جغرافیا و روابط انسانی

جغرافیا و روابط انسانی

مدل‌سازی دمای سطح زمین و روش‌های برآورد در پیش‌بینی LSD با تکنیک سنجش از دور در شهرستان تبریز، ایران

نوع مقاله : مقاله پژوهشی

نویسندگان
1 استاد آب و هواشناسی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی
2 گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی
3 گروه جغرافیای طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران
چکیده
امروزه گرم شدن زمین و افزایش دمای سطح زمین به ویژه در شهرهای بزرگ یکی از معضلات زیست محیطی است. هدف از این مقاله تخمین توانایی الگوریتم‌های Sebal، بهبود یافته تک کانال و پنجره تقسیم در تخمین دمای سطح زمین بر روی داده‌های تصویر Landsat 8 در تیرماه 1398 و استخراج نقشه‌های کاربری اراضی در 7 کلاس برای شهرستان تبریز با استفاده از شی گرا می‌باشد. روش طبقه بندی تطبیق نقشه های دمایی به دست آمده با استفاده از این سه الگوریتم مذکور با نقشه کاربری اراضی و مقایسه الگوریتم ها با یکدیگر از نظر نزدیکی دمای آنها به ایستگاه تبریز از دیگر اهداف این مقاله است. برای تخمین دقت دمای اندازه گیری شده از داده های دمای اندازه گیری شده ایستگاه تبریز در دو سانتی متر بالاتر از زمین (به عنوان نماینده شهرستان تبریز) استفاده شده است. نتایج الگوریتم‌های سبال، بهبود تک کانال و پنجره اسپلیت بیشترین دما را برای کاربری مرتع خشک و کمترین دما را برای استفاده از پوشش گیاهی نشان داد که نشان‌دهنده اهمیت پوشش گیاهی در تغییرات دمایی منطقه مورد مطالعه است. مقایسه الگوریتم های مورد مطالعه با دمای اندازه گیری شده در ایستگاه تبریز و انطباق آنها با کاربری های مختلف نشان داد که الگوریتم تک کاناله بهبود یافته با دمای واقعی دمای واقعی سطح زمین در شهرستان تبریز سازگاری بیشتری دارد. نتایج این مطالعه می تواند به برنامه ریزان محیطی که نگران افزایش دمای هوا در شهرها هستند کمک کند تا تصمیمات مناسب تری در خصوص کنترل این پدیده اتخاذ کنند.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Modeling Land Surface Temperature and Estimating Methods in Predicting LSD by Remote Sensing Technique in Tabriz County, Iran

نویسندگان English

Bromand Salahi 1
Zahra Abdu 2
Mahnaz Saber 3
1 Ph.D. of climatology, Professor, Department of Physical Geography, University of Mohaghegh Ardabili, Ardabil, Iran.
2 Faculty of Social Science, University of Mohaghegh Ardabili, Ardabil, Iran
3 Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
چکیده English

Today, global warming, increasing the Land Surface Temperature, especially in big cities, is one of the environmental problems. The purpose of this article is to estimate the ability of Sebal, improved single-channel and Split window algorithms in estimating Land Surface Temperature on Landsat 8 image data in July 2019 and extracting Land Use maps in 7 classes for Tabriz County using an object-oriented classification method. Matching the temperature maps obtained by using these three mentioned algorithms with the Land Use map and comparing the algorithms with each other in terms of the proximity of their temperature to the Tabriz station is another goal of this article. To estimate the accuracy of the measured temperature, the data of the measured temperature of the Tabriz station at two centimeters above the land (as a representative of Tabriz County) has been used. The results of Sebal, improved single-channel, and Split window algorithms showed the highest temperature for dry pasture use and the lowest temperature for vegetation use, which indicates the importance of vegetation cover in the temperature changes of the studied area. A comparison of the studied algorithms with the temperature measured in the Tabriz station and their adaptation to different uses showed that the improved single-channel algorithm is more consistent with the actual temperature of the actual Land Surface Temperature in Tabriz County. The results of this study can help environmental planners concerned about the increase in air temperature in cities to make more appropriate decisions regarding the control of this phenomenon.

کلیدواژه‌ها English

Land Surface Temperature
Land Use
Object-Oriented Classification
Tabriz County
Abdullah, S., and Barua, D. (2022) Modeling Land Surface Temperature with a Mono-Window Algorithm to Estimate Urban Heat Island Intensity in an Expanding Urban Area. Environ. Process 9, 14. https://doi.org/10.1007/s40710-021-00554-8
Agbelade, A.D., Akinyemi, T.C., and Ojerinde, G.E. (2023) Modeling and assessing the variation of land surface temperature as determinants to normalized difference vegetation index and land cover changes in Nigerian cities. Model. Earth Syst. Environ. https://doi.org/10.1007/s40808-023-01739-w
Ahmed, B., Kamruzzaman, M.D., Zhu, X., Rahman, M., and Choi, K. (2013) Simulating land cover changes and their impacts on Land Surface Temperature in Dhaka, Bangladesh. Remote Sens 5: pp 5969–5998. https://doi.org/10.3390/rs5115969
Akter, T., Gazi, M.Y., and Mia, M.B. (2021) Assessment of Land Cover Dynamics, Land Surface Temperature, and Heat Island Growth in Northwestern Bangladesh Using Satellite Imagery. Environ. Process 8: pp 661–690. https://doi.org/10.1007/s40710-020-00491-y
Al Kafy, A., Rahman, M.S., Faisal, A-A., Hasan, M.M., and Islam, M. (2020) Modelling future Land Use land cover changes and their impacts on Land Surface Temperatures in Rajshahi, Bangladesh. Remote Sens Appl Soc Environ 18:100314. https://doi.org/10.1016/j.rsase.2020.100314
Allen, R., Tasumi, M., Trezza, R., and Wim, B. (2002) SEBAL: Surface Energy Balance Algorithms for Land, Version 1.0, Funded by a NASA EOSDIS/Synergy Grant from the Raytheon Company through The Idaho Department of Water Resources.
Ang Kean, H., and Owi, W.P. (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, pp 1049-1069, DOI: 10.1080/22797254.2018.1542976
Asghari saraskanroud, S., Faal Naziri, M., and Ghale, E. (2019). The Relationship of Different Land Uses with Land Surface Temperature based on Spatial Correlation (Moran) Analysis Using Landsat 8 Satellite Images (OLI) (Case Study: Ardebil City). Geography and Environmental Planning 30(1): pp 93-110. doi: 10.22108/gep.2019.117845.1170
Babalola, O.S., Akinsanola, A.A. (2016) Change Detection in Land Surface Temperature and Land Use Land Cover over Lagos Metropolis, Nigeria. J Remote Sensing & GIS 5: 171. doi:10.4172/2469-4134.1000171
Bokaie, M., Zarkesh, M.K., Arasteh, P.D., and Hosseini, A. (2016) Assessment of urban heat island based on the relationship between Land Surface Temperature and Land Use/land cover in Tehran. Sustain Cities Soc 23: pp 94–104. https://doi.org/10.1016/j.scs.2016.03.009.
Bunai, T., Rokhmatuloh, R., Wibowo, A., and Shidiq, I.P.A.  (2020) Comparison Spatial Pattern of Land Surface Temperature with Mono Window Algorithm and Split Window Algorithm: A Case Study in South Tangerang, Indonesia, Earth and Environmental Science 149: pp 6. DOI 10.1088/1755-1315/149/1/012066.
Chaudhuri, G., and Mishra, N.B. (2016) Spatio-temporal dynamics of land cover and Land Surface Temperature in Ganges-Brahmaputra delta: a comparative analysis between India and Bangladesh. Appl Geogr 68: pp 68–83. https://doi.org/10.1016/j.apgeog.2016.01.002.
Cristóbal, J., Jiménez-Muñoz, J.C., Prakash, A., Mattar, C., Skoković, D., and Sobrino, J.A. (2018) An Improved Single-Channel Method to Retrieve Land Surface Temperature from the Landsat-8 Thermal Band. Remote Sensing 10(3): pp 431. https://doi.org/10.3390/rs10030431.
De Jesus, J.B., Santana, I.D. (2017) Estimation of Land Surface Temperature in Caatinga area using Landsat 8 data. J Hyperspectral Remote Sens 7(3): pp 150–157. https://doi.org/10.29150/jhrs.v7.3.p150-157
Dires, T., and Temesgen, F.,| Fei, L. (2020) Assessing Land Use and land cover change detection using remote sensing in the Lake Tana Basin, Northwest Ethiopia, Cogent Environmental Science 6: pp1, DOI: 10.1080/23311843.2020.1778998.
Ebrahimi Heravi, B., Rangzan, K., Riahi Bakhtiari, H., and Taghizadeh, A. (2015) Determination of urban surface temperature using landSat images (Case study: Karaj). Journal of RS and GIS for Natural Resources 6(2): pp 19-32.
Elkatoury, A., and Alazba, A.A. Mossad A (2020) Estimating Evapotranspiration Using Coupled Remote Sensing and Three SEB Models in an Arid Region. Environ. Process.7: 109–133 (2020). https://doi.org/10.1007/s40710-019-00410-w.
Entezari, A., Amir Ahmadi, A., Aliabadi, K., Khosravian, M., and Ebrahimi, M. (2016) Monitoring Land Surface Temperature and Evaluating Change Detection Land Use (Case Study: Parishan Lake Basin). Hydrogeomorphology 3(8): pp 113-139.
Feizizadeh, B., Didehban, K., and Gholamnia, K. (2016). Extraction of Land Surface Temperature (lst) based on landsat satellite images and split window algorithm study area: mahabad catchment. Geographical data 25(98): pp 171-181. https://sid.ir/paper/253219/en.
Ghosh, S., Chatterjee, N.D., and Dinda, S. (2019) Relation between urban biophysical composition and dynamics of Land Surface Temperature in the Kolkata metropolitan area: a GIS and statistical based analysis for sustainable planning. Model Earth Syst Environ 5: pp 307–329. https://doi.org/10.1007/s40808-018-0535-9
Hatefi Aardakani, M., and Rezaei Moghaddam., M.H. (2015) application of satellite images and GIS in the feasibility of the use of solar energy for providing lighting systems (case study: Zanjan-Tabriz highway). Arid regions geographic studies 6(21): pp 105-124.. https://sid.ir/paper/190665/en.
Imran, H.M., Anwar, H., Mahaad Issa, S., Mohan Kumar, D., Md.Rabiul, I., Kalimur, R., and Mansour, A. (2022) Land Surface Temperature and human thermal comfort responses to Land Use dynamics in Chittagong city of Bangladesh, Geomatics, Natural Hazards and Risk 13: pp 1, 2283-2312, DOI: 10.1080/19475705.2022.2114384
Isaya Ndossi, M., and Avdan, U. (2016) Application of Open Source Coding Technologies in the Production of Land Surface Temperature (LST) Maps from Landsat: A PyQGIS Plugin. Remote Sensing 8(5): 413. https://doi.org/10.3390/rs8050413.
Naseri, S. (2020) Estimating the Land Surface Temperature using the Single Channel algorithm and examining the impact of Land Use on temperature changes (Case study: Malayer county). Journal of Environmental Science Studies 5(2): pp 2477-2482.
Rongali, G., Keshari, A.K., and Gosain, A.K. (2018) Split-Window Algorithm for Retrieval of Land Surface Temperature Using Landsat 8 Thermal Infrared Data. J geovis spat anal 2, 14 https://doi.org/10.1007/s41651-018-0021-y
Sahana, M., Ahmed, R., and Sajjad, H. (2016) Analyzing land surface temperature distribution in response to land use/land cover change using split window algorithm and spectral radiance model in Sundarban Biosphere Reserve, India. Model. Earth Syst. Environ. 2, 81. https://doi.org/10.1007/s40808-016-0135-5
Sajjad, H., and Shankar, K. (2023) Land Use/land cover changes and their impact on Land Surface Temperature using remote sensing technique in district Khanewal, Punjab Pakistan, Geology, Ecology, and Landscapes 7: 1, pp 46-58, DOI: 10.1080/24749508.2021.1923272.
Sekertekin, A., and Bonafoni, S. (2020) Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation. Remote Sensing 12(2): 294. https://doi.org/10.3390/rs12020294
Subhanil, G., Himanshu, G., Neetu, G., and Anindita, D. (2020) Analytical study on the relationship between Land Surface Temperature and Land Use/land cover indices, Annals of GIS 26: 2, pp 201-216, DOI: 10.1080/19475683.2020.1754291.
Tafesse, B., and Suryabhagavan, K.V. (2019) Systematic modeling of impacts of land-use and land-cover changes on land surface temperature in Adama Zuria District, Ethiopia. Model. Earth Syst. Environ 5: 805–817. https://doi.org/10.1007/s40808-018-0567-1
Ünal, Y.S., Sonuç, C.Y., and Incecik, S. (2020) Investigating urban heat island intensity in Istanbul. Theor Appl Climatol 139: pp 175–190, https://doi.org/10.1007/s00704-019-02953-2
Valizadeh Kamran, K., Gholamnia, K., Eynali, G., and Moosavi, M. (2017) Estimation Land Surface Temperature and extract heat islands using split window algorithm and multivariate regression analysis (Case Study of Zanjan). The Urban Research and Planning Quarterly 8(30): pp 35-50.
Wang, X., and Prigent, C. (2020) Comparisons of Diurnal Variations of Land Surface Temperatures from Numerical Weather Prediction Analyses, Infrared Satellite Estimates and In Situ Measurements. Remote Sensing 12(3): pp 583. https://doi.org/10.3390/rs12030583.
Yusuf, Y.A., Pradhan, B., and Idrees, M.O. (2014) Spatio-temporal Assessment of Urban Heat Island Effects in Kuala Lumpur Metropolitan City Using Landsat Images. J Indian Soc Remote Sens 42: pp 829–837. https://doi.org/10.1007/s12524-013-0342-8.

  • تاریخ دریافت 21 شهریور 1402
  • تاریخ بازنگری 08 تیر 1403
  • تاریخ پذیرش 14 مهر 1402