ID:
technologies-24
Name:
Muddy Water Mapping Tool
Technology:
Machine Learning (Random Forest)
Type:
Semantic segmentation
Data used as input:
Sentinel-2 imagery
Produced datasets (openly available):
Muddy water maps
Demo (video if available):
No
Paper (if available):
Towards a Paradigm Shift on Mapping Muddy Waters with Sentinel-2 Using Machine Learning
Paper DOI (if available):
10.3390/su151813441
Project ID (if available):
101004157
Project Acronym (if available):
WQeMS
Service description:
Mapping the presence, frequency, and spatial extent of muddy water in inland drinking water reservoirs.
