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The effect of different area uses and topography on surface temperature and climate parameters

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Abstract

Global warming and the ecological burden it causes affect people and the environment negatively and make adaptation difficult. For people to adapt to the environment and vice versa, they need to do extensive research and planning. Planning, on the other hand, is taking an easy form with the technology that has recently developed. GIS infrastructures and supporting satellite images along with software help with provincial-scale planning. This study has been handled on a scale covering the provincial borders of Nevsehir. The thermal data of the 10-year-old Landsat 7 satellite was analyzed and mapped in the Arc-GIS 10.2 package program. In the same way, maps of wind, air temperature, topography, and land use were created and the relationship between them was revealed by “Spearman’s correlation” method. According to the results obtained, the average surface temperature in the study area was determined as 34.4 °C. When evaluated in terms of land use, natural grasslands have the highest surface temperature of 40.6 °C, while city structures have the highest average surface temperature of 33.3 °C. At the same time, the lowest surface temperature measured in the study area, 13.8 °C, is also found in natural grassland areas. A significant positive correlation was measured between the wind speed and the land use pattern, while a significant negative correlation emerged between the wind speed and the air temperature. In addition, there is another significant negative correlation between height and land surface temperature (LST). Furthermore, a high degree of positive significance was determined between altitude and wind speed. Finally, between air temperature and LST, a positive significance was observed.

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Data availability

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

References

  • Akbari H, Pomerantz M, Taha H (2001) Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. Sol Energy 70(3):295–310

    Google Scholar 

  • Al-Zahrani HS, Alharby HF, Fahad S (2022) Antioxidative defense system, hormones, and metabolite accumulation in different plant parts of two contrasting rice cultivars as influenced by plant growth regulators under heat stress. Front Plant Sci 13:1–21

  • Anonymous (2020) T.R. Nevşehir provincial special administration. http://www.nevsehirozelidare.gov.tr/yoremizitaniyalim. Accessed 16 Nov 2020

  • Artis DA, Carnahan WH (1982) Survey of emissivity variability in thermography of urban areas. Remote Sens Environ 12:313–329

    Google Scholar 

  • Bamagoos A, Alharby H, Fahad S (2021) Biochar coupling with phosphorus fertilization modifies antioxidant activity, osmolyte accumulation and reactive oxygen species synthesis in the leaves and xylem sap of rice cultivars under high-temperature stress. Physiol Mol Biol Plants 27(9):2083–2100

    CAS  Google Scholar 

  • Bounoua L, Nigro J, Zhang P, Thome K, Lachir A (2018) Mapping urbanization in the United States from 2001 to 2011. Appl Geogr 90:123–133

  • Cao J, Zhou W, Zheng Z, Ren T, Wang W (2021) Within-city spatial and temporal heterogeneity of air temperature and its relationship with land surface temperature. Landscape Urban Plann 206:103979

    Google Scholar 

  • Chamling M, Bera B (2020) Spatio-temporal patterns of land use/land cover change in the Bhutan-Bengal foothill region between 1987 and 2019: study towards geospatial applications and policy making. Earth Syst Environ 4(1):117–130

    Google Scholar 

  • Collados-Lara AJ, Fassnacht SR, Pulido-Velazquez D, Pfohl AK, Morán-Tejeda E, Venable NB, Pardo-Igúzquiza E, Puntenney-Desmond K (2021) Intra-day variability of temperature and its near-surface gradient with elevation over mountainous terrain: comparing MODIS land surface temperature data with coarse and fine scale near-surface measurements. Int J Climatol 41:E1435–E1449

    Google Scholar 

  • Colliander A, Fisher JB, Halverson G, Merlin O, Misra S, Bindlish R, Jackson TJ, Yueh S (2017) Spatial downscaling of SMAP soil moisture using MODIS land surface temperature and NDVI during SMAPVEX15. IEEE Geosci Remote Sens Lett 14(11):2107–2111

    Google Scholar 

  • Deilami K, Kamruzzaman M, Liu Y (2018) Urban heat island effect: a systematic review of spatio-temporal factors, data, methods, and mitigation measures. Int J Appl Earth Observ Geoinform 67:30–42

    Google Scholar 

  • 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. Sci Rep 8(1):1–12

    Google Scholar 

  • Dissanayake D (2020) Land use change and Its impacts on land surface temperature in Galle city, Sri Lanka. Climate 8(5):65

    Google Scholar 

  • Duan S-B, Li Z-L, Li H, Göttsche F-M, Wu H, Zhao W, Leng P, Zhang X, Coll C (2019) Validation of Collection 6 MODIS land surface temperature product using in situ measurements. Remote Sens Environ 225:16–29

    Google Scholar 

  • Ebrahimy H, Azadbakht M (2019) Downscaling MODIS land surface temperature over a heterogeneous area: an investigation of machine learning techniques, feature selection, and impacts of mixed pixels. Comput Geosci 124:93–102

    Google Scholar 

  • Fahad S, Ihsan MZ, Khaliq A, Daur I, Saud, S, Alzamanan S, ..., Wu C (2018) Consequences of high temperature under changing climate optima for rice pollen characteristics-concepts and perspectives. Arch Agron Soil Sci 64(11):1473–1488

  • Fick SE, Hijmans RJ (2017) WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas. Int J Climatol 37(12):4302–4315

    Google Scholar 

  • Global Solar Atlas (2022) https://globalsolaratlas.info/map. Accessed 02 Jun 2021

  • Global Wind Atlas (2022) https://globalwindatlas.info. Accessed 02 Jun 2021

  • Govind NR, Ramesh H (2020) Exploring the relationship between LST and land cover of Bengaluru by concentric ring approach. Environ Monit Assess 192(10):1–25

    Google Scholar 

  • Guha S, Govil H, Gill N, Dey A (2020) Analytical study on the relationship between land surface temperature and land use/land cover indices. Ann GIS 26(2):201–216

    Google Scholar 

  • Gul F, Ahmed I, Ashfaq M, Jan D, Fahad S, Li X, ..., Shah SA (2020) Use of crop growth model to simulate the impact of climate change on yield of various wheat cultivars under different agro-environmental conditions in Khyber Pakhtunkhwa, Pakistan. Arab J Geosc 13(3):1–14

  • Gülersoy AE (2014) 2014, Seferihisar’da arazi kullanımının zamansal değişimi (1984–2010) ve ideal arazi kullanımı için öneriler. Süleyman Demirel Üniversitesi Fen-Edebiyat Fakültesi Sosyal Bilimler Dergisi 31:155–180

    Google Scholar 

  • Guo A, Yang J, Xiao X, Xia J, Jin C, Li X (2020) Influences of urban spatial form on urban heat island effects at the community level in China. Sustain Cities Soc 53:101972

    Google Scholar 

  • Hengl T, Heuvelink GB, Tadić MP, Pebesma EJ (2012) Spatio-Temporal Prediction of Daily Temperatures Using Time-Series of MODIS LST Images. Theor Appl Climatol 107(1):265–277

    Google Scholar 

  • Hobbs RJ, Harris JA (2001) Restoration Ecology: Repairing the Earth’s Ecosystems in the New Millennium. Restor Ecol 9(2):239–246

    Google Scholar 

  • Hussain I, Ali M, Ghoneim AM, Shahzad K, Farooq O, Iqbal S, ..., Brestic M (2022) Improvement in growth and yield attributes of cluster bean through optimization of sowing time and plant spacing under climate change scenario. Saudi J Biol Sci 29(2):781–792

  • Jiang J, Tian G (2010) Analysis of the impact of land use/land cover change on land surface temperature with remote sensing. Proc Environ Sci 2:571–575

    Google Scholar 

  • Karger DN, Conrad O, Böhner J, Kawohl T, Kreft H, Soria-Auza RW, Zimmermann NE, Linder HP, Kessler M (2017) Climatologies at high resolution for the earth’s land surface areas. Sci Data 4(1):1–20

    Google Scholar 

  • Khalaf FI, Al-Awadhi J, Misak RF (2013) Land-use planning for controlling land degradation in Kuwait. In: Shahid S, Taha F, Abdelfattah M (eds) Developments in soil classification, land use planning and policy implications. Springer, Dordrecht https://doi.org/10.1007/978-94-007-5332-7_39

  • Kim HH (1992) Urban heat island. Int J Remote Sens 13(12):2319–2336

    Google Scholar 

  • Koc A, Karahan A, Bingül M (2019) Determination of relationship between land surface temperature and different land use by chaid analysis. Appl Ecol Environ Res 17(3):6051–6067

    Google Scholar 

  • Koç A, Caf A, Koç C et al (2022) Examining the temporal and spatial distribution of potential urban heat island formations. Environ Sci Pollut Res 29:55–68

  • Kumari M, Sarma K, Sharma R (2019) Using Moran’s I and GIS to study the spatial pattern of land surface temperature in relation to land use/cover around a thermal power plant in Singrauli district Madhya Pradesh, India. Remote Sens Appl Soc Environ 15:100239

    Google Scholar 

  • Kwak Y, Park C, Deal B (2020) Discerning the success of sustainable planning: a comparative analysis of urban heat island dynamics in Korean new towns. Sustain Cities Soc 61:102341

    Google Scholar 

  • Landsat Project Science Office (2002) Landsat 7 science data user’s handbook (Goddard Space Flight Center). Available online at: https://www.usgs.gov/media/files/landsat-7-data-usershandbook. Accessed 11 Oct 2021

  • Li X, Zhou W, Ouyang Z (2013) Relationship between land surface temperature and spatial pattern of greenspace: what are the effects of spatial resolution? Landscape Urban Plann 114:1–8

    Google Scholar 

  • Li H, Zhou Y, Li X, Meng L, Wang X, Wu S, Sodoudi S (2018) A new method to quantify surface urban heat island intensity. Sci Total Environ 624:262–272

    CAS  Google Scholar 

  • Li W, Ni L, Li Z-L, Duan S-B, Wu H (2019a) Evaluation of machine learning algorithms in spatial downscaling of MODIS land surface temperature. IEEE J Select Topics Appl Earth Observ Remote Sens 12(7):2299–2307

    Google Scholar 

  • Li X, Zhou Y, Yu S, Jia G, Li H, Li W (2019b) Urban heat island impacts on building energy consumption: a review of approaches and findings. Energy 174:407–419

  • Lu Y, Wu P, Ma X, Li X (2019) Detection and prediction of land use/land cover change using spatiotemporal data fusion and the cellular automata–Markov model. Environ Monit Assess 191(2):68

    Google Scholar 

  • Lv ZQ, Zhou QG (2011) Utility of Landsat image in the study of land cover and land surface temperature change. 2011 3rd Int Conf Environ Sci Inform Appl Technol Esiat 10(PT B):1287–1292

    Google Scholar 

  • Mumtaz F, Tao Y, de Leeuw G, Zhao L, Fan C, Elnashar A, Bashir B, Wang G, Li L, Naeem S (2020) Modeling spatio-temporal land transformation and its associated impacts on land surface temperature (LST). Remote Sens 12(18):2987

    Google Scholar 

  • Neteler M (2010) Estimating Daily Land Surface Temperatures in mountainous environments by reconstructed MODIS LST Data. Remote Sens 2(1):333–351

    Google Scholar 

  • Olsson L, Barbosa H, Bhadwal S, Cowie A, Delusca K, Flores-Renteria D, Hermans K, Jobbagy E, Kurz W, Li D, Sonwa DJ, Stringer L (2019) Land degradation: IPCC special report on climate change, desertification, land 5 degradation, sustainable land management, food security, and 6 greenhouse gas fluxes in terrestrial ecosystems. In: IPCC special report on climate change, desertification, land 5 degradation, sustainable land management, food security, and 6 greenhouse gas fluxes in terrestrial ecosystems. Intergovernmental Panel on Climate Change (IPCC), p 1

  • Öztürk MA, Mermut AR, Celik A (2013) Urbanisation land use land degradation and environment. Publishing House, Daya

    Google Scholar 

  • Phu NM and Hap NV (2020) Influence of inlet water temperature on heat transfer and pressure drop of dehumidifying air coil using analytical and experimental methods Case Stud Thermal Eng 18

  • Southworth J (2004) An assessment of Landsat TM band 6 thermal data for analysing land cover in tropical dry forest regions. Int J Remote Sens 25(4):689–706

    Google Scholar 

  • Sun Q, Wu Z, Tan J (2012) The relationship between land surface temperature and land use/land cover in Guangzhou, China. Environ Earth Sci 65(6):1687–1694

    Google Scholar 

  • Tafesse B, Suryabhagavan K (2019) Systematic modeling of impacts of land-use and land-cover changes on land surface temperature in Adama Zuria District. Ethiop Model Earth Syst Environ 5(3):805–817

    Google Scholar 

  • Tran DX, Pla F, Latorre-Carmona P, Myint SW, Gaetano M, Kieu HV (2017) Characterizing the relationship between land use land cover change and land surface temperature. Isprs J Photogramm Remote Sens 124:119–132

    Google Scholar 

  • Ullah S, Ahmad K, Sajjad RU, Abbasi AM, Nazeer A, Tahir AA (2019) Analysis and simulation of land cover changes and their impacts on land surface temperature in a lower Himalayan region. J Environ Manag 245:348–357

    Google Scholar 

  • ur Rahman MH, Ahmad A, Wajid A, Hussain M, Rasul F, Ishaque W, ..., Ullah A (2019). Application of CSM-CROPGRO-Cotton model for cultivars and optimum planting dates: evaluation in changing semi-arid climate. Field Crops Res 238:139-152

  • USGS (2014) http://www.usgs.gov/lansat-missions/landsat-7. Accessed 2 Feb 2022

  • Vancutsem C, Ceccato P, Dinku T, Connor SJ (2010) Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa. Remote Sens Environ 114(2):449–465

    Google Scholar 

  • Wang C, Li Y, Myint SW, Zhao Q, Wentz EA (2019) Impacts of spatial clustering of urban land cover on land surface temperature across Köppen climate zones in the contiguous United States. Landscape Urban Plann 192:103668

    Google Scholar 

  • Weng Q, Lu D, Schubring J (2004) Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sens Environ 89(4):467–483

    Google Scholar 

  • Yang J, Ren J, Sun D, Xiao X, Xia JC, Jin C, Li X (2021) Understanding land surface temperature impact factors based on local climate zones. Sustain Cities Soci 69:102818

    Google Scholar 

  • Yıldız ND, Avdan U, Yılmaz S, Matzarakis A (2018) Thermal map assessment under climate and land use changes a case study for Uzundere Basin. Environ Sci Pollut Res 25(1):940–951

    Google Scholar 

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All the authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Associate Professor Esra Özhancı and Associate Professor Ahmet Koç. The first draft of the manuscript was written by Associate Professor Esra Özhancı, and all the authors commented on previous versions of the manuscript. All the authors read and approved the final manuscript.

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Correspondence to Esra Özhancı.

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Özhancı, E., Koç, A. The effect of different area uses and topography on surface temperature and climate parameters. Environ Sci Pollut Res 30, 47038–47051 (2023). https://doi.org/10.1007/s11356-023-25580-x

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