Assessment of Water Clarity within Dokan Lake Using Remote Sensing Techniques | ||
Journal of Engineering | ||
Article 1, Volume 23, Issue 8, August 2017, Pages 13-28 | ||
Authors | ||
Hasti Shwan Abdullah; Mahmoud Saheh Al-Khafaji; Hekmat M. Ibrahim | ||
Abstract | ||
It is impractical to monitor lakes water quality by conventional field methods because of expense and time consuming. Satellite image is more convenient to be used to collect the required data for monitoring and assessing lakes water quality. This study aims to develop a water clarity estimation model based on remote sensing and GIS techniques to estimate and assess the water clarity within Dokan Lake in Kurdistan Region of Iraq. Twenty points in the lake were selected and studied at autumn and spring seasons. For assessing water clarity, the Secchi Disk Transparency (SDT) and the Trophic State Index (TSI) were used at these twenty stations in the lake. Multiple linear regressions are used to obtain mathematical models for estimating the water clarity depending on spectral reflectance of Landsat 8 OLI. In this study, the new band (coastal blue) of Landsat 8 OLI has been undertaken in developing of the monitoring models. Moreover, new Independent Component Analysis (ICA) and new 7 band ratios with 16 band combinations have been investigated. The obtained highest determination coefficient values for SDT and TSI were 0.98 and 0.87 for autumn season and 0.95 and 0.97 for spring season respectively. Generally, for spring season, the performance of all models is reduced due to seasonal change, variance of parameters and other factors. The developed models were used to map the water clarity distribution within Dokan Lake. The results of the developed SDT and TSI models showed that the correlation of all bands of Landsat 8 OLI is appropriate to monitor the water clarity. These models can be effectively used to monitor the water clarity within the lake with conservation of time efforts and cost. | ||
Keywords | ||
Clarity; Trophic State Index; Secchi Disk Transparency; Image Processing; Landsat; GIS | ||
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