UAV hyperspectral analysis of secondary salinization in arid oasis cotton fields: effects of FOD feature selection and SOA-RF
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View abstract on PubMed
Summary
This summary is machine-generated.Secondary salinization hinders agriculture in arid regions. This study uses UAV hyperspectral remote sensing and advanced algorithms to accurately monitor soil salinity, improving cotton yields and promoting sustainable agriculture.
Area Of Science
- Agricultural Science
- Remote Sensing
- Environmental Science
Background
- Secondary salinization is a major agricultural constraint in arid regions, exacerbated by mulching irrigation.
- Effective field-scale soil salinity monitoring is challenging under these conditions.
Purpose Of The Study
- To develop a high-precision, efficient UAV hyperspectral remote sensing method for monitoring soil salinity.
- To optimize soil salinity prediction models using advanced feature extraction and machine learning algorithms.
Main Methods
- UAV hyperspectral images were processed using Competitive adaptive reweighted sampling (CARS), Gray-Level Co-occurrence Matrix (GLCM), Boruta, and Brightness-Color-Index (BCI) with Fractional-order differentiation (FOD).
- Three modeling strategies were developed integrating spectral, textural, and triple-band indices.
- Seagull Optimization Algorithm for Random Forest (SOA-RF) was employed to predict soil electrical conductivity (EC) and spatial distribution.
Main Results
- Fractional-order differentiation (1.9th order optimal) enhanced spectral feature extraction.
- Integrating triple-band indices significantly improved model accuracy (R² = 0.9476).
- The SOA-RF model demonstrated superior accuracy and stability compared to conventional Random Forest.
Conclusions
- The proposed SOA-RF model accurately and non-invasively monitors soil salinity under drip irrigation with membrane mulching.
- This method is crucial for improving cotton cultivation, increasing yields, and supporting sustainable agricultural development in arid regions.
- The study provides a valuable reference for regional soil salinization prevention and control.
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