[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 Earth …

[HTML][HTML] A meta-analysis on harmful algal bloom (HAB) detection and monitoring: a remote sensing perspective

RM Khan, B Salehi, M Mahdianpari… - Remote Sensing, 2021 - mdpi.com
Algae serves as a food source for a wide range of aquatic species; however, a high
concentration of inorganic nutrients under favorable conditions can result in the …

ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters

N Pahlevan, A Mangin, SV Balasubramanian… - Remote Sensing of …, 2021 - Elsevier
Atmospheric correction over inland and coastal waters is one of the major remaining
challenges in aquatic remote sensing, often hindering the quantitative retrieval of …

A machine learning approach to estimate chlorophyll-a from Landsat-8 measurements in inland lakes

Z Cao, R Ma, H Duan, N Pahlevan, J Melack… - Remote Sensing of …, 2020 - Elsevier
Abstract Landsat-8 Operational Land Imager (OLI) provides an opportunity to map
chlorophyll-a (Chla) in lake waters at spatial scales not feasible with ocean color missions …

Decision tree and random forest classification algorithms for mangrove forest map** in Sembilang National Park, Indonesia

AD Purwanto, K Wikantika, A Deliar, S Darmawan - Remote Sensing, 2022 - mdpi.com
Sembilang National Park, one of the best and largest mangrove areas in Indonesia, is very
vulnerable to disturbance by community activities. Changes in the dynamic condition of …

[HTML][HTML] Global deep learning model for delineation of optically shallow and optically deep water in Sentinel-2 imagery

G Richardson, N Foreman, A Knudby, Y Wu… - Remote Sensing of …, 2024 - Elsevier
In aquatic remote sensing, algorithms commonly used to map environmental variables rely
on assumptions regarding the optical environment. Specifically, some algorithms assume …

[HTML][HTML] Monitoring beach topography and nearshore bathymetry using spaceborne remote sensing: A review

E Salameh, F Frappart, R Almar, P Baptista… - Remote Sensing, 2019 - mdpi.com
With high anthropogenic pressure and the effects of climate change (eg, sea level rise) on
coastal regions, there is a greater need for accurate and up-to-date information about the …

A harmonized image processing workflow using Sentinel-2/MSI and Landsat-8/OLI for map** water clarity in optically variable lake systems

BP Page, LG Olmanson, DR Mishra - Remote Sensing of Environment, 2019 - Elsevier
This study demonstrates the applicability of harmonizing Sentinel-2 MultiSpectral Imager
(MSI) and Landsat-8 Operational Land Imager (OLI) satellite imagery products to enable the …

A chlorophyll-a algorithm for Landsat-8 based on mixture density networks

B Smith, N Pahlevan, J Schalles, S Ruberg… - Frontiers in Remote …, 2021 - frontiersin.org
Retrieval of aquatic biogeochemical variables, such as the near-surface concentration of
chlorophyll-a (Chl a) in inland and coastal waters via remote observations, has long been …

[HTML][HTML] An UAV and satellite multispectral data approach to monitor water quality in small reservoirs

C Cillero Castro, JA Domínguez Gómez… - Remote Sensing, 2020 - mdpi.com
A multi-sensor and multi-scale monitoring tool for the spatially explicit and periodic
monitoring of eutrophication in a small drinking water reservoir is presented. The tool was …