Detecting Algal Bloom in Coastal Waters of Gopalpur, Odisha, Using Sentinel-2B NDCI and GIS Remote Sensing Technology

1. Brief: Algal blooms, often caused by excessive nutrient enrichment, pose a significant threat to coastal ecosystems and human activities. Coastal areas of Gopalpur, Odisha, are susceptible to algal blooms due to the convergence of multiple factors. This mini project aims to detect and monitor algal blooms using Sentinel-2B satellite imagery, specifically focusing on the Normalized Difference Chlorophyll Index (NDCI) and GIS remote sensing technology.

2. Objectives: The main objectives of this project are as follows:

• To assess the presence of algal blooms in coastal waters of Gopalpur, Odisha, using Sentinel-2B satellite imagery.
• To calculate the Normalized Difference Chlorophyll Index (NDCI) as an indicator of algal biomass.
• To spatially analyze and map the distribution of algal blooms using GIS technology.

3. Methodology:

3.1 Data Collection: Sentinel-2B Level-1C satellite imagery covering the coastal waters of Gopalpur, Odisha, was obtained from the European Space Agency (ESA) Copernicus Open Access Hub. Multiple cloud-free scenes spanning different time periods were selected to capture potential algal bloom events.

3.2 Preprocessing: The Sentinel-2B imagery underwent the following preprocessing steps:

• Atmospheric correction to remove atmospheric effects and enhance water quality information.
• Subset the imagery to focus on the study area around Gopalpur coastal waters.

3.3 NDCI Calculation: The Normalized Difference Chlorophyll Index (NDCI) was calculated using the following formula:

Where B3 is the blue band and B5 is the red edge band of Sentinel-2B imagery.

3.4 GIS Analysis: The NDCI values were imported into a GIS software (e.g., QGIS) for spatial analysis and mapping. The following steps were performed:

• Thresholding the NDCI values to identify areas with elevated chlorophyll content.
• Spatial overlay with coastline and other relevant data layers for context and analysis.
• Generating thematic maps displaying the distribution and intensity of algal blooms.

4. Results: The analysis revealed areas of increased NDCI values, indicating potential algal bloom occurrences. The spatial maps depicted the extent and severity of algal blooms in the coastal waters of Gopalpur, Odisha.

5. Discussion: The project successfully demonstrated the utility of Sentinel-2B imagery and NDCI in detecting and mapping algal blooms in coastal waters. The GIS analysis provided valuable insights into the spatial patterns and dynamics of algal bloom events.

6. Conclusion: The project highlighted the effectiveness of using Sentinel-2B NDCI and GIS remote sensing technology for detecting and monitoring algal blooms in the coastal waters of Gopalpur, Odisha. The findings can contribute to informed decision-making and management strategies to mitigate the impacts of algal blooms on coastal ecosystems and local communities.

7. Future Work: Future work could include:

• Long-term monitoring of algal bloom events using a time series of satellite imagery.
• Integration of additional environmental data (e.g., nutrient concentrations) for a more comprehensive analysis.
• Validation of algal bloom detection using in-situ measurements and field observations.

8. References:

• Gitelson, A. A., Gurlin, D., & Moses, W. (2009). Remote estimation of chlorophyll-a concentration in productive turbid waters: respective of variability in the suspended particulate matter content. Optics Express, 17(11), 8783-8797.

(Note: This is a mini project report provided for illustrative purposes. The actual content and details of the report may vary based on the specific study and data available.)