Estimating Chlorophyll Concentration

Excessive chlorophyll concentration in water bodies, often caused by nutrient pollution, leads to harmful algal blooms that disrupt aquatic ecosystems and degrade water quality. Accurate and timely detection of chlorophyll levels is critical for effective water resource management and environmental protection.

Chlorophyll concentration in water can be estimated using remote sensing. A quantum-based support vector regression (SVR) algorithm, executable on D-Wave quantum computers via quantum annealing, can be used for finding the relationship between spectral measurements and concentration levels. This involves mapping the SVR to a QUBO problem.

This quantum SVR can achieve comparable or even better results than traditional methods for chlorophyll concentration estimation, demonstrating the potential of quantum technology in remote sensing.