The Relationship between Surface Temperature and Land Use using Multi-Temporal Remote Sensing Imagery in Muang Udon Thani District
Abstract
This study aimed at investigating the relationship among surface temperature, land use and surface temperature distribution for 22 year period with Landsat satellite imagery 5, 7 and 8 between 1997 – 2019 and analyzing patterns of spatial distribution of surface temperature using spatial autocorrelation together with land use. The study of land use obtained data from satellite of 2019 using random forest (RF). The data on land use in 2019 together with average surface temperature acquired from thermal infrared band for 22 year period was analyzed to identify patterns of spatial distribution of surface temperature for global indicator using spatial autocorrelation (Moran’ I), and for local indicator using Local G-Statistics and Local Indication of Association (LISA) with the size of grid of 300 x 300 meters. The results found that in classifying land use RF yielded more accuracy (87%), most of the area was agricultural and urban community area. The analysis of surface temperature changes and patterns of surface temperature distribution for 22 year period indicated that annual average surface temperature increased in average by 6.6˚C. The patterns of distribution of global spatial autocorrelation were found to be clustered highest in urban and bare land. The results of the analysis of the relationship between average surface and building area yielded R2 equal 0.9641 and this indicated the highly degree of correlation of these two sets of data. Keywords : surface temperature ; land use ; Landsat imagery ; Muang Udon Thani DistrictReferences
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Rhee, J., Park, S., & Lu, Z. (2014). Relationship between land cover patterns and surface temperature in urban areas. GIScience & remote sensing, 51(5), 521-536.
Taksadipong, S., Chuntranuluck, S., & Rungratanaubon, T. (2015). Cooling effect of urban green area on air temperature and relative humidity. Burapha Science Journal, 19(1), 109-118.
Thai Meteorological Department. (2019). Maxumum and low temperature in Thailand. Retrieved September 8, 2019, from https://www.tmd.go.th/programs/uploads/tempstat/min_stat_latest.pdf
Veraverbeke, S., Verstraeten, W. W., Lhermitte, S., Van De Kerchove, R., & Goossens, R. (2012). Assessment of post-fire changes in land surface temperature and surface albedo, and their relation with fire–burn severity using multi-temporal MODIS imagery. International Journal of Wildland Fire, 21(3), 243-256.
Udon Thani Government. (2014). Udon Thani province plan development. Retrived August 28, 2019, from http://www.udonthani.go.th/2014/download/datacenter/Development_Plan61-64(Recover62).pdf
Xi, Y., Thinh, N., & Li, C. (2018). Spatio-temporal variation analysis of landscape pattern response to land use change from 1985 to 2015 in Xuzhou City, China. Sustainability, 10(11), 4287.
Zhao, W., & Li, Z. L. (2013). Sensitivity study of soil moisture on the temporal evolution of surface temperature over bare surfaces. International Journal of Remote Sensing, 34(9-10), 3314-3331.
Zhu, Z., Fu, Y., Woodcock, C. E., Olofsson, P., Vogelmann, J. E., Holden, C., Yu, Y. (2016). Including land cover
change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from
Guangzhou, China (2000–2014). Remote Sensing of Environment, 185, 243-257.
Anbazhagan, S., & Paramasivam, C. (2016). Statistical correlation between land surface temperature (LST) and vegetation index (NDVI) using multi-temporal landsat TM data. International Journal of Advanced Earth Science and Engineering, 5(1), 333-346.
Arifwidodo, S., & Chandrasiri, O. (2015). Urban heat island and household energy consumption in Bangkok, Thailand. Energy Procedia, 79(1), 189-194.
Avdan, U., & Jovanovska, G. (2016). Algorithm for automated mapping of land surface temperature using landsat 8 satellite data. Journal of Sensors, 2016.
Bhattacharjee, S., Chen, J., & Ghosh, S. K. (2020). Spatio‐temporal prediction of land surface temperature using
semantic kriging. Transactions in GIS, 24(1), 189-212.
Chotchaiwong, P., & Wijitkosum, S. (2019). Relationship between land surface temperature and land use in
Nakhon Ratchasima city, Thailand. Engineering Journal, 23(4), 1-14.
Dai, X., Guo, Z., Zhang, L., & 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.
Dintwe, K., Okin, G. S., & Xue, Y. (2017). Fire‐induced albedo change and surface radiative forcing in sub‐Saharan Africa savanna ecosystems: Implications for the energy balance. Journal of Geophysical Research: Atmospheres, 122(12), 6186-6201.
Fan, C., Myint, S. W., & Zheng, B. (2015). Measuring the spatial arrangement of urban vegetation and its impacts on seasonal surface temperatures. Progress in physical geography, 39(2), 199-219.
Fan, F., Weng, Q., & Wang, Y. (2007). Land use and land cover change in Guangzhou, China, from 1998 to 2003, based on Landsat TM/ETM+ imagery. Sensors, 7(7), 1323-1342.
Fu, P., & Weng, Q. (2016). A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with landsat imagery. Remote Sensing of Environment, 175,
205-214.
Ghosh, A., Sharma, R., & Joshi, P. (2014). Random forest classification of urban landscape using landsat archive and ancillary data: Combining seasonal maps with decision level fusion. Applied Geography, 48, 31-41.
Goodchild, M. F. (1986). Spatial autocorrelation (Vol. 47): Geo Books.
Guo, G., Wu, Z., Xiao, R., Chen, Y., Liu, X., & Zhang, X. (2015). Impacts of urban biophysical composition on land surface temperature in urban heat island clusters. Landscape and Urban Planning, 135, 1-10.
Ibrahim, I., Abu Samah, A., Fauzi, R., & Noor, N. M. (2016). The land surface temperature impact to land cover
types. International Archives of the Photogrammetry, Remote Sensing & Spatial Information
Sciences, 41.
Keeratikasikorn, C. (2018). A comparative study on four major cities in Northeastern Thailand using urban land density function. Geo-spatial information science, 21(2), 93-101.
Liu, Z., Ballantyne, A. P., & Cooper, L. A. (2019). Biophysical feedback of global forest fires on surface temperature. Nature communications, 10(1), 1-9.
Marome, W., & Pholcharoen, T. (2019). Institutional Analysis of Limitations to Climate Resilient Urban Development Planning: the Case of Udon Thani Province. EnvironmentAsia, 12(3).
Mohajane, M., Essahlaoui, A., Oudija, F., El Hafyani, M., Hmaidi, A. E., El Ouali, A., Teodoro, A. C. (2018). Land use/land cover (LULC) using landsat data series (MSS, TM, ETM+ and OLI) in Azrou forest, in the central middle atlas of Morocco. Environments, 5(12), 131.
Munyati, C. (2017). The potential for integrating sentinel 2 MSI with spot 5 HRG and landsat 8 OLI imagery for monitoring semi-arid savannah woody cover. International Journal of Remote Sensing, 38(17),
4888-4913.
Muttitanon, W., & Tripathi, N. (2005). Land use/land cover changes in the coastal zone of Ban Don Bay, Thailand using Landsat 5 TM data. International Journal of Remote Sensing, 26(11), 2311-2323.
Office of the Cane and Sugar Board. (2013). The project under the evaluation of the development and expansion of sugar cane varieties. Minstry of Industry, Bangkok, 35p.
Phuttharak, T., & Dhiravisit, A. (2014). Rapid urbanization-its impact on sustainable development: A case Study of Udon Thani, Thailand. Asian Social Science, 10(22), 70.
Prommahakul, K., Pheunsongkam, N., Somard, J., & Jitsukk, W. (2020). Sugarcane land change pattern and yield prediction using landsat imagery and unmanned aerial vehicle photos. Burapha Science Journal, 25(1), 168-186.
Puansurin, K., Wongtragoon, U., Singchan, B., & Suwanmaneepong, S. (2018). The study of participatory monitoring of air quality and urban heat, case study Udon Thani province, Thailand. International Journal of Agricultural Technology, 14(7 Special Issue), 1693-1708.
Rhee, J., Park, S., & Lu, Z. (2014). Relationship between land cover patterns and surface temperature in urban areas. GIScience & remote sensing, 51(5), 521-536.
Taksadipong, S., Chuntranuluck, S., & Rungratanaubon, T. (2015). Cooling effect of urban green area on air temperature and relative humidity. Burapha Science Journal, 19(1), 109-118.
Thai Meteorological Department. (2019). Maxumum and low temperature in Thailand. Retrieved September 8, 2019, from https://www.tmd.go.th/programs/uploads/tempstat/min_stat_latest.pdf
Veraverbeke, S., Verstraeten, W. W., Lhermitte, S., Van De Kerchove, R., & Goossens, R. (2012). Assessment of post-fire changes in land surface temperature and surface albedo, and their relation with fire–burn severity using multi-temporal MODIS imagery. International Journal of Wildland Fire, 21(3), 243-256.
Udon Thani Government. (2014). Udon Thani province plan development. Retrived August 28, 2019, from http://www.udonthani.go.th/2014/download/datacenter/Development_Plan61-64(Recover62).pdf
Xi, Y., Thinh, N., & Li, C. (2018). Spatio-temporal variation analysis of landscape pattern response to land use change from 1985 to 2015 in Xuzhou City, China. Sustainability, 10(11), 4287.
Zhao, W., & Li, Z. L. (2013). Sensitivity study of soil moisture on the temporal evolution of surface temperature over bare surfaces. International Journal of Remote Sensing, 34(9-10), 3314-3331.
Zhu, Z., Fu, Y., Woodcock, C. E., Olofsson, P., Vogelmann, J. E., Holden, C., Yu, Y. (2016). Including land cover
change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from
Guangzhou, China (2000–2014). Remote Sensing of Environment, 185, 243-257.
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2021-01-05
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