研究目的
To develop a new model for surface soil moisture (SSM) retrieval from CBERS-02B satellite imagery.
研究成果
The developed SSM retrieval model for CBERS-02B achieves over 90% accuracy relative to SSMs from Landsat TM. The model shows consistent accuracy across different types of lands, with higher correlation in rocky desertification land and lower in woodland. The study concludes that the model can effectively calculate SSMs for CBERS-02B satellite imagery.
研究不足
The accuracy of SSM retrieval is affected by vegetation coverage, with lower accuracy in areas with high vegetation. The model's performance may vary with different soil types and environmental conditions.
1:Experimental Design and Method Selection:
The study analyzes the existing SSM retrieval model from Landsat TM imagery and establishes the spectral radiance relationship between Landsat TM and CBERS-02B. It adjusts the model by considering the differences in response frequency and sensitivity between the two satellite sensors.
2:2B. It adjusts the model by considering the differences in response frequency and sensitivity between the two satellite sensors.
Sample Selection and Data Sources:
2. Sample Selection and Data Sources: Two test areas in China are chosen for verification. Landsat TM and CBERS-02B images are used, with preprocessing including noise removal, atmospheric correction, and geometric registration.
3:List of Experimental Equipment and Materials:
ENVI 5.0 software for image preprocessing, Landsat TM and CBERS-02B satellite images.
4:0 software for image preprocessing, Landsat TM and CBERS-02B satellite images.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The SSM retrieval model is applied to the preprocessed images, and the results are compared with SSMs retrieved from Landsat TM imagery.
5:Data Analysis Methods:
The accuracy of the proposed model is evaluated using correlation coefficient, RMSE, and bias relative to the SSMs retrieved from Landsat TM images.
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