Assessing surface water pollution in Hanoi, Vietnam, using remote sensing and machine learning algorithms

Rapid urbanization led to significant land-use changes and posed threats to surface water bodies worldwide, especially in the Global South. Hanoi, the capital city of Vietnam, has been facing chronic surface water pollution for more than a decade. Developing a methodology to better track and analyze...

Full description

Saved in:

Bibliographic Details
Published in:	Environmental science and pollution research international Vol. 30; no. 34; pp. 82230 - 82247
Main Authors:	Do, Thi-Nhung, Nguyen, Diem-My Thi, Ghimire, Jiwnath, Vu, Kim-Chi, Do Dang, Lam-Phuong, Pham, Sy-Liem, Pham, Van-Manh
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01-07-2023 Springer Nature B.V
Subjects:	Algorithms Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Biochemical oxygen demand Chemical oxygen demand Developing countries Earth and Environmental Science Ecotoxicology Environment Environmental Chemistry Environmental Health Environmental Monitoring - methods Environmental Pollutants Environmental science Land use LDCs Learning algorithms Machine Learning Monitoring methods Observational learning Pollutants Pollution monitoring Radar Radar data Radar imaging Radar satellites Regression analysis Regression models Remote sensing Remote Sensing Technology Research Article Satellite imagery Sediments Surface water Suspended sediments Urban planning Urbanization Vietnam Waste Water Technology Water Management Water monitoring Water pollution Water Pollution Control Water Quality Water quality management Water resources Vietnam Surface water pollution Hanoi City Remote sensing Water quality parameters Machine learning
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!