Advancing non-optical water quality monitoring in Lake Tana, Ethiopia: insights from machine learning and remote sensing techniques
Water quality is deteriorating in the world's freshwater bodies, and Lake Tana in Ethiopia is becoming unpleasant to biodiversity. The objective of this study is to retrieve non-optical water quality data, specifically total nitrogen (TN) and total phosphorus (TP) concentrations, in Lake Tana using...
| Main Authors: | , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Frontiers Media
2024
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/152513 |
Similar Items: Advancing non-optical water quality monitoring in Lake Tana, Ethiopia: insights from machine learning and remote sensing techniques
- Predicting optical water quality indicators from remote sensing using machine learning algorithms in tropical highlands of Ethiopia
- Daily river discharge estimates by merging satellite optical sensors and radar altimetry through artificial neural network
- Pixels to pasture: Using machine learning and multispectral remote sensing to predict biomass and nutrient quality in tropical grasslands
- From Rangelands to Cropland, Land-Use Change and its impact on soil organic carbon variables in a Peruvian Andean Highlands: A Machine Learning Modeling approach
- Estimating Leaf Area Index of Wheat Using UAV-Hyperspectral Remote Sensing and Machine Learning
- Evaluación del yogur en tres concentraciones de etanol y dos edulcorantes y sus cambios físico-químicos y sensoriales
