研究目的
To optimize a composite method for the Geostationary Ocean Color Imager (GOCI) for improved vegetation profiles using optimized BRDF composite.
研究成果
The 12-day composite period was identified as optimal for BRDF modeling with GOCI, providing a balance between sensitivity to real-time vegetation changes and spatial coverage. This optimized period improves the satellite's ability to measure terrestrial products accurately.
研究不足
The study is limited by the need for at least seven cloud-free angular samplings for reliable BRDF performance, which may not always be available. Additionally, the discrepancy between field-measured NDVI and GOCI NDVI due to atmospheric correction and land cover types presents a challenge.
1：Experimental Design and Method Selection:
The study involved optimizing the BRDF composite method for GOCI by comparing modeled surface reflectance from BRDF simulation with GOCI-measured surface reflectance across different composite periods.
2：Sample Selection and Data Sources:
Field measurements were obtained using a handheld portable CROPSCAN multispectral radiometer (MSR) at two sites in Korea. GOCI imagery was used for satellite data.
3：List of Experimental Equipment and Materials:
GOCI, the first geostationary ocean color sensor, and a CROPSCAN MSR-16 multispectral radiometer were used.
4：Experimental Procedures and Operational Workflow:
Preprocessing of GOCI imagery included converting digital numbers to top-of-atmosphere reflectance, cloud masking, and atmospheric correction. BRDF modeling was performed using a semiempirical BRDF model.
5：Data Analysis Methods:
The accuracy of BRDF modeling was assessed by comparing modeled and measured surface reflectance. The sensitivity of BRDF-adjusted NDVIs to real-time vegetation changes was evaluated by comparing with field-observation NDVI.
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