Cloud Detection for High-Resolution Satellite Imagery Using Machine Learning and Multi-Feature Fusion
Problem
Accurately locating clouds in high-resolution satellite imagery, a prerequisite for atmospheric correction, land cover classification and target recognition.
Why it matters
Cloud location errors degrade many downstream satellite imagery applications.
What the AI did
A machine-learning approach using multi-feature fusion, based on comparative analysis of spectral, textural and other cloud-background differences, detects clouds in satellite images.
Results
Overall accuracy >91.45%, Kappa >80%, producer accuracy 93.67%, user accuracy 95.67% on 102 GF-1/GF-2 images; better than other tested feature fusion methods.
Impact
Method achieved better accuracy than other tested feature fusion methods on the 102 tested images.
Record
| Venue | Remote Sensing |
|---|---|
| Published | 2016 |
| Work type | article |
| Authors | Ting Bai, Deren Li, Kaimin Sun, Yepei Chen, Wenzhuo Li |
| Citations | 111 (OpenAlex, at import time) |
| References | 52 |
| Model or method | machine learning with multi-feature fusion (no specific algorithm named) |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/rs8090715 |
| Open access | gold |
| Keywords | cloud detection, machine learning, multi-feature fusion, satellite imagery, remote sensing |
Importance rating
real but narrower advance
Abstract states accurate cloud location is a prerequisite for many satellite imagery applications (atmospheric correction, land cover, target recognition); enabling step, moderate breadth.
More in Climate & Environment
| # | Paper | Year | Citations | Importance |
|---|---|---|---|---|
| 1 | Learning skillful medium-range global weather forecasting | 2023 | 1,416 |
8
|
| 2 | Accurate medium-range global weather forecasting with 3D neural networks | 2023 | 1,631 |
8
|
| 3 | FuXi: a cascade machine learning forecasting system for 15-day global weather forecast | 2023 | 355 |
8
|
| 4 | Skilful nowcasting of extreme precipitation with NowcastNet | 2023 | 451 |
8
|
| 5 | Forecasting Renewable Energy Generation with Machine Learning and Deep Learning: Current Advances and Future Prospects | 2023 | 378 |
8
|