Mapping and Analysis of Marine Pollution in Tuticorin Coastal Area Using Remote Sensing and GIS

Raj chandar Padmanaban, Rejeesh Kumar Padmanaban

Abstract


In this project, the Marine Pollution Information System has been suggested with the help of Remote Sensing and GIS. This system provides pollution hot spot area and spread rate of the Tuticorin coastal area in Tamilnadu, India. The spread rate and hot spot analysis has been analyzed with the aid of  various Chemical, Biological and Physical parameters such as pH, Temperature, Total Suspended Sediments (TSS), Salinity, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate, Nitrite, Phosphorus as Phosphate PO4, Chlorophyll-a, Silicate, primary productivity and Ammonia. The Remote Sensing data plays vital role in pollution monitoring and analysis. The Geographic Information System and Remote Sensing facilitate to scrutinize various marine pollution such Industrial pollution, sewage pollution and anthropogenic pollution. The various pollution parameters are examined with the allusion of “General Coastal Cater Quality Standard”. The preliminary investigations of pollution spots were identified on the remote sensing data (IRS P6) through the visual interpretation techniques. From the visually interpreted data the major polluted spots were identified on the ground by ground survey method. The water samples were collected from the polluted spots. The various samples had undergone with diverse laboratory analysis and readings were stored in GIS database. The various pollution parameters reading are compared with General Coastal Cater Quality Standard values in GIS environment. The various parameters Map, Hot Spot Map and Spread Rate Map are generated with the assist of Weighted Overlay Analysis and Statistical Analysis in ARC-GIS.

 


Keywords


Remote Sensing, Geographic Information System, Marine Pollution, Digital Image Processing, Field Survey, Statistical and Overlay Analysis.

Full Text: PDF

Refbacks

  • There are currently no refbacks.




Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

*2016 Journal Impact Factor was established by dividing the number of articles published in 2014 and 2015 with the number of times they are cited in 2016 based on Google Scholar, Google Search and the Microsoft Academic Search. If ‘A’ is the total number of articles published in 2014 and 2015, and ‘B’ is the number of times these articles were cited in indexed publications during 2016 then, journal impact factor = A/B. To know More: (http://en.wikipedia.org/wiki/Impact_factor)