Water Quality Mapping of Yamuna River Stretch Passing Through Delhi State Using High Resolution Geoeye-2 Imagery

The present article utilizes high resolution Geoeye 2 imagery for mapping and monitoring pollution concentrations of 22 km stretch of river Yamuna passing through Delhi state, by developing regression models between water quality parameters (WQP’s) and the corresponding spectral reflectance values. Water samples collected from the sampling locations were analysed for 20 WQP’s and grouped into four classes namely; (WQP)organic, (WQP)inorganic, (WQP)anion and (WQP)cation. Several spectral band combinations as well as single bands were probed for performing multiple linear regression (MLR) analysis with the four WQP classes. Results reveal relatively strong positive correlations for band combination viz. [mean RGB × √B/R] with all four WQP classes yielding high R2 value (∼0.85) and RMSE (∼1.03) amongst other selected band combinations. Spatial distribution maps were generated that substantiates to the actualin-situpollution concentration levels thereby evidences the potential of high resolution Geoeye-2 imagery for monitoring and mapping pollution concentrations in the water bodies. KeYWoRDS Digital Number (DN), Multiple Linear Regression (MLR), Point and Non Point Sources, Spectral Reflectance, Water Quality Parameters (WQP’s), Yamuna River,

[1]  B. Markham,et al.  Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges , 2003, IEEE Trans. Geosci. Remote. Sens..

[2]  Martti Hallikainen,et al.  Water quality retrievals from combined Landsat TM data and ERS-2 SAR data in the Gulf of Finland , 2003, IEEE Trans. Geosci. Remote. Sens..

[3]  Jerry C. Ritchie,et al.  Comparison of measured suspended sediment concentrations with suspended sediment concentrations estimated from Landsat MSS data , 1988 .

[4]  J. A. Baig,et al.  Assessment of water quality of polluted lake using multivariate statistical techniques: a case study. , 2009, Ecotoxicology and environmental safety.

[5]  Philip A. Townsend,et al.  A MODIS approach to predicting stream water quality in Wisconsin , 2013 .

[6]  M. H. Ismail,et al.  Use of Remote Sensing and GIS in Monitoring Water Quality , 2010 .

[7]  N. Kazancı,et al.  Relationship between aquatic insects and heavy metals in an urban stream using multivariate techniques , 2010 .

[8]  A. Dekker,et al.  The use of the Thematic Mapper for the analysis of eutrophic lakes: a case study in the Netherlands. , 1993 .

[9]  Yilmaz Icaga,et al.  Fuzzy evaluation of water quality classification , 2007 .

[10]  J. B. Ellis.  Impacts of urban growth on surface water and groundwater quality : proceedings of an international symposium held during IUGG 99, the XXII General Assembly of the International Union of Geodesy and Geophysics, at Birmingham, UK 18-30 July 1999 , 1999 .

[11]  R. N. Fraser,et al.  Multispectral remote sensing of turbidity among Nebraska Sand Hills lakes , 1998 .

[12]  P. Chavez.  Image-Based Atmospheric Corrections - Revisited and Improved , 1996 .

[13]  Jisoo Hwang,et al.  Radiometric Characteristics of KOMPSAT-3 Multispectral Images Using the Spectra of Well-Known Surface Tarps , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Yunpeng Wang,et al.  Water quality change in reservoirs of Shenzhen, China: detection using LANDSAT/TM data. , 2004, The Science of the total environment.

[15]  A. Gitelson,et al.  ESTIMATION OF CHLOROPHYLL a FROM TIME SERIES MEASUREMENTS OF HIGH SPECTRAL RESOLUTION REFLECTANCE IN AN EUTROPHIC LAKE , 1998 .

[16]  J. Johnson,et al.  Use of satellite imagery to estimate surface chlorophyll a and Secchi disc depth of Bull Shoals Reservoir, Arkansas, USA , 1999 .

[17]  Dmitry Pozdnyakov,et al.  Water quality remote sensing in the visible spectrum , 1998 .

[18]  P. Lavery,et al.  Estimates of water quality in coastal waters using multi-date Landsat Thematic Mapper data , 1994 .