A remote sensing based framework for predicting water quality of different source waters

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 38, Issue , 2010, Pages

  Akbar, T A ^a   Hassan, Q K ^a   Achari, G ^a  

^a UNIVERSITY OF CALGARY   (Canada)

Author keywords

Remote sensing; Spatial modelling; Spectral bands; Water quality monitoring

Indexed keywords

SATELLITES; SURVEYING; WATER POLLUTION; WATER QUALITY;

POLLUTION LEVEL; REMOTE SENSING TECHNIQUES; SPATIAL MODELLING; SPECTRAL BAND; TOTAL PHOSPHORUS; WATER QUALITY DATA; WATER QUALITY MONITORING; WATER QUALITY VARIABLES;

REMOTE SENSING;

EID: 84923658966     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (34)

1. Alparslan, E., Aydöner, C., Tufekci, V., and Tü fekci, H., 2007. Water quality assessment at Ömerli Dam using remote sensing techniques. Environ. Monit. Assess., 135, pp. 391-398.
2. Baban, S. J., 1993. Detecting water quality parameters in the Norfolk Broads, UK, using Landsat imagery. Int. J. Remot Sens. , 14, 1247-1267.
3. Baruah, P.J., Tamura, M., Oki, K., and Nishimura, H., 2002. Neural network modeling of surface chlorophyll and sediment content in inland water from Landsat Thematic Mapper imagery using multidate spectrometer data. In: Gilbert, G.D., Frouin, R.J. (Eds.), Ocean Optics: Remote Sensing and Un derwater Imagery. Proc. SPIE Int. Soc. Opt. Eng. 4488, Seattle, pp. 205-212.
4. Brivio, P.A., Giardino, C., and Zilioli, E., 2001. Determination of chlorophyll concentration changes in Lake Garda using an image-b ased radiative transfer code for Landsat TM images. Int. J. Remote Sens., 22, 487-502.
5. Chen, C., Tang, C., Pan, Z., Zhan, H., Larson, M., and Jonsson, L., 2007, Remotely sensed assessment of w ater quality levels in the Pearl River Estuary, China. , Mar. Pollut. Bull., 54, pp. 1267-1272.
6. Cox, R.M., Forsythe, R.D.V and Olmsted, L.L., 1998. Assessing water quality in Catawba river reservoirs using landsat thematic mapper satellite data. Lake Reservior Manage., 14, pp. 405-416.
7. Dekker, A.G., Vos, R.J., and Peters, S.W.M., 2001. Comparison of remote sensing data, model results and in situ data for total suspended matter (TSM) in the southern Frisian lakes. Sci. Total Environ., 268, 197-214.
8. Dekker, A.G., Vos, R.J., Peters, and S.W.M., 2002. Analytical algorithms for lake water TSM e stimation for retrospective analysis of TM and SPOT sensor data. Int. J. Remote Sens., 23, 15-35.
9. Demographic Quarterlies, 2009. Quarterly Demographic Statistics (Alberta Population Reports). http://www.fina nce.alberta.ca/aboutalberta/demographic-quarte rlies.html (accessed 10 Apr. 2010).
10. Dogan E, Sengorur B, Koklu R, 2009. Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural ne twork technique. J. Environ. Manage., 90, 1229-1235.
11. Fraser, R.N., 1998. Multispectral remote sensing of turbidity among Nebraska Sand Hills lakes. Int. J. Remote Sens., 19, 3011-3016.
12. Gao F.,Masek J.,Schwaller M.,Hall F. 2006 On the Blending of the Landsat and MODIS Surface Reflectance: Predicting Daily Landsat Surface Reflectance. IEEE Trans Geosci. Remote Sens. 44 2207-2218.
13. Giardino, C., Pepe, M., Brivio, P.A., Ghezzi, P., and Zilioli, E., 2001. Detecting chlorophyll, Secchi disk depth and surface temperature in a sub-Alpine lake using Landsat imagery. Sci. Total Environ., 268, 19-29.
14. Hassan, Q.K., Kamal, M.M., and Hossain, A. 1998. Implementation of algorithms of geocoding and SST estimation using AVHRR data in the EASI/PACE PCI Image Processing Software over Bay of Bengal. J. NOAMI, v. 15, no. 2, pp. 63-72.
15. Hassan Q.K.,Bourque C.P.-A.,Meng F.-R.,Cox, R.M 2007 A wetness index using terrain-corrected surface temperature and normalized difference vegetation index: an evaluation of its use in a humid forest-dominated region of eastern Canada. Sensors v. 7 2028-2048.
16. Han, H., and Jordan, K.J., 2004. Estimating and mapping chlorophyll-A concentration in Pensacola Bay, Florida using Landsat ETM+ data. Int. J. Remote Sens., 26, 5245-5254.
17. Hellweger, F.L., Schlossera, P., Lalla, U., and Weissel, J.K., 2004. Use of satellite imagery for water quality studies in New York Harbor. Estuar. Coast. Shelf Sci., 61, 437-448.
18. Khorram, S., Cheshire, H., Geraci, A.L., and Rosa, G.L., 1991. Water quality mapping of Augusta Bay, Italy from Landsat-TM data. Int. J. Remote Sensing,, 12, 803-808.
19. Kloiber, S.M., Brezonik, P.L., and Bauer, M.E., 2002a . A procedure for regional lake water clarity assessment using Landsat multispectral data. Remote Sen. Environ., 82, 38-47.
20. Kloiber, S.M., Brezonik, P.L., and Bauer, M.E., 2002b . Application of Landsat imagery to regional-scale assessments of lake clarity. Water Res., 36, 4330-4340.
21. Koponen, S., Pulliainen, J., Kallio, K., and Hallikainen, M., 2002, Lake water quality classification with airborne hyperspectral spectr ometer and simulated MERIS data. Remote Sen. Environ, 79, 51-59.
22. Lathrop, R.G., 1992. Landsat Thematic Mapper monitoring of turbid inland water quality. Photogramm. Eng. Remote Sens., 58, 465-470.
23. Lathrop, R.P. and Lillesand, T.M., 1986. Use of Thematic Mapper data to assess water quality in Green Bay and Lake Michigan. Photogramm. Eng. Remote Sens., 52, 671-680.
24. Lillesand, T.M., Johnson, W.L., Deuell, R.L., Lindstrom, O.M., and Meisner, D.E., 1983. Use of Landsat data to predict the trophic state of Minnesota lakes. Photogramm. Eng. Remote Sens, 49, 219-229.
25. Mancino, G., Nolé A., Urbano V., Amato M., and Ferrara A., 2009, Assessing water quality by remote sensing in small lakes: the case study of Monticchio lakes in southern Italy. iForest, 2, pp. 154-161.
26. Mayo, M., Gitelson, A., Yacobi, Y.Z., and ben-Avraham, Z., 1995. Chlorophyll distribution in Lake Kinneret determined from Landsat Thematic Mapper data. Int. J. Remote Sens. 16, 175-182.
27. Onderka and P. Pekarova, 2008. Retrieval of suspended particulate matter concentrations in the Danube River from Landsat ETM data, Sci. Total Environ. 397 (1-3) (2008), pp. 238-243.
28. Östlund, C., Flink, P., Strombeck, N., Pierson, D. , and Lindell, T., 2001, Mapping of the water quality of lake Erken, Sweden, from imaging spectrometry and landsat thematic mapper. Sci. Total Environ., 268, pp. 139-154.
29. Panda, U.M., Sundaray, K.S., Rath, P., Nayak, B.B., Bhatta, D., 2006. Application of factor and cluster analysis for characterization of river and estuarine water systems-A case study: Mahanadi River (India). J. Hydrol., 331, 434-445.
30. Swanson, H., Zurawell, R., Steele Lake Water Quality Monitoring Report, 2006. Monitoring and Evaluation Branch, Environmental Assurance Division, Alberta Environment, Edmonton, Alberta.
31. Statistics Canada, 2005. About Alberta. http://www40.statcan.gc.ca/l01/cst01/phys01-eng.htm?sdi=area (accessed 10 Apr.2010).
32. Vignolo, A, Pochettinoa, A., Ciceronea, D., 2006, Water quality assessment using remote sensing techni ques: Medrano Creek, Argentina, J. Environ. Manage., 81, pp. 429-433.
33. Wang, F., Han, L., Kung, T., and Van Arsdale, R.B., 2006, Applications of Landsat-5 TM imagery in assessing and mapping water qual ity in Reelfoot Lake, Tennessee. Int. J. Remote Sens., 27, pp. 5269-5283.
34. Wu, M., Zhang, W., Wang, X., and Luo, D., 2009, Application of MODIS satellite data in monitoring water quality parameter s of Chaohu Lake in China. Environ Monit. Assess., 148, pp. 255-264.