Journals / Türkiye Uzaktan Algılama Dergisi / 2026 / Volume: 8

Spatial effects of urban road network development on land surface temperature and vegetation dynamics: The case of Selçuklu district (2015–2025)

Taha Kağan Aydın(KONYA TEKNİK ÜNİVERSİTESİ)0000-0001-6903-0847
Pages
—
Publication Date
2026-07-03
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings indicate that the total road network length increased by 28.75% (approximately 360 km) over the ten-year period.

📌 3 Key Takeaways

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Objective & Hypothesis:In the Selçuklu district of Konya province, changes associated with the expanding road network, together with variations in Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) between 2015 and 2025, were evaluated.
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Key Findings & Data:Landsat satellite data were processed on the Google Earth Engine (GEE) platform, and NDVI and LST analyses were conducted for the summer months (June–July–August) of 2015 and 2025.
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Conclusion & Impact:The findings indicate that the total road network length increased by 28.75% (approximately 360 km) over the ten-year period.
🔬Design:Research Article
📍Scope:2015 Verileri
⚙️Variables:Urban road network · LST · NDVI

Abstract

In the Selçuklu district of Konya province, changes associated with the expanding road network, together with variations in Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) between 2015 and 2025, were evaluated. In this context, Remote Sensing (RS) and Geographic Information System (GIS) techniques were employed to assess the relationship between transportation infrastructure transformation and changes in the urban thermal environment and vegetation dynamics. Landsat satellite data were processed on the Google Earth Engine (GEE) platform, and NDVI and LST analyses were conducted for the summer months (June–July–August) of 2015 and 2025. Road network data were obtained from OpenStreetMap (OSM) via the Overpass Turbo interface, and spatial analyses were carried out in the ArcGIS environment. The findings indicate that the total road network length increased by 28.75% (approximately 360 km) over the ten-year period. This increase was mainly concentrated in residential, track, and secondary road classes, reflecting the acceleration of urban expansion processes. In parallel, a significant rise in surface temperatures was observed, with median LST values increasing from 33.38°C to 42.12°C. NDVI analyses revealed generally limited overall change, although the median NDVI value increased by approximately 7.86%. However, spatial variations indicate vegetation loss in areas of intense urban development. Consistent with the inverse relationship between NDVI and LST, areas with reduced vegetation exhibited higher temperature increases, whereas lower temperature values were observed in areas with dense vegetation. Overall, the results demonstrate that road network expansion has significant implications not only for transportation development but also for urban thermal conditions and vegetation patterns. Integrating environmental indicators such as LST and NDVI into road network planning can support decision-makers in mitigating urban heat accumulation, optimizing transportation networks, and promoting sustainable urban development.

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Cite This Article

Aydın, T. K. (2026). Spatial effects of urban road network development on land surface temperature and vegetation dynamics: The case of Selçuklu district (2015–2025). Türkiye Uzaktan Algılama Dergisi, Volume: 8. https://doi.org/10.51489/tuzal.1935050

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References (29)

  1. Azizi, P., Soltani, A., Bagheri, F., Sharifi, S., & Mikaeili, M. (2022). An integrated modelling approach to urban growth and land use/cover change. Land, 11(10), 1715. https://doi.org/10.3390/land11101715
  2. Cai, X., Wu, Z., & Cheng, J. (2013). Using kernel density estimation to assess the spatial pattern of road density and its impact on landscape fragmentation. International Journal of Geographical Information Science, 27(2), 222-230. https://doi.org/10.1080/13658816.2012.663918
  3. Carlucci, M., Ferrara, C., Rontos, K., Zambon, I., & Salvati, L. (2020). The long breadth of cities: Revisiting worldwide urbanization patterns, 1950–2030. Applied Economics, 52(38), 4162-4174. https://doi.org/10.1080/00036846.2020.1731410
  4. Chen, S. P., Li, Y., Zhang, H. X., Yang, J., & Yang, J. (2017). Study on urban form spatial differentiation based on road density analysis: a case study of Guangzhou, China. Advances in Transportation Studies, 1(Special).
  5. Faiyetole, A. A., & Adewumi, V. A. (2024). Urban expansion and transportation interaction: Evidence from Akure, southwestern Nigeria. Environment and Planning B: Urban Analytics and City Science, 51(1), 57-74. https://doi.org/10.1177/23998083231169427
  6. Gu, D., Andreev, K., & Dupre, M. E. (2021). Major trends in population growth around the world. China CDC Weekly, 3(28), 604. https://doi.org/10.46234/ccdcw2021.160
  7. Guo, J., Wang, W., Lyu, F., Jia, S., Liang, D., & Guo, H. (2026). Moderating mechanisms of urban environment and vegetation structure in the cooling effect of urban green space: A case study of Glasgow. Sustainable Cities and Society, 107120. https://doi.org/10.1016/j.scs.2026.107120
  8. Guo, Z., Esperon-Rodriguez, M., Davin, E., Huang, H., Chen, B., Hejazi, M.,. & Zhou, Y. (2026). Global urban vegetation exhibits divergent thermal effects: From cooling to warming as aridity increases. Science Advances, 12(1), eaea9165. https://doi.org/10.1126/sciadv.aea9165
  9. Hasyim, A. W., Sukojo, B. M., Anggraini, I. A., Fatahillah, E. R., & Isdianto, A. (2025). Urban heat island effect and sustainable planning: Analysis of land surface temperature and vegetation in Malang City. International Journal of Sustainable Development and Planning, 20(2), 683-697. https://doi.org/10.18280/ijsdp.200218
  10. Henderson, V. (2003). The urbanization process and economic growth: The so-what question. Journal of Economic Growth, 8(1), 47-71. https://doi.org/10.1023/A:1022860800744
  11. Kara, Y., & Yavuz, V. (2025). Urban microclimates in a warming world: land surface temperature (LST) trends across ten major cities on seven continents. Urban Science, 9(4), 115. https://doi.org/10.3390/urbansci9040115
  12. Li, H., Li, Y., Wang, T., Wang, Z., Gao, M., & Shen, H. (2021). Quantifying 3D building form effects on urban land surface temperature and modeling seasonal correlation patterns. Building and Environment, 204, 108132. https://doi.org/10.1016/j.buildenv.2021.108132
  13. Lu, D., Song, K., Zang, S., Jia, M., Du, J., & Ren, C. (2015). The effect of urban expansion on urban surface temperature in Shenyang, China: An analysis with landsat imagery. Environmental Modeling & Assessment, 20(3), 197-210. https://doi.org/10.1007/s10666-014-9426-2
  14. Maity, B., Mallick, S. K., & Rudra, S. (2021). Integration of urban expansion with hybrid road transport network development within Haldia Municipality, West Bengal. The Egyptian Journal of Remote Sensing and Space Science, 24(3), 471-483. https://doi.org/10.1016/j.ejrs.2020.10.005
  15. Mann, D., Rankavat, S., & Joshi, P. K. (2022). Road network drives urban ecosystems-a longitudinal analysis of impact of roads in the central Himalaya. Geocarto International, 37(4), 1100-1125. https://doi.org/10.1080/10106049.2020.1750064
  16. Roba, Z. R., & Tabor, K. W. (2025). Geospatial analysis of vegetation and land surface temperature for urban heat island mitigation in Hawassa City, Ethiopia. Scientific Reports, 15(1), 31786. https://doi.org/10.1038/s41598-025-17014-0
  17. Shu, B., Chen, Y., Zhang, K. X., Dehghanifarsani, L., & Amani-Beni, M. (2024). Urban engineering insights: Spatiotemporal analysis of land surface temperature and land use in urban landscape. Alexandria Engineering Journal, 92, 273-282. https://doi.org/10.1016/j.aej.2024.02.066
  18. Singh, P., Verma, P., Chaudhuri, A. S., Singh, V. K., & Rai, P. K. (2024). Evaluating the relationship between Urban Heat Island and temporal change in land use, NDVI and NDBI: a case study of Bhopal city, India. International Journal of Environmental Science and Technology, 21(3), 3061-3072. https://doi.org/10.1007/s13762-023-05141-y
  19. Tanoori, G., Soltani, A., & Modiri, A. (2024). Machine learning for urban heat island (UHI) analysis: Predicting land surface temperature (LST) in urban environments. Urban Climate, 55, 101962. https://doi.org/10.1016/j.uclim.2024.101962
  20. Ullah, M., Li, J., & Wadood, B. (2020). Analysis of urban expansion and its impacts on land surface temperature and vegetation using RS and GIS, a case study in Xi’an City, China. Earth Systems and Environment, 4(3), 583-597. https://doi.org/10.1007/s41748-020-00166-6
  21. Wang, Z., Han, Q., & de Vries, B. (2019). Land use/land cover and accessibility: Implications of the correlations for land use and transport planning. Applied Spatial Analysis and Policy, 12(4), 923-940. https://doi.org/10.1007/s12061-018-9278-2
  22. Xu, H. (2010). Analysis of impervious surface and its impact on urban heat environment using the normalized difference impervious surface index (NDISI). Photogrammetric Engineering & Remote Sensing, 76(5), 557-565. https://doi.org/10.14358/PERS.76.5.557
  23. Yang, H., Xi, C., Zhao, X., Mao, P., Wang, Z., Shi, Y.,. & Li, Z. (2020). Measuring the urban land surface temperature variations under Zhengzhou city expansion using landsat-like data. Remote Sensing, 12(5), 801. https://doi.org/10.3390/rs12050801
  24. Yue, W., Xu, J., Tan, W., & Xu, L. (2007). The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat 7 ETM+ data. International Journal of Remote Sensing, 28(15), 3205-3226. https://doi.org/10.1080/01431160500306906
  25. Zehawi, R. N., & Hameed, A. H. (2022). The impact of urban growth pattern on local road network: A system dynamics study. International Journal of Design & Nature and Ecodynamics, 17(2), 221-231. https://doi.org/10.18280/ijdne.170208
  26. Zhang, T., Xu, R., & Ye, J. (2026). Spatial heterogeneity of the relationship between NDVI and LST under urban land use patterns—a case study of Shanghai (2000–2024). Environmental Monitoring and Assessment, 198(2), 171. https://doi.org/10.1007/s10661-026-14997-9
  27. Zhao, G., Zheng, X., Yuan, Z., & Zhang, L. (2017). Spatial and temporal characteristics of road networks and urban expansion. Land, 6(2), 30. https://doi.org/10.3390/land6020030
  28. Guo, Z., Esperon-Rodriguez, M., Davin, E., Huang, H., Chen, B., Hejazi, M.,. & Zhou, Y. (2026). Global urban vegetation exhibits divergent thermal effects: From cooling to warming as aridity increases. Science Advances, 12(1), eaea9165. https://doi.org/10.1126/sciadv.aea9165
  29. Yang, H., Xi, C., Zhao, X., Mao, P., Wang, Z., Shi, Y.,. & Li, Z. (2020). Measuring the urban land surface temperature variations under Zhengzhou city expansion using landsat-like data. Remote Sensing, 12(5), 801. https://doi.org/10.3390/rs12050801