Empirical estimation of suspended solids concentration in the Indus Delta Region using Landsat-7 ETM+ imagery

J Environ Manage. 2018 Mar 1:209:254-261. doi: 10.1016/j.jenvman.2017.12.070. Epub 2018 Jan 4.

Abstract

Suspended Solids Concentration (SSC) in water is related to its quality and transparency. Satellite remote sensing has proven to be an efficient means of monitoring water quality in large deltas because in situ sampling methods are costly, laborious, time consuming, and spatially constrained. In this study, the potential of Landsat's Enhanced Thematic Mapper Plus (ETM+) sensor was explored to develop a model for remote sensing-based quantification of SSC within the large, turbid Indus Delta Region (IDR, south of Pakistan). Six scenes were atmospherically corrected using the Dark Object Subtraction (DOS) method, to formulate a model for monitoring water quality of the IDR. An empirical model was developed and validated using in situ SSC measurements (9.4-761.4 mg/L) from several data collection campaigns coinciding (within an 11-day window) with satellite overpasses. It was found that using Band 1 (blue: 450-520 nm), Band 2 (green: 520-600 nm), Band 3 (red: 630-690 nm), and Band 5 (shortwave infrared: 1550-1750 nm) of Landsat-7 ETM + along with the Normalized Difference Suspended Sediment Index (NDSSI) can help in precise and accurate estimation of SSC, resulting in a relatively small Root Mean Square Error of 67.24 mg/L, Mean Absolute Error of 54.75 mg/L, and coefficient of determination of 0.88. Further, it was also evident that residuals do not increase with an increasing time window (0-11 days) between the satellite overpass and in situ data collection. Therefore, the established algorithm can potentially be used for frequent (after 8 days) synoptic mapping of SSC in the IDR and other similar estuarine environments.

Keywords: Estuarine system; Indus Delta Region; Landsat-7 ETM+; Normalized difference suspended sediment index; Remote sensing; Suspended solids; Water quality.

MeSH terms

  • Environmental Monitoring*
  • Pakistan
  • Satellite Imagery
  • Water Quality*