Open AccessLandsat-7 ETM+ Based Remote Sensing as a Tool for Assessing Lakes Water Quality Characteristics
Author(s) -
Diego Fernando Cabezas-Alzate,
Yeison Alberto Garcés-Gómez,
Vladimir Henao Céspedes
Publication year - 2021
Publication title -
xi'nan jiaotong daxue xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 21
ISSN - 0258-2724
DOI - 10.35741/issn.0258-2724.56.1.28
Subject(s) - turbidity , multispectral image , remote sensing , water quality , environmental science , mean squared error , hydrology (agriculture) , mathematics , statistics , geology , ecology , oceanography , geotechnical engineering , biology
The article describes a new method using remote sensing techniques to set the mathematical models that allow the estimation of the most relevant parameters for water quality monitored in Laguna de Sonso lake, Valle del Cauca, determined using Landsat-7 ETM+ multispectral images. Chlorophyll-a (Chl-a), Turbidity, Dissolved Oxygen (DO), and Total Phosphorus (P) are the parameters chosen for this study. The annual dry and wet seasons were defined, from 2010 to 2017, with a total of 70 images. It was necessary to carry out a process of masking the water Buchón (Eichhornia crassipes) and replacing pixels using the statistical average of the two established annual seasons. For the case of Chl-a, the NDI ratio between the red and near-infrared (NIR) bands was the best correlated with an ; for turbidity, a regression with the red band, with an ; for DO, the ratio with the highest correlation was a simple ratio (SR) between the green and blue bands, with an ; and for P, a regression of the NIR band was enough, presenting an . Finally, the adjusted mathematical models were obtained for each established parameter, allowing the estimation of each parameter to monitor the lagoon water quality using images from the ETM+ sensor.