The acidity of seawater is one of the parameters that is widely used by coastal researchers to detect anomalies so that it is feared that it will damage the order of the ecosystem on the existing coast. This study aims to map and create an algorithm for an acidity distribution model and correlate it with the growth of chlorophyll-a where this compound is a parameter used to determine the growth or large or small population of fish in water bodies on the coast. By knowing the concentration of chlorophyll-a, the existing fish population can be predicted so that fishermen can know the location to carry out capture fisheries. The method used in this study is remote sensing technology using satellite image reflectants where the reflectant value will be used as an independent variable and the acidity value and chlorophyll-a are dependent variables. The results obtained in this study are that the most optimal acidity distribution model is from the 412 nm Rrs wavelength channel from the Aqua MODIS satellite image with an R2 correlation value of 0.526 while for the relationship between acidity and the growth of chlorophyll-a concentration, a mathematical model of Chlor-a = 23.45pH + 19.712 was obtained with an R2 correlation value of 0.529. The conclusion that can be conveyed is that the concentration of chlorophyll-a is more or less correlated with the level of acidity on the coast of Pasuruan with statistical analysis at an error rate of 5%, in the future higher satellite images can be used to be able to compare the pattern of the relationship between acidity and the concentration of chlorophyll-a on the coast.