Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 1097–1105, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-1097-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 1097–1105, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-1097-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Oct 2019

19 Oct 2019

A NOVEL WATER INDEX (SWI) FOR SALTY WATER FROM LANDSAT 8 OLI/TIRS

F. Yousefian1, M. Sahebi2, M. Shokri1, and M. Moradi1 F. Yousefian et al.
  • 1K. N. Toosi University of Technology, Mirdamad, Tehran, Iran
  • 2Remote Sensing Research Center, K. N. Toosi University of Technology, Mirdamad, Tehran, Iran

Keywords: water, salty Lake, PSO, Landsat 8, Salty Water Index (SWI), Effectiveness criteria

Abstract. Monitoring natural resources is one of the most important tasks in earth observation and remote sensing satellites. Water resources play a crucial role in the life of human on the planet. Among the water resources, salty lakes are of particular importance in biological, physical and environmental issues. In this study, a new Salty Water Index (SWI) for Landsat 8 Operational Land Imager (OLI) images is proposed based on salty lakes by particle swarm optimization (PSO), where water doesn’t combine by cloud, shadow, and salty areas. SWI is implemented on four famous and important salty lakes with the proper distribution of the whole world and different Salinity, including Lake Assal, Great Salt Lake, Eyre Lake, and Lake Urmia. The performance of SWI is compared with other water indices by overall accuracy, f-score, kappa coefficient, and standard deviation to mean ratio. Results show the efficiency of SWI on all cases due to 0.0055 Standard deviation to mean for SWI compared to 0.0395, 0.0255, 0.0873, 0.0214, 0.0524, 0.0408 and 0.0375 for NDWI, MNDWI, AWEIsh, AWEI, WRI, MOWI, and MBWI, respectively. Also, Effectiveness criteria (E) determines the efficiency of each band of Landsat 8. In this regard, results show the high performance of Green and Near IR band in all conditions and relatively proper performance of some other bands based on a special condition of each case study. The proposed method is also suggested to readers to obtain novel spectral indices of other classes and other sensors.