The feasibility of using Landsat OLI images for water turbidity estimation in Gandoman wetland, Iran
Subject Areas : Journal of Radar and Optical Remote Sensing and GIS
Ghazal lotfi
1
(
Department of environmental sciences, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
)
mozhgan Ahmadi Nadoushan
2
(
Department of environmental sciences, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
)
Mohammadhadi Abolhasani
3
(
Department of environmental sciences, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
)
Keywords: Monitoring, pollution, Water resources, Linear regression, Landsat 8 OLI,
Abstract :
Change detection of wetlands is one of the essential requirements for the management and assessment of wetlands. Monitoring water quality is a crucial issue for assessing the environmental consequences of human interventions in wetland ecosystems. The present study aims at studying the capability of satellite images in assessing the water turbidity and comparing their capability with that of ground sampling. Four stations in four directions were chosen in Gandoman wetland, located in Chaharmahal and Bakhtiari Province. Samples were taken three times in the wetland with the intervals of 30 days from September to December 2017. The turbidity index was calculated and the relationship between the data obtained from ground-based measurement and from satellite images was studied using linear regression analysis and correlation coefficient. The comparison between the amounts of turbidity observed in different stations in different months revealed that the turbidity value was at its highest point (214.49 NTU) in station number three in September, and its lowest point (2.25 NTU) in station number four in October and, therefore, there was a significant difference between the values (p<0.05). The results were also indicative of a significant correlation between the measured amounts of turbidity and the reflectance values of blue and red bands in the satellite images. Remote sensing techniques can overcome the limitations of traditional methods and be used as appropriate substitutes in monitoring the quality of water.
