Optimization of comprehensive wheat growth index system and monitoring model based on LAI
Mingguang Diao, Shuning Liang, Jianing Chen, Chuyan Zhang, Yong Liu · 2025
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Description
Diao, Liang, Chen, Zhang, and Liu build a wheat growth monitoring system in twenty twenty-five. Tracking wheat growth helps farm decisions and food security. The team combines satellite images with machine learning for this task. Their target is leaf area index, a key measure of crop canopy.
They used Sentinel-2 satellite images and field measures of leaf area. Eleven vegetation indices were ranked by how well they tracked the target. The top eight formed a combined index system. Three learning models were tested, each tuned by a swarm optimization method. A tuned gradient boosting model gave the best accuracy by a clear margin. The authors say the approach is stable and reliable for wheat monitoring.
Catalog record
| CREATOR | Mingguang Diao, Shuning Liang, Jianing Chen, Chuyan Zhang, Yong Liu |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 96 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |