Analyzing the impacts of Discharges from coastal outfalls on water quality of Kuwait Bay via Landsat monitoring DOI Creative Commons

Reem M. Alrashed,

Sarah M. Hasan,

Nawaf Almutairi

et al.

Journal of Engineering Research, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 1, 2024

Language: Английский

Monitoring the Industrial waste polluted stream - Integrated analytics and machine learning for water quality index assessment DOI
Ujala Ejaz, Shujaul Mulk Khan,

Sadia Jehangir

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 450, P. 141877 - 141877

Published: March 28, 2024

Language: Английский

Citations

15
Habitat quality and degradation change analysis for the Sundarbans mangrove forest using invest habitat quality model and machine learning DOI
Ismail Mondal,

Pijush Kanti Naskar,

Saleh Alsulamy

et al.

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: July 26, 2024

Language: Английский

Citations

10
Variability of bio-optical properties of Sundarbans mangrove estuarine ecosystem using elemental analysis, Sentinel 3 OLCI imageries and Neural Network models DOI
Ismail Mondal,

Isha Jha,

Arafat Hossain

et al.

Advances in Space Research, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 1, 2024

Language: Английский

Citations

7
Mitigating Coastal Flood Risks in the Sundarbans: A Combined InVEST and Machine Learning Approach DOI
Ismail Mondal, Vikas Mishra, SK Ariful Hossain

et al.

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2025, Volume and Issue: 138, P. 103855 - 103855

Published: Jan. 6, 2025

Language: Английский

Citations

0
Decoding the drivers of variability in chlorophyll-a concentrations in the Pearl River estuary: Intra-annual and inter-annual analyses of environmental influences DOI
Chunlei Ma, Jun Zhao, Zhang Guang

et al.

Environmental Research, Journal Year: 2025, Volume and Issue: 268, P. 120783 - 120783

Published: Jan. 6, 2025

Language: Английский

Citations

0
Developing a Semi-Automated Technique of Surface Water Quality Analysis Using GEE And Machine Learning: A Case Study for Sundarbans DOI Creative Commons
Sheikh Fahim Faysal Sowrav,

Sujit Kumar Debsarma,

Mohan Kumar Das

et al.

Heliyon, Journal Year: 2025, Volume and Issue: 11(3), P. e42404 - e42404

Published: Feb. 1, 2025

This study presents a semi-automated approach for assessing water quality in the Sundarbans, critical and vulnerable ecosystem, using machine learning (ML) models integrated with field remotely-sensed data. Key parameters-Sea Surface Temperature (SST), Total Suspended Solids (TSS), Turbidity, Salinity, pH-were predicted through ML algorithms interpolated Empirical Bayesian Kriging (EBK) model ArcGIS Pro. The predictive framework leverages Google Earth Engine (GEE) AutoML, utilizing deep libraries to create dynamic, adaptive that enhance prediction accuracy. Comparative analyses showed ML-based effectively captured spatial temporal variations, aligning closely measurements. integration provides more efficient alternative traditional methods, which are resource-intensive less practical large-scale, remote areas. Our findings demonstrate this technique is valuable tool continuous monitoring, particularly ecologically sensitive areas limited accessibility. also offers significant applications climate resilience policy-making, as it enables timely identification of deteriorating trends may impact biodiversity ecosystem health. However, acknowledges limitations, including variability data availability inherent uncertainties predictions dynamic systems. Overall, research contributes advancement monitoring techniques, supporting sustainable environmental management practices Sundarbans against emerging challenges.

Language: Английский

Citations

0
Quantification of chlorophyll-a in inland waters by remote sensing algorithm based on modified equivalent spectra of Sentinel-2 DOI Creative Commons
Wenbin Pan, Fei Yu, Jialin Li

et al.

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103061 - 103061

Published: Feb. 1, 2025

Language: Английский

Citations

0
An Optimal Strategy for Estimating Chlorophyll-a Concentration in Case II Waters to Support Sustainable Development Goals DOI
Shang Tian, Xiaotong Zhu, Han Zhang

et al.

Advances in Space Research, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0
Comparative analysis of k-nearest neighbors distance metrics for retrieving coastal water quality based on concurrent in situ and satellite observations DOI
Bonyad Ahmadi, Mehdi Gholamalifard, Seyed Mahmoud Ghasempouri

et al.

Marine Pollution Bulletin, Journal Year: 2025, Volume and Issue: 214, P. 117816 - 117816

Published: March 13, 2025

Language: Английский

Citations

0
Prediction of Urban Surface Water Quality Scenarios Using Water Quality Index (WQI), Multivariate Techniques, and Machine Learning (ML) Models in Water Resources, in Baitarani River Basin, Odisha: Potential Benefits and Associated Challenges DOI
Abhijeet Das

Earth Systems and Environment, Journal Year: 2025, Volume and Issue: unknown

Published: April 9, 2025

Language: Английский

Citations

0