Reservoir water temperature modeling by geostatistical analysis of ASTER images (Case Study: Dez Dam, Iran)

Document Type: Original Article


1 Department of Geomatic Engineering, Shahid Rajaee Teacher Training University

2 Department of RS-GIS, Faculty of Geographic Sciences, Kharazmi University

3 Department of Environmental Sciences, Shahid Rajaee Teacher Training University

4 Faculty of Geo-Information Science and Earth Observation, University of Twente


Satellite data have been used for temperature modeling both in urban areas and water. This paper
studies viability of ASTER satellite images that provide high spatial and spectral resolution to model water
surface temperature, as a fundamental water quality parameter. This study is focused on Dez dam reservoir
residing in Khuzestan province, south west of Iran. After the image corrections required for the ASTER
image, the NDWI was determined. Water pixels extraction was done using the NDWI equal to 0.88. Using
multiple linear regression analysis (MLR), water temperature model was retrieved by a recursive approach.
The suggested model estimates the water surface temperature measured at ground control stations data.
A high R-square of 0.87 was observed between the control station data and modeled temperature. After
validation test of the temperature model at ground control station, the validity of the interpolated data in long
distance was assessed. The spatial auto-correlation (Moran-I) and clustering analysis (Hot Spot) of the result
also show that while long distance interpolation in the inner area of the dam reservoir seems acceptable,
different interpolations are required at shores of the dam reservoir and at river outlets to model water surface
temperature of the dam reservoir.


Abrams M., Hook S. and Ramachandran B. (2003). ASTER User Handbook, JPL Publication, USA.
Brivio, P. A., Giardino, C. and Zilioli E. (2001). Validation of satellie data for quality auurance in lake monitoring applications. The Science of the Total Environment, 268: 3-18.
Calzada, S.,Bricaud, A. and Gentili, B.(2008). Estimates of sea surface nitrate concentrations from sea surface temperature and chlorophyll concentration in upwelling areas: A case study for the Benguala System, Remote Sensing of Environment, 112: 3173-3180.
Chapman, D. 1992. Water Quality Assessments, Chapman and Hall, London, UK.
Chavula, G., Brezonik, P., Thenkabail, P., Jonson, T and Bauer, M. (2009). Estimating the surface temperature of lake Malawi using AVHRR and MODIS satellite imagery. Journal of Physics and Chemistry of Earth, 34: 749-754.
Ganaie, H. A., Hashia, H. and Kalota, D. (2013). Delineation of water prone area using normalized diffwrence water index (NDWI) and transect method. International Journal of Remote Sensing Applications, 3(2): 53-58.
Hellweger, F. L., Schlosser, P., Lall, U. and Weissel, J. K. (2004).Use of satellite imagery for water quality studies in New York Harbor. Estuarine, Coastal and Shelf Science, 61: 437-448.
Kishino, M., Tanaka, A. and Ishizaka, J. (2005).Retrieval of Chlorophyll-A, suspended solids and colored dissolved organic matter in Tokyo bay using ASTER data. Remote Sensing of Environment, 99(1): 66-74.
Lillesand T., Kiefer R. and Chipman J. (2007). Remote Sensing and Image Interpretation. John Wiley & Sons, New York, USA.
Matejicek, L. ,Engst, P., Janour, Z. and Benesova, L.(2006).A GIS-based approach to spatio-temporal analysis of environmental pollution in urban areas. Ecological Modeling, 199(3): 261-277.
Matsuoka, Y., Kawamura, H., Sakaida, F. and Hosoda, K.(2011). Retrieval of high-resolution sea surface temperature data for Sendai-Bay Japan using the Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER), Remote Sensing of Environment, 115: 205-213.
Oesch, D. C., Jaquet, J. M., Klaus, R. and Schenker, P. (2008). Multi-scale thermal pattern monitoring of a large lake using a muoti-sensor approach. International Journal of Remote Sensing, 29(20): 5785-5808.
Perlman, H. 2013. Water Properties. USGS Water Science School; (accessed on 17 July 2015).
Purkis, S. and Klemas, V. (2011). Remote Sensing and Global Environmental Change. John Wiley & Sons, New York, USA.
Ritchie, J., Zimba, P. and Everitt, H. (2003). Remote sensing techniques to assess water quality, Photogrammetric Engineering and Remote Sensing, 69(6): 695-704.
Sarangi, R., (2011). Remote sensing-based estimation of surface Nitrate and its variability in the southern Peninsular Indian Water., International Journal of Oceanography, 2011: 20-36.
Tarantino, E. (2012). Monitoring spatial and temporal distribution of sea surface temperature with TIR sensor data. Italian Journal of Remote Sensing, 44(1): 97-107.
Wooster, M., Patterson, G., Loftie, R. and Sear, C. (2001). Derivation and validation of the seasonal thermal structure of the lake Malawi using multi-satellite AVHRR observations. International Journal of Remote Sensing, 22: 2593-2972.