Skip to main content

Advertisement

SpringerLink
Log in

Analyzing the effects of urban expansion on land surface temperature patterns by landscape metrics: a case study of Isfahan city, Iran

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Urban expansion can cause extensive changes in land use and land cover (LULC), leading to changes in temperature conditions. Land surface temperature (LST) is one of the key parameters that should be considered in the study of urban temperature conditions. The purpose of this study was, therefore, to investigate the effects of changes in LULC due to the expansion of the city of Isfahan on LST using landscape metrics. To this aim, two Landsat 5 and Landsat 8 images, which had been acquired, respectively, on August 2, 1985, and July 4, 2015, were used. The support vector machine method was then used to classify the images. The results showed that Isfahan city had been encountered with an increase of impervious surfaces; in fact, this class covered 15% of the total area in 1985, while this value had been increased to 30% in 2015. Then LST zoning maps were created, indicating that the bare land and impervious surfaces categories were dominant in high temperature zones, while in the zones where water was present or NDVI was high, LST was low. Then, the landscape metrics in each of the LST zones were analyzed in relation to the LULC changes, showing that LULC changes due to urban expansion changed such landscape properties as the percentage of landscape, patch density, large patch index, and aggregation index. This information could be beneficial for urban planners to monitor and manage changes in the LULC patterns.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Alberti, M., & Marzluff, J. (2004). Ecological resilience in urban ecosystems: linking urban patterns to ecological and human function. Urban Ecosystem, 7(3), 241–265.

    Article  Google Scholar 

  • Artis, D. A., & Carnahan, W. H. (1982). Survey of emissivity variability in thermography of urban areas. Remote Senseng of Environment, 12, 313–329.

    Article  Google Scholar 

  • Asgarian, A., Amiri, B. J., & Sakieh, Y. (2015). Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach. Urban Ecosystem, 18, 209–222.

    Article  Google Scholar 

  • Bain, D. J., & Brush, G. S. (2004). Placing the pieces: reconstructing the original property mosaic in a warrant and patent watershed. Landscape Ecology, 19(8), 843–856.

    Article  Google Scholar 

  • Chavez, P. S. (1996). Image-based atmospheric corrections—revisited and improved. Photogrammetric Engineering and Remote Sensing, 62(9), 1025–1036.

    Google Scholar 

  • Gallo, K. P., McNab, A. L., Karl, T. R., Brown, J. F., Hood, J. J., & Tarpley, J. D. (1993). The use of a vegetation index for assessment of the urban heat island effect. International Journal of Remote Sensing, 14(11), 2223–2230.

    Article  Google Scholar 

  • Ghobadi, Y., Pradhan, B., Shafri, H. Z. M., & Kabiri, K. (2015). Assessment of spatial relationship between land surface temperature and landuse/cover retrieval from multi-temporal remote sensing data in South Karkheh Sub-basin, Iran. Arabian Journal of Geosciences, 8, 525–537.

    Article  Google Scholar 

  • Iran Meteorological Organization (n.d.) http://www.irimo.ir/.

  • Jiménez-Muñoz, J. C., Sobrino, J. A., Skoković, D., Mattar, C., & Cristóbal, J. (2014). Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data. IEEE Geoscience and Remote Sensing Letters, 11, 1840–1843.

    Article  Google Scholar 

  • Keshtkar, H., & Voigt, W. (2016). Potential impacts of climate and landscape fragmentation changes on plant distributions: coupling multitemporal satellite imagery with GIS-based cellular automata model. Ecological Informatics, 32, 145–155.

    Article  Google Scholar 

  • Leo, N. D., Escobedo, F. J., & Dubbeling, M. (2016). The role of urban green infrastructure in mitigating land surface temperature in Bobo-Dioulasso, Burkina Faso. Environment, Development and Sustainability, 18, 373–392.

    Article  Google Scholar 

  • 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 and Urban Planning, 114, 1–8.

    Article  Google Scholar 

  • Liu, H., & Weng, Q. (2008). Seasonal variations in the relationship between landscape pattern and land surface temperature in Indianapolis, USA. Environmental Monitoring and Assessment, 144(1), 199–219.

    Article  Google Scholar 

  • Liu, H., & Weng, Q. (2009). Scaling effect on the relationship between landscape pattern and land surface temperature: a case study of Indianapolis, United States. Photogrammetric Engineering & Remote Sensing, 75(3), 291–304.

    Article  Google Scholar 

  • Lo, C. P., & Quattrochi, D. A. (2003). Land-use and land-cover change, urban heat island phenomenon, and health implications: a remote sensing approach. Photogrammetric Engineering and Remote Sensing, 69, 1053–1063.

    Article  Google Scholar 

  • Mantero, P., Moser, G., & Serpico, S. B. (2005). Partially supervised classification of remote sensing images through SVM-based probability density estimation. IEEE Transactions on Geoscience and Remote Sensing, 43(3), 559–570.

    Article  Google Scholar 

  • McGarigal, K. (2015). Fragstats help. Amherst: Department of Environmental Conservation University of Massachusetts.

    Google Scholar 

  • McGarigal, K., & Marks, B. J. (1995). FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Gen. Tech. Report PNW-GTR-351, USDA Forest Service, Pacific Northwest Research Station, Portland, OR.

  • Memon, R. A., Leung, D. Y., & Chunho, L. (2008). A review on the generation, determination and mitigation of Urban Heat Island. Journal of Environmental Sciences, 20, 120–128.

    Article  Google Scholar 

  • Quattrochi, D. A., & Luvall, J. C. (1999). Thermal infrared remote sensing for analysis of landscape ecological processes: methods and applications. Landscape Ecology, 14(6), 577–598.

    Article  Google Scholar 

  • Smith, R. M. (1986). Comparing traditional methods for selecting class intervals on choropleth maps. The Professional Geographer, 38(1), 62–67.

    Article  Google Scholar 

  • Statistical Center of Iran. (2011). Iran statistical yearbook. https://www.amar.org.ir/.

  • Turner, M. G. (1990). Spatial and temporal analysis of landscape patterns. Landscape Ecology, 4, 21–30.

    Article  Google Scholar 

  • Turner, M. G. (2005). Landscape ecology: what is the state of the science? Annual Review of Ecological Evolution and Sensing, 36, 319–344.

    Article  Google Scholar 

  • United Nations. (2014). World urbanization prospects: the 2014 revision. New York.

  • Valor, E., & Caselles, V. (1996). Mapping land surface emissivity from NDVI: application to European, African and South American areas. Remote Sensing of Environment, 57, 167–184.

    Article  Google Scholar 

  • Voogt, J. A., & Oke, T. R. (1997). Complete urban surface temperatures. Journal of Applied Meteorology, 36, 1117–1132.

    Article  Google Scholar 

  • Wan, Z. (1999). MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD) version 3.3. Santa Barbara: Institute for Computational Earth System Science, University of California.

    Google Scholar 

  • Weng, Q. (2009). Thermal infrared remote sensing for urban climate and environmental studies: methods, applications, and trends. ISPRS Journal of Photogrammetry and Remote Sensing, 64, 335–344.

    Article  Google Scholar 

  • Weng, Q., Liu, H., & 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(2), 203–219.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Wu, J., Jelinski, D. E., Luck, M., & Tueller, P. T. (2000). Multiscale analysis of landscape heterogeneity: scale variance and pattern metrics. Geographic Information Sciences, 6(1), 6–19.

    Google Scholar 

  • Xie, M., Wang, Y., Chang, Q., Fu, M., & Ye, M. (2013). Assessment of landscape patterns affecting land surface temperature in different biophysical gradients in Shenzhen, China. Urban Ecosystem, 16, 871–886.

    Article  Google Scholar 

  • Zhang, J., & Wang, Y. (2008). Study of the relationships between the spatial extent of surface urban heat islands and urban characteristic factors based on Landsat ETM+ data. Sensors, 8, 7453–7468.

    Article  Google Scholar 

  • Zhang, Y., Odehb, I. O. A., & Ramadanc, E. (2013). Assessment of land surface temperature in relation to landscape metrics and fractional vegetation cover in an urban/peri-urban region using Landsat data. International Journal of Remote Sensing, 34(1), 168–189.

    Article  Google Scholar 

  • Zhou, W., Huang, G., & Cadenasso, M. L. (2011). Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes. Landscape and Urban Planning, 102, 54–63.

    Article  Google Scholar 

  • Zhou, W., Qian, Y., Li, X., Li, W., & Han, L. (2014). Relationships between land cover and the surface urban heat island: seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures. Landscape Ecology, 29, 153–167.

    Article  Google Scholar 

Download references

Acknowledgements

This research has been supported by the Isfahan University of Technology.

Author information

Authors and Affiliations

  1. Department of Natural Resources, Isfahan University of Technology, Isfahan, 8415683111, Iran

    Maliheh Madanian, Ali Reza Soffianian, Saeid Soltani Koupai & Saeid Pourmanafi

  2. Remote Sensing Division, Geomatic Engineering, University of Isfahan, Isfahan, 8174673441, Iran

    Mehdi Momeni

Authors
  1. Maliheh Madanian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ali Reza Soffianian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Saeid Soltani Koupai
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Saeid Pourmanafi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mehdi Momeni
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ali Reza Soffianian.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Madanian, M., Soffianian, A.R., Koupai, S.S. et al. Analyzing the effects of urban expansion on land surface temperature patterns by landscape metrics: a case study of Isfahan city, Iran. Environ Monit Assess 190, 189 (2018). https://doi.org/10.1007/s10661-018-6564-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-018-6564-z

Keywords

Search

Navigation