A machine learning algorithm for mapping small reservoirs using Sentinel-2 satellite imagery in Google Earth Engine
This report outlines an advanced methodology for mapping small reservoirs in Northern Ghana, utilizing Sentinel-2 satellite imagery and Google Earth Engine. Aimed at enhancing mapping accuracy by reducing cloud contamination, the method filters image collections, applies optimal cloud masks, and com...
| Main Authors: | , , |
|---|---|
| Format: | Informe técnico |
| Language: | Inglés |
| Published: |
International Water Management Institute (IWMI). CGIAR Initiative on Aquatic Foods
2023
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/139360 |
Similar Items: A machine learning algorithm for mapping small reservoirs using Sentinel-2 satellite imagery in Google Earth Engine
- Google earth engine script for semi-automated mapping of small reservoirs using sentinel-2 satellite imagery
- User Manual: Google earth engine script for semi-automated mapping of small reservoirs using sentinel-2 satellite imagery
- Small reservoirs in the northern regions of Ghana and their vulnerability to drying
- Monitoring spatial-temporal variations of surface areas of small reservoirs in Ghana’s Upper East Region using Sentinel-2 satellite imagery and machine learning
- Protocol for data collection and processing from Satellite imagery using Google Earth Engine
- Advancing Soil Moisture Prediction Using Satellite and UAV-based Imagery with Machine Learning Models