Investigating the effect of land use changes on land surface temperature in cold and semi-arid areas (Case study: Central Zone of Sanandaj City)

Document Type : Research Paper

Authors

Department of Environment Science, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran

Abstract

Nowadays, different societies are facing increasing population and extensive urbanization. Land use changes is one of the phenomena that is very important in the world and has significantly impact on the environment. The purpose of this research is investigating the effect of land use change on land surface temperature in the central zone of Sanandaj city. Using supervised classification method, maximum likelihood algorithm, the land use map was classified into five categories agriculture, bare, urban, vegetation, and water. The land surface temperature examined using Sebal algorithm in a period of 19 years. The obtained results from land use analysis in the study area revealed that urban, agriculture, vegetation and water areas show an increasing trend but bare lands show a decreasing trend from 2000 to 2019. Minimum land surface temperature arrived to 6.15 ºC and 5.26 ºC in 2000 and 2019, respectively. Also, maximum temperature increased from 49.22 ºC to 51.39 ºC in this 19 years period. The highest surface temperature in both mentioned years were obtained in bare lands. Vegetation and water areas have the lowest surface temperature in this period. Unlike Mediterranean and tropical cities which experience the urban heat island, Sanandaj city, with cold and semi-arid climate, experienced the urban cool island. Urban cool island is due to the surrounding urban areas with bare lands with high surface temperature.

Keywords

Ahmad, A. and Quegan, S., 2012. Analysis of maximum likelihood classification on multispectral data. Applied Mathematical Sciences 6, 6425-6436.
Aldhshan, S.R.S. and Shafri, H.Z., 2019. Change detection on land use/land cover and land surface temperature using spatiotemporal data of Landsat: a case study of Gaza Strip. Arab J Geosci 12(443), 1-14.
Allen, R.G., Tasumi, M., Mors, A., 2002. Satellite-based Evapotranspiration by METRIC and Landsat for western estates water management, US Bureau Reclamation Evapotranspiration workshop.
Amanollahi, J., Tzanis, C., Ramli, M.F., Abdullah, A.M., 2016. Urban heat evolution in a tropical area utilizing Landsat imagery. Atmospheric Research 167, 175-182.
Darvishi, S.H., Rashidpour, M., Solaimani, K., 2019. Investigation of the relationship between land use changes and surface temperature using satellite images Case study: Marivan city. Geography and Development 54, 143-162.
Deng, Y., Wang, S., Bai, X., Tian, Y., Wu, L., Xiao, J., 2018. Relationship among land surface temperature and LUCC, NDVI in typical karst area. Scientific Rep 8(641), 1-12.
Efstathiou, M.N., Tzanis, C., Cracknell, A.P., Varotsos, C.A., 2011. New features of land and sea surface temperature anomalies. Remote Sens 32, 3231-3238.
Entezari, A.R., Amir Ahmadi, A., Aliabadi, K., Khosravian, M., Ebrahimi, M., 2016. Surface temperature monitoring and evaluation of land use change trends (Case study: Parishan Lake watershed). Hydrogeomorphology 8, 113-139.
Frey, C.M., Rigo, G., Parlow, E., 2009. Investigation of the daily Urban Cooling Island (UCI) in two coastal cities in an arid environment. Dubai and Abu Dhabi (UAE). City, 81, 2-6.
Garcia-Cueto, O., Jauregui-Ostos, E., Toudert, D., Tejeda-Martinez, A., 2007. Detection of the urban heat island in Mexicali, BC, Mexico and its relationship with land use. Atmosfera 20(2), 111-131.
Georgescu, M., Moustaoui, M., Mahalov, A., Dudhia, J., 2011. An alternative explanation of the semiarid urban area “oasis effect”. Journal of Geophysical Research: Atmospheres 116, 1-13.
Grimm, N.B., Faeth, S.H., Golubiewski, N.E., Redman, C.L., Wu, J., Bai, X., Briggs, J.M., 2008. Global change and the ecology of cities. Science 319(5864), 756-760.
Hereher, M.E., 2017. Effect of land use/cover change on land surface temperatures-The Nile Delta, Egypt. Journal of African Earth Sciences 126, 75-83.
Howard, L., 1818. The climate of london: deduced from meteorological observations. Cambridge.
Hua, A.K. and Ping, O.W., 2018. The influence of land-use/land-cover changes on land surface temperature: a
case study of Kuala Lumpur metropolitan city. European Journal of Remote Sensing 51(1), 1049-1069.
Jafari, A., 2005. Iranian Geology. Tehran: Institute of Geography and Cartography of Geology, 3, 1488 p.
Latif, M.S., 2014. Land surface temperature retrival of landsat-8 data using split window algorithm- A case study of ranchi district. International Journal of Engineering Development and Research 2(4), 23-39.
Lejeune, Q., Davin, E.L., Guillod, B.P., Seneviratne, S.I., 2015. Influence of Amazonian deforestation on the future evolution of regional surface fluxes, circulation, surface temperature and precipitation. Clim Dyn 44, 2769-2786.
Lillesand, T.M., Kiefer, R.W., Chipman, J.W., 2004. Remote sensing and image interpretation. 5th edition, Wiley and Sons, New York, 812 p.
Liu, L. and Zhang, Y., 2011. Urban heat island analysis using the Landsat TM data and ASTER data: A case study in Hong Kong. Remote Sens 3(7), 1535-1552.
Liu, G., Zhang, Q., Li, G., Doronzo, D.M., 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), 1-12.
Maithani, S., 2009. A neural network based urban growth model of an indian city. Indian Soc. Remote Sensing 37, 363-376.
Pal, S. and Ziaul, S., 2017. Detection of land use and land cover change and land surface temperature in english bazar urban centre. The Egyptian Journal of Remote Sensing and Space Science 20(1), 125-145.
Rasul, A., Balzter, H., Smith, C., 2015. Spatial variation of the daytime surface urban cool island during the dry season in Erbil, Iraqi Kurdistan, from Landsat 8. Urban Climate 14, 176-186.
Reisi, M., Ahmadi Nadoushan, M., Aye, L., 2019. Remote sensing for urban heat and cool islands evaluation in semi-arid areas. Global Journal of Environmental Science and Management 5(3), 319-330.
Rozenstein, O., Qin, Z.H., Derimian, Y., Karnieli, A., 2014. Derivation of land surface temperature for landsat-8 TRIS using a split window algorithm, sensors 14(4), 5768-5780.
Rwanga, S.S. and Ndambuki, J.M., 2017. Accuracy assessment of land use/land cover classification using remote sensing and GIS. International Journal of Geosciences 8, 611-622.
Seif, A. and Mokarram, M., 2012. Change detection of Gil Playa in the Northeast of Fars Province. Iran Am J Sci Res 86, 122-130.
Singh, P., Kikon, N., Verma, P., 2017. Impact of land use change and urbanization on urban heat island in Lucknow city, Central India. A remote sensing based estimate. Sustainable cities and societ 32, 100-114.
Sisodia, P.S., Tiwari, V., Kumar, A., 2014. Analysis of supervised maximum likelihood classification for remote sensing image. Recent Advances and Innovations in Engineering (ICRAIE): IEEE 1-4.
Sobrino, J.A., Jimenez-Munoz, J.C., Soria, G., Romaguera, M., Guanter, L., Moreno, J., Plaza, A., Martinez, P., 2008. Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE Transaction of Geoscience Remote Sensing 46, 316-327.
Wang, R., Cai, M., Ren, Ch., Bechtel, B., Xu, Y., Ng, E., 2019. Detecting multitemporal land cover change and land surface temperature in Pearl River Delta by adopting local climate zone. Urban Climate 28, 1-16.
Wheeler, S.M., Abunnasr, Y., Dialesandro, G., Assaf, E., Agopian, S., Gamberini, V.C., 2019. Mitigating urban heating in dryland cities: A Literature Review. Journal of Planning Literature 34(4), 434-446.
Xiao, H., Kopecká, M., Guo, S., Guan, Y., Cai, D., Zhang, C., 2018. Responses of Urban Land Surface Temperature on Land Cover: A Comparative Study of Vienna and Madrid. Sustainability 10(2), 260.
Yang, X., Li, Y., Luo, Z., Chan, P.W., 2016. The urban cool island phenomenon in a high-rise high-density city and its mechanisms. Int. J. Climatol 1-16.
Youneszadeh, S., Amiri, N., Pilesjo, P., 2015. The effect of land use change on land surface temperature in the Netherlands. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 40, 745.
Zareie, S., Khosravi, H., Nasiri, A., Dastorani, M., 2016. Using landsat the-matic mapper (TM) Sensor to detect change in land surface temperature in rela-tion to land use change in Yazd, Iran. Solid Earth 7, 1551-1564.
Zhang, Y., Balzter, H., Zou, C., Xu, H., Tang, F., 2015. Characterizing bi-temporal patterns of land surface temperature using landscape metrics based on sub-pixel classifications from Landsat TM/ETM+. International Journal of Applied Earth Observation and Geoinformation 42, 87-96.
Zhou, W., Huang, G., Cadenasso, M.L., 2011. Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes. Landscape and Urban Planning 10(2), 54-63.