NIR-red algorithms-based model for chlorophyll-a retrieval in highly turbid Inland Densu River Basin in South-East Ghana, West Africa

摘要

Chlorophyll-a concentration is a significant conditioning factor for analysing variation of water quality. It is also an important indicator for examining phytoplankton and biomass both in inland and oceanic waters. The study aims at developing an approach to quantify chlorophyll-a concentration using Landsat-8 Optical land imager sensor data in Densu River, West Africa. Twelve water samples across Densu River were collected to measure chlorophyll-a concentration. Satellite data base chlorophyll-a concentration was determined using NIR-red algorithm. The chlorophyll-a concentration obtained through this algorithm was validated with laboratory-measured chlorophyll-a concentration. Regression analysis between laboratory-measured and modelled chlorophyll-a concentration revealed strong relationship. Thus, NIR-red algorithm has proved an effective tool in measuring and mapping chlorophyll-a concentration. The algorithm can also be utilised for assessing quality of different water bodies at spatial scales.