اصغری سراسکانرود، صیاد؛ هادی امامی (1398). پایش دمای سطح زمین و بررسی رابطه کاربری اراضی با دمای سطح با استفاده از تصاویر سنجنده OLI و +ETM مطالعه موردی: (شهرستان اردبیل)، تحقیقات کاربردی علوم جغرافیایی (علوم جغرافیایی). دوره 19. شماره 53. صفحات 215-195.
https://sid.ir/paper/102206/fa
انتظاری، علیرضا؛ رحمان زندی؛ مریم خسرویان (1398). ارزیابی تغییرات فضایی پوشش گیاهی و دمای سطح زمین با استفاده از تصاویر لندست و مادیس، مطالعه موردی: استان فارس 2017-1986، مهندسی و مدیریت آبخیز. دوره 11. شماره 4. 940-929.
درویشی، شادمان؛ کریم سلیمانی؛ مصطفی رشیدپور (1398). تأثیر شاخص های گیاهی و خصوصیات سطح شهری بر تغییرات دمای سطح زمین مطالعه موردی (شهرستان سنندج)، سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی. سال دهم. شماره اول.
رنگزن، کاظم؛ سعید ملکی؛ ایوب تقیزاده؛ پیمان حیدریان (1392). مدلسازی توسعه فضایی شهری با استفاده از تکنولوژی سامانههای اطلاعات جغرافیایی و رگرسیون وزندار مکانی (GWR): نمونه موردی کلانشهر تهران، پایان نامه ارشد سنجش از دور GIS. دانشکده علوم زمین.
https://elmnet.ir/doc/10651141-42011
زندی، رحمان؛ محمد سلمانیمقدم؛ زهره روکی (1402). سنجش میزان خودهمبستگی فضایی دمای سطح زمین با کاربری اراضی نمونۀ مطالعه: شهر اصفهان، جغرافیا و برنامهریزی محیطی. دوره 34. شماره 1. صفحات 76-67.
عزیمند، کیوان؛ حسین عقیقی؛ داوود عاشورلو؛ عارف شاهیآقبلاغی (1399). تجزیه وتحلیل اثرهای ویژگیهای کالبدی و مورفولوژیکی زمینهای ساخته شده بر تغییرات دمای سطح زمین در مناطق نیمهخشک، فصلنامه علوم محیطی. دوره 18. شماره 2. صفحات 18-1.
https://envs.sbu.ac.ir/article_98133.html
کلانتری، خلیل (1391). پردازش و تحلیل داده ها در تحقیقات اجتماعی- اقتصادی، تهران. انتشارات فرهنگ صبا. چاپ پنجم.
https://www.gisoom.com/book/11157179
هاشمیدرهبادامی، سیروس؛ علی درویشی بلورانی؛ کاظم علویپناه؛ محمد ملکی؛ رضا بیات (1398). تحلیل تغییرات جزیره حرارتی سطوح شهری در روز و شب با استفاده از محصولات چند زمانه سنجنده مادیس.
Alexander C (2020). Normalised difference spectral indices and urban land cover as indicators of land surface temperature (LST). International Journal of Applied Earth Observation and Geoinformation, 86, 102013.
https://doi.org/10.1016/j.jag.2019.102013
Aliabadi, K. and A. Dadashi-roudbari (2019). Investigation of changes in spatial autocorrelation patterns of Iran's maximum temperature. Geographical Studies of Arid Areas, 6 (21): 86-104. (In Persian).
https://jargs.hsu.ac.ir/article_161397_9d56569aa9c61455ffbb9eb4731adb91.pdf
Alibakhshi Z, Ahmadi M& Farajzadeh ASL M (2020). Modeling Biophysical Variables and Land Surface Temperature Using the GWR Model: Case Study-Tehran and Its Satellite Cities. Journal of Indian Society of Remote Sensing,48, 59-70.
Adegoke, C. and A. Sojobi (2015). "Climate change impact on infrastructure in Osogbo metropolis, south-west Nigeria." Journal of Emerging Trends in Engineering and AppliedSciences.167-156, (3) 6.
Akbari, H., Menon, S and Rosenfeld, A (2007). Global cooling: effect of urban albedo on global temperature algorithms for estimating sea and land surface temperature with ATSR data. Int J Remote Sens.17. 2114-2089, (11).
https://heatisland.lbl.gov/publications/global-cooling-effect-urban-albedo
Alhawiti، RH, Mitsova) 2016). Using Landsat-8 data to investigate the correlation between urban heat island and urban land uses. International Journal of Research in Engineering and Technology, 5,457-466.
Azhdari, A., Soltani, A. and Alidadi, M (2018). Urban morphology and landscape structure effect on land surface temperature: evidence from Shiraz, a semi-arid city. Sustainable Cities and Society. 41, 853-864.
https://doi.org/10.1016/j.scs.2018.06.034
Balew A, Korme T (2020). Monitoring land surfacetemperature in Bahir Dar city and its surrounding using Landsat images. The Egyptian Journal of Remote Sensing and Space Science.
https://doi.org/10.1016/j.ejrs.2020.02.001.
Bari, E, Nipa. N.J & Roy B (2021). Association of vegetation indices with atmospheric & biological factors using MODIS time series products, Environ. Challeng., 5 (2021), 100376.
Chen, X.L. Zhao, H.M. Li, P.X. & Yin, Z.Y (2006) .Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes, Remote Sensing of Environment.146-133,104.
Deilami K. Kamruzzaman M (2017). Modelling the urban heat island effect of smart growth policy scenarios in Brisbane, Land Use Pol., 64 (2017), 38-55.
Deng, C. & Wu, C (2013). Examining the Impacts of Urban Biophysical Compositions on Surface Urban Heat Island: A Spectral Unmixing and Thermal Mixing Approach. Remote Sensing of Environment, 131, 262-274. https://doi.org/10.1016/j.rse.2012.12.020.
Emami& Emami (2018). Investigation of Urban Biophysical Compounds in the Formation of Thermal Islands Using RS and GIS (Case Study: Yazd (2018). Journal of Radar and Optic Remote Sensing” (JRORS)), 2018.04.13. Environment, Vol.127, 210-222.
https://jrors.yazd.iau.ir/article_542418
Ezimand, K., Kakroodi, A. A and Kiavarz, M (2019). The development of spectral indices for detecting builtup from LANDSAT TM:5.Remote Sensing of Environment.90.440-434,(4).
Feyisa G.L. Meilby H, Darrel G. Jenerette, S. Pauliet (2016). Locally optimized separability enhancement indices for urban land cover mapping: exploring thermal environmental consequences of rapid urbanization in Addis Ababa, Ethiopia, Remote Sens. Environ., 175, 14-31.
Gohain, K.J. P. Mohammad & Goswami A (2021). Assessing the impact of land use land cover changes on land surface temperature over Pune city, India, Quat. Int., 575–576 (2021), 259-269.
Guanglei H. Hongyan Z, Yeqiao W, Zhihe Q, Zhengxiang Z (2010). Retrieval and spatial distribution of land surface temperature in the middle part of jilin province based on MODIS data, Sci. Geogr. Sin., 30 (3) (2010), 421-427. Accessed: Aug. 16, 2021.
Guha, S. Govil. H (2021). An assessment on the relationship between land surface temperature and normalized difference vegetation index Environ. Dev. Sustain., 23 (2) (2021), 1944-1963.
Guha S. Govil H, Dey A Gill N (2017). Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy, Eur. J. Remote Sens., 51 (1) (2018), 667-678.
Guha S. Govil H, Mukherjee S (2017). Dynamic analysis and ecological evaluation of urban heat islands in Raipur city, India,J. Appl. Remote Sens., 11 (3) (2017),1.
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.
Imhoff, M. L., Zhang, P., Wolfe, R. E., & Bounoua, L (2010). Remote sensing of the urban heat island effect across biomes in the continental USA. Remote sensing of environment,114(3): 504-513.
Imran, ESE (2012). Detection of land use and surface temperature change in different resolutions. Geographic Information System Journal, 4,189-203.
Jain S, Sannigrahi S, Sen S, Bhatt S, Chakraborti S& Rahmat S (2020). Urban heat island intensity and its mitigation strategies in the fast-growing urban area. Journal of Urban Management, 9(1), 54-66.
https://doi.org/10.1016/j.jum.2019.09.004.
Jiménez-Muñoz JC, Sobrino JA (2008). Split-window coefficients for land surface temperature retrieval from low-resolution thermal infrared sensors. IEEE Geosci Remote Sens Lett 5:806-809.
Lazzarini, M., Marpu, P.R. and Ghedira, H (2013). Temperature-land cover interactions: the inversion of
urban heat island phenomenon in desert city areas. Remote Sensing of Environment. 130, 136-152.
Lee PS-H, Park J (2020). An Effect of Urban Forest on Urban Thermal Environment in Seoul, South Korea, Based on Landsat Imagery Analysis.Forests, 11(6): 630.
https://doi.org/10.3390/f11060630.
Lei Wang,
Yao Lu and
Yunlong Yao (2019). Comparison of Three Algorithms for the Retrieval of Land Surface Temperature from Landsat 8 Images, 19 November 2019.
Lillesand, T., Kiefer, R. W., & Chipman, J (2015). Remote sensing and image interpretation. John Wiley & Sons.
ISBN: 978-1-118-34328-9.
Nie Q. Man W, Li Z, Y (2016). Huang, Spatiotemporal impact of urban impervious surface on land surface temperature in Shanghai, China,Can. J. Rem. Sens., 42 (6) (2016), 680-689.
Pearsall H (2017). Staying cool in the compact city: vacant land and urban heating in Philadelphia, Pennsylvania, Appl. Geogr., 79 (2017), 84-92.
Rasul, A., Balzter, H., Smith, C., Remedios, J., Adamu, B., Sobrino, J., Srivanit, M. and Weng, Q (2017). A review on remote sensing of urban heat and cool islands. Land. 6, 1-10.
Rodriguez Lopez J.M, Heider K, Scheffran J (2017). Frontiers of urbanization: identifying and explaining urbanization hot spots in the south of Mexico City using human and remote sensing,Appl. Geogr., 79 (2017), 1-10.
Rongali G, Keshari AK, Gosain AK, Khosa R (2018). A mono-window algorithm for land surface temperature estimation from Landsat 8, thermal infrared sensor data: a case study of the Beas River Basin, India. Pertanika J Sci Technol 26:829-840.
https://www.researchgate.net/publication/324982810.
Rongali, Gopinadh & Keshari, Ashok K. & Gosain, Ashwani K. & Rakesh Khosa (2018). Split-Window Algorithm for Retrieval of Land SurfaceTemperature Using Landsat 8 Thermal Infrared Data, Journal of Geovisualization and Spatial Analysis (2018). 2: 14.
Roy B. Bari E., N.J. Nipa, S.A (2021). Ani, Comparison of temporal changes in urban settlements and land surface temperature in Rangpur and Gazipur Sadar, Bangladesh after the establishment of city corporation, Remote Sens. Appl. Soc. Environ., 23 (2021), 100587.
Sharma, A. Conry, P. Fernando, H. Hamlet, A.F. Hellmann, J. & Chen, F (2016). Green and cool roofs to mitigate urban heat island effects in the Chicago metropolitan area: Evaluation with a regional climate model. Environmental Research Letters, (6)11064004(6).
Sobrino JA, El Kharraz J, Li ZL (2003). Surface temperature and water vapor retrieval from MOODIS data. Int J Remote Sens 24:5161-5182.
Sobrino JA, Li Z, Stoll MP, Becker F (1996). Multi-channel and multiangle algorithms for estimating sea and land surface temperature with ATSR data. Int J Remote Sens 17:2089-2114.
Sobrino JA, Romaguera M (2008). Land surface temperature retrieval from MSG1-SEVIRI data. Remote Sens Environ 92:247-254.
Kashki, A., Karami, M., Zandi, R., & Roki, Z (2021). Evaluation of the effect of geographical parameters on the formation of the land surface temperature by applying OLS and GWR, A case study Shiraz City, Iran. Urban Climate, 37, 100832.
Wan Mohd Jaafar WS, Abdul Maulud KN, Muhmad Kamarulzaman AM, Raihan A, Md Sah S, Ahmad A, Saad SNM, Mohd Azmi AT, Jusoh Syukri NKA, Razzaq Khan W (2020). The Influence of Deforestation on Land Surface Temperature-A Case Study of Perak and Kedah, Malaysia. Forests, 11(6): 670.
Weng, Q., Liu, H. and Lu, D (2007). Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis, United States. Urban Ecosystems. 10, 203-219.
Weng, Q., Lu, D.& Schubring, J (2006). Estimation of Land Surface Temperature Vegetation Abundance Relationship for Urban Heat Island Studies, Remote Sensing of Environment, 89(4), 467-483.
Xu, S., Ehlers, M (2017). Hyperspectral image sharpening based on Ehlers fusion.International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W7: 941-947.
https://doi.org/10.5194/isprs-archives-XLII-2-W7-941-2017.
Xu, H., Yunhao, C., Shangming, D., & Wenxia, Q (2011). Dynamical Monitoring and Evaluation Methods to Urban Heat Island Effects Based on RS & GIS. Procedia Environmental Sciences.Volume 10, 1228-1237.
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(6): 1551.
https://doi.org/10.5194/se-7-1551-2016.
Zhang, C., Luo, L., Xu, W., & Ledwith, V (2008). Use of local Moran's I and GIS toidentify pollution hotspots of Pb in urban soils of Galway, Ireland. Science of theTotal Environment, 398(1), 212-221
Zhang, Y. Yiyun, C. Qing, D. & Jiang, P (2012). Study on Urban Heat Island Effect Based on Normalized Difference Vegetated Index: A Case Study of Wuhan City, the 18th Biennial Conference of International Society for Ecological Modeling, Procedia Environmental Sciences 13.
)