Water quality mapping using multi-date images from digital camera



Conclusion
A digital image captured by conventional digital camera can be used to generate water quality mapping. This technique will reduce the cost in acquiring the airborne imaging. The problem of cloud cover can also be avoided because the light aircraft, from where the image is being captured, normally flies below the cloud levels. A digital camera that can capture digital images will provide multi-band data by separating the colour images into individual components. The proposed image correction techniques produced encouraging results with high value of correlation coefficient.

A new multi-spectral algorithm has been developed for mapping the total suspended solid by using the digital images capture from the light aircraft. Multi-date sea-truth data also can be used to validate the algorithm.


Figure 7. Contour map of TSS for the study area. (Orange, TSS=150-200 mg/l; red, TSS= 201-250 mg/l; white,TSS>250 mg/l.)

References
  1. Alle, R.J., and Johnson, J.E., 1999, Use of satellite imagery to estimate surface chlorophyll-a and Secchi disc depth of Bull Shoals, Arkansas, USA. International Journal of Remote Sensing, 20, 1057-1072.

  2. Baban, S.M., 1993, Detecting water quality parameters in the Norfolk Broads, U. K., using Landsat imagery. International Journal of Remote Sensing, 14, 1247-1267.

  3. Dekker, A.G., and Peters, S.W.M., 1993, The use of Thematic Mapper for the analysis of eutrophic lakes: a case study in the Netherlands. International Journal of Remote Sensing, 14, 799-821.

  4. Ekstrand, S., 1992, Landsat TM based quantification of chlorophyll-a during algae blooms in coastal waters. International Journal of Remote Sensing, 13, 1913-1926.

  5. Forster, B.C., Xingwei, I.S., and Baide, X., 1993, Remote sensing of water quality parameters using landsat TM. International Journal of Remote Sensing, 14, 2759-2771.

  6. Gallegos, C. L., and Correl, D. L., 1990, Modeling spectral diffuse attenuation, absorption and scattering coefficients in a turbid estuary. Limnology and Oceanography, 35, 1486-1502.

  7. Gallie, E. A., and Murtha, P. A., 1992, Specific absorption and backscattering spectra for suspended minerals and chlorophyll-a in Chilko Lake, British Columbia. Remote Sensing of Environment, 39, 103-118.

  8. Keiner, L. E., and Xiao, H. Y, 1998, A neural network model for estimating sea surface chlorophyll and sediments from thematic mapper imagery. Remoter Sensing of Environment, 66, 153-165.

  9. Kirk, J. T. O., 1984, Dependence of relationship between inherent and apparent optical properties of water on solar altitude. Limnology and Oceanography, 29, 350-356.

  10. Koponen, S., Pulliainen, J., Kallio, K., and Hallikainen, M., 2002, Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data. Remote Sensing of Environment, 79, 51-59.

  11. Ritchie, C. J., Cooper, C. M., and Yong, Q. J., 1987, Using Landsat Multispectral Scanner data to estimate suspended sediments in Moon Lake, Missisippi. Remote Sensing of Environment, 23, 65-81.
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