研究目的
To characterize an extreme algal bloom event in a reservoir using LANDSAT 8-OLI sensor and in situ sampling, and to build semiempirical models for chlorophyll-a concentration estimation.
研究成果
The combined use of satellite and in situ chlorophyll-a data improves phytoplankton bloom delimitation, enhancing the understanding of spatial patterns associated with natural and anthropogenic interventions. Both models lead to comparable trophic class assessment, mostly hypertrophic. However, improvements are needed for low chlorophyll-a concentration estimation and temporal studies.
研究不足
Both models fail to predict chlorophyll-a concentration near river intrusion (North), where low reflectance values are recorded. Further studies are needed to improve the models for low chlorophyll-a concentration estimation and to perform temporal studies.
1：Experimental Design and Method Selection:
The study combines remote sensing data from LANDSAT 8-OLI with in situ sampling to analyze an algal bloom event. Semiempirical models are developed to estimate chlorophyll-a concentration from satellite data.
2：Sample Selection and Data Sources:
Eight sampling sites in San Roque Reservoir were selected for in situ measurements and satellite imagery analysis.
3：List of Experimental Equipment and Materials:
LANDSAT 8-OLI sensor for satellite imagery, Secchi disk for water clarity measurement, and laboratory equipment for chlorophyll-a and algae abundance measurement.
4：Experimental Procedures and Operational Workflow:
In situ parameters including Secchi depth and coordinates were measured, water samples were collected for chlorophyll-a and algae abundance measurement. Satellite imagery was processed to obtain surface reflectance data.
5：Data Analysis Methods:
Correlation between in situ chlorophyll-a measurements and satellite reflectance data was performed using Rstudio. Semiempirical models were developed using linear regression.
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