Open AccessNIR‐red algorithms‐based model for chlorophyll‐a retrieval in highly turbid Inland Densu River Basin in South‐East Ghana, West Africa
Author(s) -
Rani Meenu,
Rehman Sufia,
Sajjad Haroon,
Sidiki Alare Rahinatu,
Chaudhary B.S.,
Patairiya Shashikanta,
Rawat J.S.,
Chetri Tilok,
Patel Swagatika,
Kumar Pavan
Publication year - 2019
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2018.6145
Subject(s) - structural basin , chlorophyll a , drainage basin , algorithm , geography , oceanography , remote sensing , environmental science , geology , computer science , cartography , biology , botany , geomorphology
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.