An investigation of the relationship between land surface temperatures, geographical and environmental characteristics, and biophysical indices from Landsat images

Subject Areas : Geospatial systems development

Abbasali Vali ¹ (Assoc. Prof. Department of Desert Management, Faculty of Natural Resource and Earth Sciences, University of Kashan)
Abolfazl Ranjbar ² (Assoc. Prof. Department of Desert Management, Faculty of Natural Resource and Earth Sciences, University of Kashan)
Marzieh Mokarram ³ (Assist. Prof. Department of Geomorphology, Darab School of Agriculture and Natural Resources, Shiraz University)
Farideh Taripanah ⁴ (PhD Student of Desertification Combating, Faculty of Natural Resource and Earth Sciences, University of Kashan)

Received: 2019-06-19 Accepted : 2019-08-09 Published : 2019-09-23

Keywords: Land surface temperature (LST), Normalized difference vegetation index (NDVI), Normalized difference moisture index (NDMI), Kharestan, Landsat images,

Abstract :

Land surface temperature (LST) is an important indicator of habitat quality assessment for a local and global scale. In the present study, the effects of multiple factors on land use, geological formations, topographical and climate factors on LST in Kharestan region were investigated. To this end, images of July Landsat 7 and 8 satellites during the period 2000-2017, digital elevation model, geological map and topography were used. The surface temperature was extracted using a split-window method and also land use extracted from the supervised classification method which has been done in 2017. The correlation between surface temperature and elevation, aspect, slope, vegetation, soil moisture, and air temperature variables was investigated using statistical methods. The results indicated that the surface temperature average was 43 °C, Normalized difference vegetation index (NDVI) was 0.144 and Normalized difference moisture index (NDMI) was 0.068. According to the classification of images with an overall accuracy of 99.96% and kappa coefficients of 0.96, pasture and horticultural land cover the highest and lowest area, respectively. The highest surface temperature, 53 °C was observed in bare soil and residential areas and the lowest 29 °C in horticultural land. Moreover, the highest and lowest surface temperatures were related to Pabdeh-Gurpi and Asmari formations, respectively. In sunny slopes, the highest correlation, R2>0.5 was observed between surface temperature, elevation, temperature, vegetation, and surface moisture. Furthermore, in shady slopes, the surface temperature had the highest correlation, R2>0.5 with elevation, temperature, and vegetation. Among the above factors, elevation and temperature had the most influence on surface temperature. In addition, the correlation between vegetation index and a normalized moisture index with inverse surface temperature was >0.9. Also, the correlation between surface temperature and the air temperature was positive. Therefore, land use, geology, topography, vegetation, soil moisture, and air temperature are important factors in ecosystem temperature equilibrium. 

References:

ابراهیمی، ح.، ا. گندم‌کار، ع. المدرسی و م. ح. رامشت. 1395. برآورد دمای سطح زمین و تأثیر پوشش گیاهی بر دمای سطح با استفاده از تصاویر مودیس (مطالعه موردی: حوزه تویسرکان). فصلنامه جغرافیا (برنامه‌ریزی منطقه ­ای)، 6(4): 23-32.

اصغری سراسکانرود، ص. و ه. امامی. 1396. پایش دمای سطح زمین و بررسی رابطه کاربری اراضی با دمای سطح با استفاده از تصاویر سنجنده ⁺ETM و OLI (مطالعه موردی: شهرستان اردبیل). نشریه تحقیقات کاربردی علوم جغرافیایی، 19(53): 195-215.

اکبری، ا.، م. ابراهیمی، ح. نژاد سلیمانی و ب. فیضی­زاده. 1394. ارزیابی دمای سطح زمین در ارتباط با روند تغییرات کاربری اراضی با استفاده از تصاویر ماهواره‌ای (مطالعه موردی: حوزه آبخیز طالقان). جغرافیا و برنامه‌ریزی محیطی، 26(4): 151-170.

بهرامی، ش.، ا. اکبری و ع. دوران. 1392. بررسی تأثیر عوامل جغرافیایی بر حرارت سطحی زمین با استفاده از تصاویر ماهواره­ای در مخروط آتشفشان تفتان. نشریه سنجش‌ازدور و سامانه اطلاعات جغرافیایی در منابع طبیعی، 4(4): 11-24.

حمزه، س.، ن. میجانی و م. کریمی فیروزجانی. 1397. مدل ­سازی ارتباط دمای سطح زمین، شرایط توپوگرافی و پوشش گیاهی با استفاده از تصاویر ماهواره­ای لندست 8. پژوهش­های جغرافیای طبیعی، 50(1): 35-55.

درویشی، ش.، ک. سلیمانی و م. رشیدپور. 1398. تأثیر شاخص ­های گیاهی و خصوصیات سطح شهری بر تغییرات دمای سطح زمین (مطالعه موردی: شهرستان سنندج). نشریه سنجش‌ازدور و سامانه اطلاعات  جغرافیایی در منابع طبیعی، 10(1): 17-35.

فاطمی، ب. و ی. رضایی. 1391. مبانی سنجش‌ازدور. چاپ سوم، انتشارات آزاده،  269 صفحه.

قربان نیا خیبری، و.، م. م. میرسنجری،  ه.  لیاقتی و م.  آرمین. 1396. برآورد دمای سطح زمین کاربری اراضی و پوشش زمین شهرستان دنا با استفاده از الگوریتم پنجره مجزا و داده­ های ماهواره لندست. فصلنامه علوم محیطی، 15(4): 55-74.

کیانی سلمی، ا. و ع. ابراهیمی. 1397. ارزیابی تأثیر توسعه شهری و تغییرات پوشش اراضی بر دمای سطح زمین در شهر شهرکرد. نشریه سنجش از در و سامانه اطلاعات جغرافیایی در منابع طبیعی، 9(4): 102-118.

ملک پور، پ. و م. طالعی. 1389. بررسی تغییرات درجه حرارت سطح و پوشش- کاربری زمین شهری با استفاده از داده ­های سنجنده ⁺ETM (مطالعه موردی: شهر تهران). نشریه سنجش‌ازدور و GIS ایران، 2(3): 89-102.

میجانی، ن.، س. حمزه و م. کریمی فیروزجانی. 1398. کمی ­سازی تأثیر پارامترهای سطحی و شرایط اقلیمی بر دمای سطح زمین با استفاده از داده‌های انعکاسی و حرارتی سنجش‌ازدور. نشریه سنجش‌ازدور و سامانه اطلاعات  جغرافیایی در منابع طبیعی، 10(1): 36-59.

Alemu MM. 2019. Analysis of spatio-temporal land surface temperature and normalized difference vegetation index changes in the Andassa watershed, Blue Nile Basin, Ethiopia. Journal of Resources and Ecology, 10(1): 77-86.

Artis DA, Carnahan WH. 1982. Survey of emissivity variability in thermography of urban areas. Remote Sensing of Environment, 12(4): 313-329.

Babalola O, Akinsanola A. 2016. Change detection in land surface temperature and land use /land cover over Lagos Metropolis, Nigeria. Journal of Remote Sensing & GIS, 5(2): 1-7.

Deng Y, Wang S, Bai X, Tian Y, Wu L, Xiao J, Chen F, Qian Q. 2018. Relationship among land surface temperature and LUCC, NDVI in typical karst area. Scientific Reports, 8(1): 641-653.

Estoque RC, Murayama Y, Myint SW. 2017. Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment, 577: 349-359.

Fatemi M, Narangifard M. 2019. Monitoring LULC changes and its impact on the LST and NDVI in District 1 of Shiraz City. Arabian Journal of Geosciences, 12(4): 127.

Feizizadeh B, Blaschke T, Nazmfar H, Akbari E, Kohbanani HR. 2013. Monitoring land surface temperature relationship to land use/land cover from satellite imagery in Maraqeh County, Iran. Journal of Environmental Planning and Management, 56(9): 1290-1315.

Feng Y, Gao C, Tong X, Chen S, Lei Z, Wang J. 2019. Spatial patterns of land surface temperature and their influencing factors: a case study in Suzhou, China. Remote Sensing, 11(2): 182-194.

Ferrelli F, Cisneros MAH, Delgado AL, Piccolo MC. 2018. Spatial and temporal analysis of the LST-NDVI relationship for the study of land cover changes and their contribution to urban planning in Monte Hermoso, Argentina. Documents d'anàlisi geogràfica, 64(1): 25-47.

He J, Zhao W, Li A, Wen F, Yu D. 2019. The impact of the terrain effect on land surface temperature variation based on Landsat-8 observations in mountainous areas. International Journal of Remote Sensing, 40(5-6): 1808-1827.

Ibrahim M, Abu-Mallouh H. 2018. Estimate land surface temperature in relation to land use types and geological formations using spectral remote sensing data in northeast Jordan. Open Journal of Geology, 8(02): 174-185.

Karimi A, Pahlavani P, Bigdeli B. 2017. Land use analysis on land surface temperature in urban areas using a geographically weighted regression and landsat 8 imagery, A case study: Tehran, Iran. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-4/W4, 2017, Tehran's Joint ISPRS Conferences of GI Research, SMPR and EOEC 2017, 7–10 October 2017, Tehran, Iran

Kayet N, Pathak K, Chakrabarty A, Sahoo S. 2016. Spatial impact of land use/land cover change on surface temperature distribution in Saranda Forest, Jharkhand. Modeling Earth Systems and Environment, 2(3): 127-139.

Li Z, Duan S, Tang B, Wu H, Ren H, Yan G, Tang R, Leng P. 2016. Review of methods for land surface temperature derived from thermal infrared remotely sensed data. Journal of Remote Sensing, 20: 899-920.

Lu Y, Feng X, Xiao P, Shen C, Sun J. 2009. Urban heat island in summer of Nanjing based on TM data. In: 2009 Joint Urban Remote Sensing Event. IEEE, pp 1-5.

Markham BL, Barker JL. 1985. Spectral characterization of the Landsat Thematic Mapper sensors. International Journal of Remote Sensing, 6(5): 697-716.

Mushore TD, Odindi J, Dube T, Mutanga O. 2017. Prediction of future urban surface temperatures using medium resolution satellite data in Harare metropolitan city, Zimbabwe. Building and Environment, 122: 397-410.

Mutiibwa D, Strachan S, Albright T. 2015. Land surface temperature and surface air temperature in complex terrain. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(10): 4762-4774.

Nurwanda A, Honjo T. 2018. Analysis of land use change and expansion of surface urban heat island in Bogor city by remote sensing. ISPRS International Journal of Geo-Information, 7(5): 165-178.

Oluseyi IO, Olusegun AJ. 2011. Managing land use transformation and land surface temperature change in Anyigba Town, Kogi State, Nigeria. Journal of Geography and Geology, 3(1): 77-85.

Pal S, 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.

Patil A, Panhalkar S, Bagwan S, Bansode S. 2019. Impact of land use/landcover change on land surface temperature using geoinformatics techniques. International Journal of Research and Analytical Reviews (IJRAR), 5(4): 551-559.

Peng W, Zhou J, Wen L, Xue S, Dong L. 2017. Land surface temperature and its impact factors in Western Sichuan Plateau, China. Geocarto International, 32(8): 919-934.

Ramachandra T, Kumar U. 2010. Greater bangalore: emerging urban heat island. GIS Development, 14(1): 86-104.

Ranagalage M, Simwanda M, Estoque RC, Murayama Y. 2019. Spatial analysis of surface urban heat islands in four rapidly growing African cities. Remote Sensing, 11(14): 1645-1658.

Rouse Jr JW, Haas R, Schell J, Deering D. 1974. Monitoring vegetation systems in the Great Plains with ERTS. Paper presented at the Third Earth Resources Technology Satellite-1 Symposium. Volume 1: Technical Presentations, section A, Texas A&M Univ.; College Station, TX, United States, NASA; United States, Vol. 1, Sect. A p 309-317 (SEE N74-30705 20-13),

Sheng J, Wilson JP, Lee S. 2009. Comparison of land surface temperature (LST) modeled with a spatially-distributed solar radiation model (SRAD) and remote sensing data. Environmental Modelling & Software, 24(3): 436-443.

Sobrino JA, Jimenez-Munoz JC, Paolini L. 2004. Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90(4): 434-440.

Sun D, Kafatos M. 2007. Note on the NDVI‐LST relationship and the use of temperature‐related drought indices over North America. Geophysical Research Letters, 34(24).

Tian Y, Bai X, Wang S, Qin L, Li Y. 2017. Spatial-temporal changes of vegetation cover in Guizhou Province, Southern China. Chinese Geographical Science, 27(1): 25-38.

Wang H, Zhang Y, Tsou J, Li Y. 2017. Surface urban heat island analysis of Shanghai (China) based on the change of land use and land cover. Sustainability, 9(9): 1538.

Xiao F, Li Y-Z, Yun D, Feng L, Yi Y, Qi F, Xuan B. 2014. Monitoring perennial sub-surface waterlogged croplands based on MODIS in Jianghan Plain, middle reaches of the Yangtze River. Journal of Integrative Agriculture, 13(8): 1791-1801.

XU H-Q. 2005. A study on information extraction of water body with the modified normalized difference water index (MNDWI). Journal of Remote Sensing, 5: 589-595.

Yuan F, Bauer ME. 2007. Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sensing of Environment, 106(3): 375-386.

Zaharaddeen I, Baba II, Zachariah A. 2016. Estimation of land surface temperature of Kaduna metropolis, Nigeria using Landsat images. Science World Journal, 11(3): 36-42.

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): 1551-1564.

Zhang B, Gao J-x, Yang Y. 2014. The cooling effect of urban green spaces as a contribution to energy-saving and emission-reduction: A case study in Beijing, China. Building and Environment, 76: 37-43.

Zhang F, Kung H, Johnson VC, LaGrone BI, Wang J. 2018. Change detection of land surface temperature (LST) and some related parameters using landsat image: a case study of the Ebinur Lake watershed, Xinjiang, China. Wetlands, 38(1): 65-80.

Zhang X, Estoque RC, Murayama Y. 2017. An urban heat island study in Nanchang City, China based on land surface temperature and social-ecological variables. Sustainable Cities and Society, 32: 557-568.

Zheng H, Chen Y, Pan W, Cai Y, Chen Z. 2019. Impact of Land Use/Land Cover Changes on the Thermal Environment in Urbanization: A Case Study of the Natural Wetlands Distribution Area in Minjiang River Estuary, China. Polish Journal of Environmental Studies, 28(4): 3025-3041.