Abstract
Land surface temperature (LST) is one of the key parameter used for analyzing the heat energy balance and thermal flux of land surfaces. It is also useful for making urban heat transfer models, water resource management, climate change modeling, and environmental studies. This study is to find the surface temperature of Jubail Industrial City, which is one of the biggest industrial areas in the world. The study also aims to analyze the spatial and temporal variations of LST of the city. Landsat 8 Thermal Infrared Remote Sensor (TIRS) data has been used for this study and the surface temperature has been estimated by using single-channel (SC) method. The study reveals that the surface temperature is relatively low and ranging from 20 to 30 °C in January. However, the industrial area and some parts of the residential area have more temperature than the rest of the city. During the month of March, the temperature increases gradually and reaches high in June. During the summer, the surface temperature in the residential area of the city is around 40–50 °C. The temperature in the sub urban areas is moderate; however, high temperature (50–55 °C) has been recorded in the industrial area of the city. Significant heat islands of temperature more than 60 °C have also been noted near the iron and steel factories of the industrial area. In the month of September, the land surface temperature in most part of the city is lower than that of peak summer.
Similar content being viewed by others
References
Akhoondzadeh M, Saradjian MR (2008) Comparison of land surface temperature mapping using MODIS and ASTER images in semi-arid area. Int Arch Photogramm Remote Sens Spat Inf Sci XXXVII(Part B8) Beijing
Ali AR, Mohammed ES (2016) Impact of industrial activities on land surface temperature using remote sensing and GIS techniques—a case study in Jubail, Saudi Arabia. J Geogr Nat Disast S6:002. https://doi.org/10.4172/2167-0587.S6-002
Asmat A, Mansor S, Tai Hong W (2003) Rule based classification for urban heat island mapping. Proceedings of the 2nd FIG Regional Conference Marrakech, Morocco, 2–5 December
Becker F, Li ZL (1995) Surface temperature and emissivity at various scales: definition, measurement and related problems. Remote Sens Rev 12:225–253
Behrendt A, Wagner G, Petrova A, Shiler, M, Pal S, Schaberl T, Wulfmeyer V (2005) Modular LIDAR systems for high-resolution 4-dimensional measurements of water vapor, temperature, and aerosols SPIE 2005, 5653, 220
Betts AK, Ball JH Beljaars ACM, Miller MJ, Viterbo PA (1996) The land surface-atmosphere interaction: a review based on observational and global modelling perspectives. J Geophys Res 101:7209–7225
Carlson TN, Ripley DA (1997) On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sens Environ 62:241–252
Coll C, Caselles V (1997) A split-window algorithm for land surface temperature from advanced very high resolution radiometer data: validation and algorithm comparison. J Geophys Res-Atmos 102:16697–16713
Dickinson RE (1994) Satellite systems and models for future climate change. In: Henderson-Sellers A (ed) Future Climates of the World: A Modelling Perspective, 16th edn. World Survey of Climatology Elsevier, Amsterdam, p 27
El-Nahry AH, Rashash A (2013) Impact of industrial on surface temperature using thermal infrared remote sensing and GIS techniques—a case study of Juabil City, KSA, The 8th National GIS Symposium in Saudi Arabia
Grimmond SUE (2007) Urbanization and global environmental change: local effects of urban warming. Geogr J 173:83–88
Hall FG, Huemmrich KF, Goetz SJ, Sellers PJ, Nickeson JE (1992) Satellite remote sensing of surface energy balance: success failures, and unresolved issues in FIFE. J Geophys Res 97:19,061–19,089
Jia LM, Su ZB, Li ZL, Djepa V, Wang JM (2001) Modelling sensible heat flux using estimates of soil and vegetation temperatures: the HEIFE and IMGRASS experiments. In: Beniston M, Verstraete M (eds) Remote sensing and climate modeling: synergies and limitations. Eds; Kluwer Academic Publishers, Berlin, pp 23–49
Kalma J, McVicar T, McCabe M (2008) Estimating land surface evaporation: a review of methods using remotely sensed surface temperature data. Surv Geophys 29:421–469
Kumar S, Bhasker U, Padmakumari K (2012) Estimation of land surface temperature to study urban heat island effect using Landsat ETM+ image. Int J Eng Sci Technol 4(02):771–777
Kustas W, Anderson M (2009) Advances in thermal infrared remote sensing for land surface modeling. Agric For Meteorol 149:2071–2081
Li J, Wang X, Wang X, Ma W, Zhang H (2009) Remote sensing evaluation of urban heat island and its spatial pattern of the Shanghai metropolitan area, China. Ecol Complex 6(4):413–420
Li Z-L, Tang B-H, Hua W, Ren H, Yan G, Wan Z, Trigo IF, Sobrino JA (2013) Satellite-derived land surface temperature: current status and perspectives. Remote Sens Environ 131:14–37
Linh NT, Huy TQ, Jungwon H, Dongyeob H (2015) Land surface temperatures of industrial complexes in Jeonnam using Landsat 7 ETM+ satellite images. Journal of the KRSA 31(3):99–112
Liu G, Zhang Q, Li G, Doronzo DM (2016) Response of land cover types to land surface temperature derived from Landsat-5 TM in Nanjing metropolitan region, China. Environ Earth Sci 75:1386
Moran MS, Rahman AF, Washburne JC, Goodrich DC, Weltz MA, Kustas WP (1996) Combining the Penman-Monteith equation with measurements of surface temperature and reflectance to estimate evaporation rates of semiarid grassland. Agric For Meteorol 80:87–109
Muro J, Canty M, Conradsen K, Hüttich C, Nielsen AA, Skriver H, Remy F, Strauch A, Thonfeld F, Menz G (2016) Short-term change detection in wetlands using Sentinel-1 time series. Remote Sens 8(10):795. https://doi.org/10.3390/rs8100795
Musa T, Xu W, Hou W (2018) Terence Darlington Mushore (2018) Comparative analysis of responses of land surface temperature to long-term land use/cover changes between a coastal and Inland City: a case of Freetown and Bo town in Sierra Leone. Remote Sens 10:112. https://doi.org/10.3390/rs10010112
Mushore TD, Mutanga O, Odindi J, Dube T (2017) Linking major shifts in land surface temperatures to long term land use and land cover changes: a case of Harare, Zimbabwe. Urban Climate 20:120–134
Nayak S, Mandal M (2012) Impact of land-use and land-cover changes on temperature trends over Western India. Curr Sci 102:1166–1173
Pal S, Devara PA (2012) Wavelet-based spectral analysis of long-term time series of optical properties of aerosols obtained by LIDAR and radiometer measurements over an urban station in Western India. J Atmos Sol Terr Phys 84–85:75–87
Quattrochi DA, Luvall JC (2004) Thermal remote sensing in land surface processing. CRC Press, Boca Raton
Rajendran P, Mani K (2015) Estimation of spatial variability of land surface temperature using Landsat 8 imagery. Int J Eng Sci 4(11):19–23
Salisbury JW, D’Aria DM (1992) Emissivity of terrestrial materials in the 8-14 pm atmospheric window. Remote Sens Environ 42:83–106
Schmugge TJ, Becker F, Li ZL (1991) Spectral emissivity variations observed in airborne surface temperature measurements. Remote Sens Environ 35:95–104
Sobrino José A, Jiménez-Muñoz JC, Sòria G, Romaguera M, Guanter L, Moreno J, Associate Member IEEE, Plaza A, Senior Member IEEE, Pablo MM (2008) Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE Trans Geosci Remote Sens 46(2)
Sumit K, Rohit G, Nivedita K, Aneesh M (2018) Assessment of land surface temperature variation due to change in elevation of area surrounding Jaipur, India. The Egyptian Journal of Remote Sensing and Space Sciences 21:87–94
Tan KC, Lim HS, MatJafri MZ, Abdullah K (2010) Land surface temperature retrieval by using ATCOR3_T and normalized difference vegetation index methods in Penang Island. Am J Appl Sci 7(5):717–723
Vlassova L, Perez-Cabello F, Nieto H, Martín P, Riaño D, de la Riva J (2014) Assessment of methods for land surface temperature retrieval from Landsat-5 TM images applicable to multiscale tree-grass ecosystem modeling. Remote Sens 6:4345–4368. https://doi.org/10.3390/rs6054345
Wan Z (1999) MODIS land-surface temperature algorithm theoretical basis document. Institute for Computational Earth System Science University of California, Santa Barbara Santa Barbara, pp 93106–93060
Wan Z, Dozier J (1996) A generalized split- window algorithm for retrieving land-surface temperature from space. IEEE Trans Geosci Remote Sens 34(4)
Weng Q (2009) Thermal infrared remote sensing for urban climate and environmental studies: methods, applications, and trends. ISPRS J Photogramm Remote Sens 64:335–344
Yu X, Guo X, Zhaocong W (2014) Land surface temperature retrieval from Landsat 8 TIRS—comparison between radiative transfer equation-based method, split window algorithm and single channel method. Remote Sens 6:9829–9852. https://doi.org/10.3390/rs6109829
Zaharaddeen ISA, Ibrahim I, Baba, Zachariah A (2016) Estimation of land surface temperature of Kaduna metropolis, Nigeria using Landsat images. Sci World J 11(3):36–42
Zanter K (2016) LANDSAT 8 (L8) data users handbook. Department of the Interior U.S. Geological Survey Version 2.0
Zareie S, Khosravi H, Nasiri A, Dastorani M (2016) Using Landsat thematic mapper (TM) sensor to detect change in land surface temperature in relation to land use change in Yazd, Iran. Solid Earth 7:1551–1564
Zhan X, Kustas WP, Humes KS (1996) An inter comparison study on models of sensible heat flux over partial canopy surfaces with remotely sensed surface temperature. Remote Sens Environ 58:242–256
Zhang F, Tiyip T, Kung H et al (2016) Dynamics of land surface temperature (LST) in response to land use and land cover (LULC) changes in the Weigan and Kuqa river oasis, Xinjiang, China. Arab J Geosci 9:499
Zhou J, Chen YH, Wang JF, Zhan WF (2011) Maximum night-time urban heat island (UHI) intensity simulation by integrating remotely sensed data and meteorological observations. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 4:138–146
Acknowledgements
The authors are thankful to the Managing Director, Jubail Industrial College, Jubail Industrial City, Saudi Arabia, for his kind support and encouragement to applied scientific research and development. The authors are also thankful to the Deputy Directors, Chairman, and Faculty members of the college for extending effective provisions, support, and encouragement for performing the work.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mujabar, S., Rao, V. Estimation and analysis of land surface temperature of Jubail Industrial City, Saudi Arabia, by using remote sensing and GIS technologies. Arab J Geosci 11, 742 (2018). https://doi.org/10.1007/s12517-018-4109-y
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12517-018-4109-y