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Title: Development of an effective methodology for marine pollution monitoring in an industrialized urban envirnoment: (A remotesensing approach)

Abstract

The study area chosen for marine pollution monitoring was Thane Creek; near Bombay city; which essentially constitutes an industrialized urban setting. The area chosen within the Thane Creek, was between Vikhroli Creek and the Vashi Bridge in the south (approx. 75, kms.). Remote sensing technique was applied for assessing water quality parameters around Thane Creek in addition to conventional chemical analysis of samples collected during the pass of the satellite. The variation in the ranges of the water quality parameters chemically analyzed were: pH (6.67 - 7.94), Salinity (5.65 - 33.05 g/Kg), Turbidity (0.2 - 15.0 NTU), TSS (2.1 - 400 mg/L), TDS (850 - 38,500 mg/L), Temperature (24{degrees} - 30{degrees}C), and Colour (colourless-, green-, red-, or black). In the remote sensing studies. Turbidity and Temperature were quantified using Landsat TM data. An empirical approach of relating TM data to ground reference data for these parameters was employed through regression analysis. Two regression models were adapted namely Multiple Regression and Linear Regression. Comparative study between the two model techniques was carried out in order to arrive at the best possible method.

Authors:
; ;  [1]
  1. Indian Institute of Technology, Bombay (India); and others
Publication Date:
OSTI Identifier:
478156
Report Number(s):
CONF-970319-
TRN: 97:002802-0049
Resource Type:
Conference
Resource Relation:
Conference: 4. thematic international conference on remote sensing for marine and coastal environments: technology and applications, Orlando, FL (United States), 17-19 Mar 1997; Other Information: PBD: 1997; Related Information: Is Part Of Proceedings of the fourth international conference on remote sensing for marine and coastal environments. Technology and applications: Volume I; PB: 741 p.
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; STREAMS; WATER QUALITY; TURBIDITY; REMOTE SENSING; TEMPERATURE DISTRIBUTION; WATER POLLUTION; INDIA; QUANTITATIVE CHEMICAL ANALYSIS

Citation Formats

Inamdar, A B, Venkatakrishnan, N, and Nayak, B P. Development of an effective methodology for marine pollution monitoring in an industrialized urban envirnoment: (A remotesensing approach). United States: N. p., 1997. Web.
Inamdar, A B, Venkatakrishnan, N, & Nayak, B P. Development of an effective methodology for marine pollution monitoring in an industrialized urban envirnoment: (A remotesensing approach). United States.
Inamdar, A B, Venkatakrishnan, N, and Nayak, B P. 1997. "Development of an effective methodology for marine pollution monitoring in an industrialized urban envirnoment: (A remotesensing approach)". United States.
@article{osti_478156,
title = {Development of an effective methodology for marine pollution monitoring in an industrialized urban envirnoment: (A remotesensing approach)},
author = {Inamdar, A B and Venkatakrishnan, N and Nayak, B P},
abstractNote = {The study area chosen for marine pollution monitoring was Thane Creek; near Bombay city; which essentially constitutes an industrialized urban setting. The area chosen within the Thane Creek, was between Vikhroli Creek and the Vashi Bridge in the south (approx. 75, kms.). Remote sensing technique was applied for assessing water quality parameters around Thane Creek in addition to conventional chemical analysis of samples collected during the pass of the satellite. The variation in the ranges of the water quality parameters chemically analyzed were: pH (6.67 - 7.94), Salinity (5.65 - 33.05 g/Kg), Turbidity (0.2 - 15.0 NTU), TSS (2.1 - 400 mg/L), TDS (850 - 38,500 mg/L), Temperature (24{degrees} - 30{degrees}C), and Colour (colourless-, green-, red-, or black). In the remote sensing studies. Turbidity and Temperature were quantified using Landsat TM data. An empirical approach of relating TM data to ground reference data for these parameters was employed through regression analysis. Two regression models were adapted namely Multiple Regression and Linear Regression. Comparative study between the two model techniques was carried out in order to arrive at the best possible method.},
doi = {},
url = {https://www.osti.gov/biblio/478156}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jun 01 00:00:00 EDT 1997},
month = {Sun Jun 01 00:00:00 EDT 1997}
}

Conference:
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