Koutsias, GP Petropoulos… - Geocarto …, 2021 - Taylor & Francis
Land use/land cover (LULC) is a fundamental concept of the Earth's system intimately
connected to many phases of the human and physical environment. Earth observation (EO) …

[HTML][HTML] Advances in Earth observation and machine learning for quantifying blue carbon

TD Pham, NT Ha, N Saintilan, A Skidmore… - Earth-Science …, 2023 - Elsevier
Blue carbon ecosystems (mangroves, seagrasses and saltmarshes) are highly productive
coastal habitats, and are considered some of the most carbon-dense ecosystems on the …

Comparison of machine learning methods for estimating mangrove above-ground biomass using multiple source remote sensing data in the red river delta biosphere …

TD Pham, N Yokoya, J Xia, NT Ha, NN Le… - Remote Sensing, 2020 - mdpi.com
This study proposes a hybrid intelligence approach based on an extreme gradient boosting
regression and genetic algorithm, namely, the XGBR-GA model, incorporating Sentinel-2 …

Advances in multi-and hyperspectral remote sensing of mangrove species: A synthesis and study case on airborne and multisource spaceborne imagery

G Lassalle, MP Ferreira, LEC La Rosa… - ISPRS Journal of …, 2023 - Elsevier
This study summarizes the advances in mangrove species mapping based on multispectral
and hyperspectral imagery achieved over the last decade. The influence of species diversity …

A review of carbon monitoring in wet carbon systems using remote sensing

AD Campbell, T Fatoyinbo, SP Charles… - Environmental …, 2022 - iopscience.iop.org
Carbon monitoring is critical for the reporting and verification of carbon stocks and change.
Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and …

Species-level classification and mapping of a mangrove forest using random forest—utilisation of AVIRIS-NG and sentinel data

MD Behera, S Barnwal, S Paramanik, P Das… - Remote Sensing, 2021 - mdpi.com
Although studies on species-level classification and mapping using multisource data and
machine learning approaches are plenty, the use of data with ideal placement of central …

Aboveground biomass estimates of tropical mangrove forest using Sentinel-1 SAR coherence data-The superiority of deep learning over a semi-empirical model

SM Ghosh, MD Behera - Computers & Geosciences, 2021 - Elsevier
The availability of advanced Machine Learning algorithms has made the estimation process
of biophysical parameters more efficient. However, the efficiency of those methods seldom …

A survey of computer vision techniques for forest characterization and carbon monitoring tasks

S Illarionova, D Shadrin, P Tregubova, V Ignatiev… - Remote Sensing, 2022 - mdpi.com
Estimation of terrestrial carbon balance is one of the key tasks in the understanding and
prognosis of climate change impacts and the development of tools and policies according to …

Development of forest aboveground biomass estimation, its problems and future solutions: A review

T Ma, C Zhang, L Ji, Z Zuo, M Beckline, Y Hu, X Li… - Ecological …, 2024 - Elsevier
Forest aboveground biomass (AGB) is crucial as it serves as a fundamental indicator of the
productivity, biodiversity, and carbon storage of forest ecosystems. This paper presents a …