Monitoring inland water via Sentinel satellite constellation: A review and perspective
Abstract Clean Water and Sanitation, the sixth goal of Sustainable Development Goals
(SDGs 6) is a call for action by the United Nations aiming at balancing the water cycle for …
(SDGs 6) is a call for action by the United Nations aiming at balancing the water cycle for …
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 …
challenges in aquatic remote sensing, often hindering the quantitative retrieval of …
Meta-Analysis of Satellite Observations for United Nations Sustainable Development Goals: Exploring the Potential of Machine Learning for Water Quality Monitoring
SS Mukonza, JL Chiang - Environments, 2023 - mdpi.com
This review paper adopts bibliometric and meta-analysis approaches to explore the
application of supervised machine learning regression models in satellite-based water …
application of supervised machine learning regression models in satellite-based water …
An ensemble machine learning model for water quality estimation in coastal area based on remote sensing imagery
The accurate estimation of coastal water quality parameters (WQPs) is crucial for decision-
makers to manage water resources. Although various machine learning (ML) models have …
makers to manage water resources. Although various machine learning (ML) models have …
Improving satellite retrieval of oceanic particulate organic carbon concentrations using machine learning methods
Particulate organic carbon (POC) plays vital roles in marine carbon cycle, serving as a part
of “biological pump” moving carbon to the deep ocean. The blue-to-green band ratio …
of “biological pump” moving carbon to the deep ocean. The blue-to-green band ratio …
Drone-borne sensing of major and accessory pigments in algae using deep learning modeling
Intensive algal blooms increasingly degrade the inland water quality. Hence, this study
aimed to analyze the algal phenomena quantitatively and qualitatively using synoptic …
aimed to analyze the algal phenomena quantitatively and qualitatively using synoptic …
Random forest: An optimal chlorophyll-a algorithm for optically complex inland water suffering atmospheric correction uncertainties
A robust and reliable chlorophyll-a (Chla) concentration algorithm is still lacking for optically
complex waters due to the lack of understanding of the bio-optical process. Machine …
complex waters due to the lack of understanding of the bio-optical process. Machine …
Determining the primary sources of uncertainty in retrieval of marine remote sensing reflectance from satellite ocean color sensors
A Gilerson, E Herrera-Estrella, R Foster… - Frontiers in Remote …, 2022 - frontiersin.org
Uncertainties in the retrieval of the remote sensing reflectance, Rrs, from Ocean Color (OC)
satellite sensors have a strong impact on the performance of algorithms for the estimation of …
satellite sensors have a strong impact on the performance of algorithms for the estimation of …
Evaluation of Ocean Color Atmospheric Correction Methods for Sentinel-3 OLCI Using Global Automatic In Situ Observations
The Ocean and Land Color Instrument (OLCI) on Sentinel-3 is one of the most advanced
ocean color satellite sensors for aquatic environment monitoring. However, limited studies …
ocean color satellite sensors for aquatic environment monitoring. However, limited studies …
Machine Learning Based Long‐Term Water Quality in the Turbid Pearl River Estuary, China
Total suspended solid (TSS) and chlorophyll‐a (Chl‐a) are critical indicators of water quality.
Moderate‐resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite provides a …
Moderate‐resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite provides a …