Document Type : Research Paper

Authors

1 Department of Natural Resources, Isfahan University of Technology

2 Associate professor, Department of Natural Resources, Isfahan University of Technology

Abstract

Land surface temperature (LST) is an essential parameter in ecological, hydrologic, climatic, and related studies. The objective of this study was to evaluate the performance of Artis and Sobrino algorithms for retrieving LST from 2009 Landsat TM thermal infrared band in Damaneh region of Isfahan province. The accuracy of LST extracted from geometrically corrected image was then assessed against field-based LST data recorded at 10 meteorological stations using linear regression analysis. The results showed that both algorithms were able to map LST spatial distribution in the region and they were significantly correlated (R>0.97), but the Artis algorithm performed slightly better than Sobrino one. This algorithm explained up to 72% of the variation in the field measurements of LST. According to this algorithm, bare lands and highly vegetated agricultural and rangeland areas had the highest (328k0) and lowest LST (291k0) in the region, respectively. As the results indicated here the decrease in vegetation cover corresponds with increase in temperature values, therefore, remotely-sensed LST information with their extensive coverage can have a key role in ecosystem management.

Keywords

[1] Amiri, R., Weng, Q., Alimohammadi, A. and Alavipanah, S. K., (2009). Spatial–temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area, Iran. Remote Sensing of Environment, 113 (12), 2606-2617.
[2] Artis, D. A. and Carnahan, W. H., (1982). Survey of emissivity variability in thermography of urban areas. Remote Sensing of Environment, 12 (4), 313-329.
[3] Becker, F., (1987). The impact of spectral emissivity on the measurement of land surface temperature from a satellite. International Journal of Remote Sensing, 8 (10), 1509-1522.
[4] Becker, F. and Li, Z. L., (1995). Surface temperature and emissivity at various scales: Definition, measurement and related problems. Remote Sensing Reviews, 12 (3-4), 225-253.
[5] Benmecheta, A., Abdellaoui, A. and Hamou, A., (2013). A comparative study of land surface temperature retrieval methods from remote sensing data. Canadian Journal of Remote Sensing, 39 (01), 59-73.
[6] Carnahan, W. H. and Larson, R. C., (1990). An analysis of an urban heat sink. Remote Sensing of Environment, 33 (1), 65-71.
[7] Caselles, V., Coll, C., Valor, E. and Rubio, E., (1995). Mapping land surface emissivity using AVHRR data application to La Mancha, Spain. Remote Sensing Reviews, 12 (3-4), 311-333.
[8] Dai, X., Guo, Z., Zhang, L. and Li, D., (2010). Spatio-temporal exploratory analysis of urban surface temperature field in Shanghai, China. Stochastic Environmental Research and Risk Assessment, 24 (2), 247-257.
[9] Dashtekian, K. and M. A. Dehghani, (2008). Land surface temperature analysis of desert area in relation with vegetation and urban development using RS and GIS, case study: Yazd-Ashkezar area. Pajouhesh & Sazandegi, 77, 169-179.
[10] Gallo, K. P. and Tarpley, J. D., (1996). The comparison of vegetation index and surface temperature composites for urban heat-island analysis. International Journal of Remote Sensing, 17 (15), 3071-3076.
[11] Gangopadhyay, P. K., Van der Meer, F., Van Dijk, P. M. and Saha, K., (2012). Use of satellite-derived emissivity to detect coalfire-related surface temperature anomalies in Jharia coalfield, India. International Journal of Remote Sensing, 33 (21), 6942-6955.
[12] Hong, S.h., Hendrickx, J. M. H. and Borchers, B., (2009). Up-scaling of SEBAL derived evapotranspiration maps from Landsat (30m) to MODIS (250m) scale. Journal of Hydrology, 370 (1–4), 122-138.
[13] Jensen, J. R., (1996). Introductory Digital Image Processing, A Remote Sensing Perspective, 2nd Edition, Upper Saddle River, New Jersey: Prentice Hall Press.
[14] Kant, Y. and Badarinath, K. V. S., (2002). Ground-based method for measuring thermal infrared effective emissivities: Implications and perspectives on the measurement of land surface temperature from satellite data. International Journal of Remote Sensing, 23 (11), 2179-2191.
[15] Kite, G. and Droogers, P., (2000). Comparing Estimates of Actual Evapotranspiration From Satellites, Hydrological Models, and Field Data: A Case Study from Western Turkey.
[16] Lillesand, T., Kiefer, R. W. and Chipman, J., (2004). Remote Sensing and Image Interpretation, 6 Edition, Wiley; 6 Press.
[17] Mallick, J., Singh, C. K., Shashtri, S., Rahman, A. and Mukherjee, S., (2012). Land surface emissivity retrieval based on moisture index from LANDSAT TM satellite data over heterogeneous surfaces of Delhi city. International Journal of Applied Earth Observation and Geoinformation, 19, 348-358.
[18] Qin, Z., Karnieli, A. and Berliner, P., (2001). A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. International Journal of Remote Sensing, 22 (18), 3719-3746.
[19] Sobrino, J. A., El Kharraz, J. and Li, Z. L., (2003). Surface temperature and water vapour retrieval from MODIS data. International Journal of Remote Sensing, 24 (24), 5161-5182.
[20] Sobrino, J. A., Jiménez-Muñoz, J. C. and Paolini, L., (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90 (4), 434-440.
[21] Srivastava, P. K., Majumdar, T. J. and Bhattacharya, A., (2010). Study of land surface temperature and spectral emissivity using multi-sensor satellite data. Journal of Earth System Science, 119 (1), 67-74.
[22] Srivastava, P. K., Majumdar, T. J. and Bhattacharya, A. K., (2009). Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Advances in Space Research, 43 (10), 1563-1574.
[23] Sun, Q., Tan, J. and Xu, Y., (2010). An ERDAS image processing method for retrieving LST and describing urban heat evolution: a case study in the Pearl River Delta Region in South China. Environmental Earth Sciences, 59 (5), 1047-1055.
[24] Van de Griend, A. A., and Owe, M, (1993). On the relationship between thermal emissivity and the normalized difference vegetation index for natural surface. International Journal of Remote Sensing, 14 (6), 119-131.
[25] Wan, Z., Wang, P. and Li, X., (2004). Using MODIS Land Surface Temperature and Normalized Difference Vegetation Index products for monitoring drought in the southern Great Plains, USA. International Journal of Remote Sensing, 25 (1), 61-72.
[26] Wan, Z., Zhang, Y., Zhang, Q. and Li, Z. L., (2004). Quality assessment and validation of the MODIS global land surface temperature. International Journal of Remote Sensing, 25 (1), 261-274.
[27] Weng, Q., Lu, D. and Schubring, J., (2004). Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89 (4), 467-483.
[28] Zhangyan, J., Yunhao, C. and Jing, L., (2006). On urban heat island of Beijing based on landsat TM data. Geo-spatial Information Science, 9 (4), 293-297.