Revealing the Trend of the Impact of Urban Development on the Creation of Heat Islands within the Boundaries and Buffer Zone of the National Botanical Garden of Iran

Document Type : Research Paper

Authors

1 Forest Research Division, Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran.

2 Desert Research Division, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran.

3 Iranian Research Institute of Plant Protection, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran.

Abstract

Objective: Botanical gardens are of particular importance worldwide as centers for preserving biodiversity and as genetic and environmental reserves for education, cultural development, scientific research, and tourism. The National Botanical Garden of Iran, with its history spanning more than half a century and a high diversity of native and exotic plants, as well as various animal species, is considered a unique institution in Iran and the Middle East. However, urban development in the area has become a serious threat to its preservation over the past two decades. This study aims to reveal the impact of urban development on the formation of heat islands within the boundaries and buffer zone of the National Botanical Garden of Iran.
Method: In this study, Landsat 8 satellite imagery from five years (1990, 2000, 2010, 2020, and 2025) was used to assess two indices: land surface temperature (LST) and urban thermal field variation index (UTFVI).
Results: The temporal and spatial analysis of temperature over the 35 years from 1990 to 2025 indicated an upward trend. As a result the temperature class above 45 degrees Celsius increased from zero percent in 1990 to 24.55 percent in 2025. The study of spatial trends in the area and territory of the National Botanical Garden of Iran indicated that heat islands have occurred more frequently within the garden. Accordingly, the images of the LST index in 2025 clearly showed that the highest level in the temperature class above 45 degrees Celsius was observed in the garden area. On the other hand, the highest level in the class below 30 degrees Celsius was observed in the garden area. An examination of the spatial and temporal changes in the thermal comfort variance index (UTFVI) showed that over 35 years, the trend in changes in the thermal comfort index in the upper and middle classes within the garden area increased, reaching from 37.47 and 0 percent in 1990 to 45.81 and 1.99 percent in 2025, respectively. However, the bad, worse, and worst classes were mostly within the garden area.
Conclusions: The results of the present study clearly show the role of land-use changes and construction in increasing heat island intensity, and the role of vegetation development in improving thermal comfort. Considering the deterioration and drying of Chitgar Forest Park in the east and southeast of the National Botanical Garden of Iran, which will increase the negative effects of climate change and heat islands, authorities need to prioritize protecting and enhancing vegetation cover to ensure ecological sustainability. Special attention should be given to maintaining diversity and the percentage of vegetation, especially broadleaf trees, within the garden and Chitgar Forest Park, to foster a healthier environment.

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Main Subjects


Ahmadaali, K., Eskandari Damaneh, H., Ababaei, B., & Eskandari Damaneh, H. (2021). Impacts of droughts on rainfall use efficiency in different climatic zones and land uses in Iran. Arabian Journal of Geosciences, 14(2), 126.‏https://doi.org/10.1007/s12517-020-06389-1
Ahmadi, M., Dadashiroudbari, A. & Esfandiari, N. (2019). Monitoring the Urban heat islands with a Fractal Net Evolution (FNEA) Approach (Case Study: Tehran Metropolis). Iranian Journal of Remote Sensing and GIS, 11(1), 93-112. https://doi: 10.52547/gisj.11.1.93 [in Persian]
Akbari, H., & Rose, L. S. (2008). Urban Surfaces and Heat Island Mitigation Potentials. Journal of the Human-Environment System, 11(2), 85–101. https://doi.org/10.1618/JHES.11.85
Aslani, A., Sereshti, M., & Sharifi, A. (2025). Urban heat island mitigation in Tehran: District-based mapping and analysis of key drivers. Sustainable Cities and Society125, 106338.‏ https://doi.org/10.1016/j.scs.2025.106338
Battista, G., & De Lieto Vollaro, R. (2017). Correlation between air pollution and weather data in urban areas: Assessment of the city of Rome (Italy) as spatially and temporally independent regarding pollutants. Atmospheric Environment, 165, 240–247. https://doi.org/10.1016/J.ATMOSENV.2017.06.050
Bian, J., Wang, Y., Li, A., Zhang, Z., Nan, X., Lei, G., ... & Naboureh, A. (2026). Generating high spatio-temporal fractional vegetation cover reference product for the Wanglang mountain area via space-air-ground integration approach. Geo-spatial Information Science, 1-20. https://doi.org/10.1080/10095020.2026.2633647
Bobes-Jesus, V., Pascual-Muñoz, P., Castro-Fresno, D., & Rodriguez-Hernandez, J. (2013). Asphalt solar collectors: A literature review. Applied Energy, 102, 962–970. https://doi.org/10.1016/J.APENERGY.2012.08.050
Chen, G., & Sun, W. (2018). The role of botanical gardens in scientific research, conservation, and citizen science. Plant diversity, 40(4), 181-188.‏‏ https://doi.org/10.1016/j.pld.2018.07.006
Chen, Y., Wang, Y., Zhou, D., & Luo, X. (2025). Regression-based predictive modeling of summer urban microclimate: Quantifying contributions from urban design and urban heat emissions. Urban Climate, 62, 102550. https://doi.org/10.1016/j.uclim.2025.102550
Chenghao, W., Zhi -Hua W., & Jiachuan, Y. (2017). Cooling effect of urban trees on the built environment of contiguous United States. Earth's Future, 6 (8): 1066 -1081.
Duan, X., Haseeb, M., Tahir, Z., Mahmood, S. A., Tariq, A., Jamil, A., Ullah, S., & Abdullah-Al-Wadud, M. (2025). A geospatial and statistical analysis of land surface temperature in response to land use land cover changes and urban heat island dynamics. Scientific Reports, 15(1), 4943. https://doi.org/10.1038/s41598-025-89167-x
Eskandari Damaneh, H., Gholami, H., Khosravi, H., Mahdavi Najafabadi, R., Khoorani, A., & Li, G. (2020). Modeling Spatial and Temporal Changes in Land-Uses and Land Cover of the Urmia Lake Basin Applying Cellular Automata and Markov Chain. Geography and Environmental Sustainability, 10(2), 57-72. https://10.22126/ges.2020.5303.2238 [in Persian]
Eskandari Damaneh, H., Cheraghi, M., Khosravi, H., & Adeli Sardooei, M. (2021a). The effect of land use change on the formation of heat islands using remote sensing (Case study: Kerman). Journal of Natural Environment, 74(3), 614–628. https://doi.org/10.22059/jne.2022.327993.2258 [in Persian]
Eskandari Damaneh, H., Gholami, H., Mahdavi, R., Khorani, A. & Li, J. (2021b). Monitoring Land Degradation and Desertification in the Arid and Semi-arid Regions with an Emphasis in Response to Gross Primary Production Relative to the Climatic Variables during the 2001-2017 in the Province of Fars. Watershed Management Research, 34(1), 41-58. https://10.22092/wmej.2020.342030.1317 [in Persian]
Eskandari Damaneh, H., Khosravi, H., & Eskandari Damaneh, H. (2024). Investigating the land use changes effects on the surface temperature using Landsat satellite data: Melesse, A. M., Rahmati, O., & Khsoravi, K. (Eds.). Remote Sensing of Soil and Land Surface Processes: Monitoring, Mapping, and Modeling. Elsevier, 155–174. https://doi.org/10.1016/B978-0-443-15341-9.00007-1
Fattah, Md. A., & Morshed, S. R. (2022). Assessment of the responses of spatiotemporal vegetation changes to climatic variability in Bangladesh. Theoretical and Applied Climatology, 148(1), 285–301. https://doi.org/10.1007/s00704-022-03943-7
Feng, F., Yang, X., Jia, B., Li, X., Li, X., Xu, C., & Wang, K. (2024). Variability of urban fractional vegetation cover and its driving factors in 328 cities in China. Science China Earth Sciences, 67(2), 466-482. https://doi.org/10.1007/s11430-022-1219-2
Hamzehee, B., Panahi, P., Matinizadeh, M., Dargahian, F., Abbasi, H. & Alizadeh Aliabadi, A. (2023). An overview of the role of buffer zones in the protection and sustainability of natural ecosystems (Case study: National Botanical Garden of Iran). Iranian Journal of Forest and Range Protection Research, 20(2), 219-234. https://doi.org/10.22092/ijfrpr.2022.360457.1558 [in Persian]
Hasan, I., Goni, O., Katha, Z. T., Rabby, M. I., Hossain, S., Banik, A., Hasan, S., & Rahman, I. (2025). Prediction modeling of land surface temperature in relation to land cover dynamics and health risk perception analysis in barishal city of Bangladesh. Scientific Reports, 15(1), 30730. https://doi.org/10.1038/s41598-025-14868-2
Hou, H., Zhou, W., Wang, J., Yu, M., Cao, J., Wang, Y., ... & Wang, Z. H. (2025). Urbanization-induced disparity of extreme heat distribution in metropolitan Beijing. Sustainable Cities and Society, 127, 106458. https://doi.org/10.1016/j.scs.2025.106458
Jamaludin, N. J., Abdullah, A. F., Muhadi, N. A., & Wayayok, A. (2025). Assessment and enhancement of Landsat 8 land surface temperature retrieval using mono window algorithm and machine learning approaches. Journal of Atmospheric and Solar-Terrestrial Physics, 276, 106618. https://doi.org/10.1016/J.JASTP.2025.106618
Koushesh Vatan, M A and Asghari Zamani, A. (2021). Study of land surface temperature concerning land-use in Tabriz city using the Landsat 8 data. Economic Geography Research, 2(3), 49-58. https://doi.org/20.1001.1.27173747.1400.2.1.4.0 [in Persian]
Liu, X., Pei, F., Wen, Y., Li, X., Wang, S., Wu, C., Cai, Y., Wu, J., Chen, J., Feng, K., Liu, J., Hubacek, K., Davis, S. J., Yuan, W., Yu, L., & Liu, Z. (2019). Global urban expansion offsets climate-driven increases in terrestrial net primary productivity. Nature Communications, 10(1), 5558. https://doi.org/10.1038/s41467-019-13462-1
Manna, S., & Sarkar, A. (2025). Quantifying urban Land Surface Temperature (LST) dynamics in an industrial and mining hub of Eastern India using remote sensing and geospatial analysis. Theoretical and Applied Climatology, 150(1–2), 345–362. https://doi.org/10.1007/s00704-025-05386-2
Guerra, B. R., Abrantes, P. C. D. R. M., & Ranieri, V. E. L. (2026). Effective buffer zones to reduce the vulnerability of protected areas: case study of southeastern Brazil. Journal for Nature Conservation, 127278.‏ https://doi.org/10.1016/j.jnc.2026.127278
Mohajerani, A., Bakaric, J., & Jeffrey-Bailey, T. (2017). The urban heat island effect, its causes, and mitigation, with reference to the thermal properties of asphalt concrete. Journal of Environmental Management, 197, 522–538. https://doi.org/10.1016/J.JENVMAN.2017.03.095
Naim, M. N. H., & Kafy, A. A. (2021). Assessment of urban thermal field variance index and defining the relationship between land cover and surface temperature in Chattogram city: A remote sensing and statistical approach. Environmental Challenges, 4, 100107.‏ https://doi.org/10.1016/j.envc.2021.100107
Owen, J. G. (1990). Patterns of mammalian species richness in relation to temperature, productivity, and variance in elevation. Journal of mammalogy, 71(1), 1-13. https://doi.org/10.2307/1381311
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 Sciences, 20(1), 125–145. https://doi.org/10.1016/J.EJRS.2016.11.003
Patra, S., Gavsker, K. K., & Das, T. (2025). Assessing urban landscape dynamics and its relations to changing surface thermal character and prospects: a geospatial study of a tropical industrial city using machine learning algorithms. Environmental Science and Pollution Research, 1-35.‏ https://doi.org/10.1007/s11356-025-36572-4
Qaderi, F., Asadi, P., Tamadoni, A. & Azizi, M. (2018). Evaluation of Sustainability of Development in Zone 22 of Tehran by Ecological Footprint Method. Geography and Development, 16(50), 231-245. https://doi.org/10.22111/gdij.2018.3575 [in Persian]
Saini, J., Gupta, A. K., Dhupper, R., & Shrivastava, A. (2025). Spatio-temporal study of urban dynamics with implications on land surface temperature of Gurugram City, India. Environmental Monitoring and Assessment, 197(8), 946. https://doi.org/10.1007/s10661-025-14392-w
Shahfahad, S., Talukdar, S., Naikoo, M. W., Rihan, M., Mohammad, P., & Rahman, A. (2024). Seasonal dynamics of land surface temperature and urban thermal comfort with land use land cover pattern in semi-arid Indian cities: Insights for sustainable urban management. Urban Climate, 57, 102105. https://doi.org/10.1016/j.uclim. 2024.102105
Suthar, G., Singh, S., Kaul, N., & Khandelwal, S. (2024). Prediction of land surface temperature using spectral indices, air pollutants, and urbanization parameters for Hyderabad city of India using six machine learning approaches. Remote Sensing Applications: Society and Environment, 35. https://doi.org/10.1016/j.rsase.2024.101265
Taiwo, B. E., Kafy, A. A., Samuel, A. A., Rahaman, Z. A., Ayowole, O. E., Shahrier, M., ... & Abosede, O. O. (2023). Monitoring and predicting the influences of land use/land cover change on cropland characteristics and drought severity using remote sensing techniques. Environmental and Sustainability Indicators, 18, 100248. https://doi.org/10.1016/j.indic.2023.100248
Torkaman, J., Ghodskhah Daryaei, M., & Sahranavard, S. (2023). Effects of climatic parameters and air pollutants of Tehran city on the growth of Pinus eldarica in Chitgar forest park during time series (1975-2015). Iranian Journal of Health and Environment, 16(2), 357-366. [in Persian]
Wang, L., & Yang, Z.-L. (2020). Changes in Land Use Influenced by Anthropogenic Activity. Oxford University Press. https://doi.org/10.1093/acrefore/9780199389414.013.37
Zhao, Q., Guo, Y., Ye, T., Gasparrini, A., Tong, S., Overcenco, A., Urban, A., Schneider, A., Entezari, A., Vicedo-Cabrera, A. M., Zanobetti, A., Analitis, A., Zeka, A., Tobias, A., Nunes, B., Alahmad, B., Armstrong, B., Forsberg, B., Pan, S.-C., … & Li, S. (2021). Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study. The Lancet Planetary Health, 5(7), e415–e425. https://doi.org/10.1016/S2542-5196(21)00081-4
Zhu, L., Guo, Z., Xing, H., & Sun, W. (2023). A coupled temporal–spectral–spatial multidimensional information change detection framework method: A case of the 1990–2020 Tianjin, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 5741-5758.‏ https://doi.org/10.1109/JSTARS.2023.3288218