Skip to main content

Spatio-temporal footprints of urbanisation in Surat, the Diamond City of India (1990–2009)

Environmental Monitoring and Assessment volume 185, pages 3313–3325 (2013)Cite this article

Abstract

Urbanisation is a ubiquitous phenomenon with greater prominence in developing nations. Urban expansion involves land conversions from vegetated moisture-rich to impervious moisture-deficient land surfaces. The urban land transformations alter biophysical parameters in a mode that promotes development of heat islands and degrades environmental health. This study elaborates relationships among various environmental variables using remote sensing dataset to study spatio-temporal footprint of urbanisation in Surat city. Landsat Thematic Mapper satellite data were used in conjugation with geo-spatial techniques to study urbanisation and correlation among various satellite-derived biophysical parameters, [Normalised Difference Vegetation Index, Normalised Difference Built-up Index, Normalised Difference Water Index, Normalised Difference Bareness Index, Modified NDWI and land surface temperature (LST)]. Land use land cover was prepared using hierarchical decision tree classification with an accuracy of 90.4 % (kappa = 0.88) for 1990 and 85 % (kappa = 0.81) for 2009. It was found that the city has expanded over 42.75 km2 within a decade, and these changes resulted in elevated surface temperatures. For example, transformation from vegetation to built-up has resulted in 5.5 ± 2.6 °C increase in land surface temperature, vegetation to fallow 6.7 ± 3 °C, fallow to built-up is 3.5 ± 2.9 °C and built-up to dense built-up is 5.3 ± 2.8 °C. Directional profiling for LST was done to study spatial patterns of LST in and around Surat city. Emergence of two new LST peaks for 2009 was observed in N–S and NE–SW profiles.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

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

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

References

  • Alberti, M. (2005). The effects of urban patterns on ecosystem function. International Regional Science Review, 28, 168–192.

    Article  Google Scholar 

  • Amiri, R., Weng, Q., Alimohammadi, A., & Alavipanah, S. K. (2009). Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area, Iran. Remote Sensing of Environment, 113, 2606–2617.

    Article  Google Scholar 

  • Anyamba, A., & Tucker, C. J. (2005). Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003. Journal of Arid Environments, 63, 596–614.

    Article  Google Scholar 

  • Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., & Holtslag, A. A. M. (1998). A remote sensing surface energy balance algorithm for land (SEBAL) 1. Formulation. Journal of Hydrology, 212–213, 198–212.

    Article  Google Scholar 

  • Baur, B., & Baur, A. (1993). Climatic warming due to thermal radiation from an urban area as possible cause for the local extinction of a land snail. Applied Ecology, 30, 333–340.

    Article  Google Scholar 

  • Bolund, P., & Hunhammar, S. (1999). Ecosystem services in urban areas. Ecological Economics, 29, 293–301.

    Article  Google Scholar 

  • Bridhikitti, A., & Overcamp, T. J. (2012). Estimation of Southeast Asian rice paddy areas with different ecosystems from moderate-resolution satellite imagery. Agriculture, Ecosystems and Environment, 146, 113–120.

    Article  Google Scholar 

  • Brun, S. E., & Band, L. E. (2000). Simulating runoff behavior in an urbanizing watershed. Computers, Environment and Urban Systems, 24, 5–22.

    Article  Google Scholar 

  • Buyantuyev, A., & Wu, J. (2012). Urbanization diversifies land surface phenology in arid environments: interactions among vegetation, climatic variation, and land use pattern in the Phoenix metropolitan region, USA. Landscape and Urban Planning, 105, 149–159.

    Article  Google Scholar 

  • Carlson, T. N., & Ripley, D. A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62, 241–252.

    Article  Google Scholar 

  • Census of India (2011). Government of India.

  • Chen, J. (2007). Rapid urbanization in China: a real challenge to soil protection and food security. Catena, 69, 1–15.

    Article  Google Scholar 

  • Chen, X.-L., Zhao, H.-M., Li, P.-X., & Yin, Z.-Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment, 104, 133–146.

    Article  Google Scholar 

  • Delgado-V, C. A., & French, K. (2012). Parasite-bird interaction in urban areas: Current evidence and emerging questions. Landscape and urban planning, 105, 5–14.

    Article  Google Scholar 

  • Essa, W., et al. (2012). Evaluation of the DisTrad thermal sharpening methodology for urban areas. International Journal of Applied Earth Observation and Geoinformation, 19, 163–172.

    Article  Google Scholar 

  • Gabor, P., & Jombach, S. (2009). The relationship between the biological activity and the land surface temperature in Budapest. Applied Ecology and Environmental Research, 7, 241–251.

    Google Scholar 

  • Gallo, K. P., Tarpley, J. D., Mcnab, A. L., & Karl, T. R. (1995). Assessment of urban heat islands: a satellite perspective. Atmospheric Research, 37, 37–43.

    Article  Google Scholar 

  • Gao, B. (1996). NDWI—a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257–266.

    Article  Google Scholar 

  • Gillies, R. R., et al. (1997). A verification of the ‘triangle’ method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface radiant temperature. International Journal of Remote Sensing, 18, 3145–3166.

    Article  Google Scholar 

  • Goetz, S. J. (1997). Multi-sensor analysis of NDVI, surface temperature and biophysical variables at a mixed grassland site. International Journal of Remote Sensing, 18, 71–94.

    Article  Google Scholar 

  • Huang, S. L., Yeh, C. T., & Chang, L. F. (2010). The transition to an urbanizing world and the demand for natural resources. Current Opinion in Environmental Sustainability, 2(3), 136–143

    Google Scholar 

  • Jackson, T. J., et al. (2004). Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans. Remote Sensing of Environment, 92, 475–482.

    Article  Google Scholar 

  • Jiang, J., & Tian, G. (2010). Analysis of the impact of land use/land cover change on land surface temperature with remote sensing. Procedia Environmental Sciences, 2, 571–575.

    Article  Google Scholar 

  • Jong, R., et al. (2011). Analysis of monotonic greening and browning trends from global NDVI time-series. Remote Sensing of Environment, 115, 692–702.

    Article  Google Scholar 

  • Joshi, P. K., Bairawa, B. M., Sharma, R., & Sinha, V. S. P. (2011). Assessing urbanization patterns over India using temporal DMSP-OLS night time satellite data. Current Science, 100, 1479–1482.

    Google Scholar 

  • Julien, Y., & Sobrino, J. A. (2009). The Yearly Land Cover Dynamics (YLCD) method: an analysis of global vegetation from NDVI and LST parameters. Remote Sensing of Environment, 113, 329–334.

    Article  Google Scholar 

  • Julien, Y., Sobrino, J. A., & Verhoef, W. (2006). Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999. Remote Sensing of Environment, 103, 43–55.

    Article  Google Scholar 

  • Kalnay, E., & Cai, M. (2003). Impact of urbanization and land-use change on climate. Nature, 423, 528–531.

    Article  CAS  Google Scholar 

  • Kaushal, S., et al. (2008). Interaction between urbanisation and climate variability amplifies watershed nitrate export in Maryland. Environmental Science and Technology, 42, 5872–5878.

    Article  CAS  Google Scholar 

  • Li, Z., & Fox, J. M. (2012). Mapping rubber tree growth in mainland Southeast Asia using time-series MODIS 250 m NDVI and statistical data. Applied Geography, 32, 420–432.

    Article  Google Scholar 

  • Liu, L., & Zhang, Y. (2011). Urban heat island analysis using the Landsat TM data and ASTER data: a case study in Hong Kong. Remote Sensing, 3, 1535–1552.

    Article  Google Scholar 

  • Ma, Y., Kuang, Y., & Huang, N. (2010). Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+ imagery. International Journal of Applied Earth Observation and Geoinformation, 12, 110–118.

    Article  Google Scholar 

  • Maki, M., Ishiahra, M., & Tamura, M. (2004). Estimation of leaf water status to monitor the risk of forest fires by using remotely sensed data. Remote Sensing of Environment, 90, 441–450.

    Article  Google Scholar 

  • Maxwell, S. K., & Sylvester, K. M. (2012). Identification of “ever-cropped” land (1984–2010) using Landsat annual maximum NDVI image composites: Southwestern Kansas case study. Remote Sensing of Environment, 121, 186–195.

    Article  Google Scholar 

  • Mckinney, M. L. (2006). Urbanization as a major cause of biotic homogenization. Biological Conservation, 127, 247–260.

    Article  Google Scholar 

  • Nasipuri, P., & Chatterjee, A. (2009). Land use around Maithon reservoir: a study from high-resolution ASTER data. Current Science, 97, 25–27.

    Google Scholar 

  • Ng, C. N., Xie, Y. J., & Yu, X. J. (2011). Measuring the spatio-temporal variation of habitat isolation due to rapid urbanization: a case study of the Shenzhen River cross-boundary catchment, China. Landscape and Urban Planning, 103, 44–54.

    Article  Google Scholar 

  • Owen, T. W., Carlson, T. N., & Gillies, R. R. (1998). An assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization. International Journal of Remote Sensing, 19, 1663–1681.

    Article  Google Scholar 

  • Paul, M. J., & Meyer, J. L. (2001). Streams in the urban landscape. Annual Review of Ecology and Systematics, 32, 333–365.

    Article  Google Scholar 

  • Pu, R., Gong, P., Michishita, R., & Sasagawa, T. (2006). Assessment of multi-resolution and multi-sensor data for urban surface temperature retrieval. Remote Sensing of Environment, 104, 211–225.

    Article  Google Scholar 

  • Punia, M., Joshi, P. K., & Porwal, M. C. (2011). Decision tree classification of land use land cover for Delhi, India using IRS-P6 AWiFS data. Expert Systems with Applications, 38, 5577–5583.

    Article  Google Scholar 

  • Purevdorj, T., Tateishi, R., Ishiyama, T., & Honda, Y. (1998). Relationships between percent vegetation cover and vegetation indices. International Journal of Remote Sensing, 19, 3519–3535.

    Article  Google Scholar 

  • Qin, Z., Karnieli, A., & Berliner, P. (2001). A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel–Egypt border region. International Journal of Remote Sensing, 22, 3719–3746.

    Article  Google Scholar 

  • Raynolds, M. K., Comiso, J. C., Walker, D. A., & Verbyla, D. (2008). Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI. Remote Sensing of Environment, 112, 1884–1894.

    Article  Google Scholar 

  • Sandholt, I., Rasmussen, K., & Anderson, J. (2002). A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment, 79, 213–224.

    Article  Google Scholar 

  • Schott, J. R., et al. (2001). Caliberation of Landsat thermal data and application to water resource studies. Remote Sensing of Environment, 78, 108–117.

    Article  Google Scholar 

  • Schwarz, N., Schlink, U., Franck, U., & Grobmann, K. (2012). Relationship of land surface and air temperatures and its implications for quantifying urban heat island indicators—an application for the city of Leipzig (Germany). Ecological Indicators, 18, 693–704.

    Article  Google Scholar 

  • Scolozzi, R., & Geneletti, D. (2012). A multi-scale qualitative approach to assess the impact of urbanization on natural habitats and their connectivity. Environmental Impact Assessment Review, 36, 9–22.

    Article  Google Scholar 

  • Serrano, L., et al. (2000). Deriving water content of chaparral vegetation from AVIRIS data. Remote Sensing of Environment, 74, 570–581.

    Article  Google Scholar 

  • Son, N. T., et al. (2012). Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data. International Journal of Applied Earth Observation and Geoinformation, 18, 417–427.

    Article  Google Scholar 

  • Souch, C., & Grimmond, S. (2006). Applied climatology: urban climate. Progress in Physical Geography, 30, 270–279.

    Article  Google Scholar 

  • Stehman, S. V. (1996). Estimation of Kappa coefficient and its variance using stratified random sampling. Photogrammetric Engineering and Remote Sensing, 26, 401–407.

    Google Scholar 

  • Sun, Q., Tan, J., & Xu, Y. (2010). An ERDAS image processing method for retrieving LST and describing urban heat evolution: a case study in the Pearl River Delta Region in South China. Environmental Earth Sciences, 59, 1047–1055.

    Article  Google Scholar 

  • Surat Municipal Corporation (2011). Surat Municipal Corporation, http://www.suratmunicipal.org [Online]. Surat Municipal Corporation. Accessed 27 July 2012.

  • Tan, J., et al. (2010). The urban heat island and its impact on heat waves and human health in Shanghai. International Journal of Biometeorology, 54, 75–84.

    Article  Google Scholar 

  • Taubenböck, H., et al. (2009). Urbanization in India—spatiotemporal analysis using remote sensing data. Computers, Environment and Urban Systems, 33, 179–188.

    Article  Google Scholar 

  • Threlfall, C. G., Law, B., & Banks, P. B. (2012). Sensitivity of insectivorous bats to urbanization: implications for suburban conservation planning. Biological Conservation, 146, 41–52.

    Article  Google Scholar 

  • Uddin, S., et al. (2010). A remote sensing classification for land-cover changes and micro-climate in Kuwait. International Journal of Sustainable Development and Planning, 5, 367–377.

    Article  Google Scholar 

  • UN. (2010). World Urbanisation Prospects—The 2009 Revision. New York: Department of Economic and Social Affairs, Population Division.

    Google Scholar 

  • Voogt, J. A., & Oke, T. R. (2003). Thermal remote sensing of urban climates. Remote Sensing of Environment, 86, 370–384.

    Article  Google Scholar 

  • Weiss, J. L., Gutzler, D. S., Coonrod, J. E. A., & Dahm, C. N. (2004). Long-term vegetation monitoring with NDVI in a diverse semi-arid setting, central New Mexico, USA. Journal of Arid Environments, 58, 249–272.

    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, 467–483.

    Article  Google Scholar 

  • Wenhui, K. (2012). Spatio-temporal patterns of intra-urban land use change in Beijing, China Between 1984 and 2008. Chinese Geographical Sciences, 22, 210–220.

    Article  Google Scholar 

  • Wentz, E. A., et al. (2008). Expert system classification of urban land use/cover for Delhi, India. International Journal of Remote Sensing, 29(15), 4405–4427.

    Article  Google Scholar 

  • Whitford, V., Ennos, A. R., & Handley, J. F. (2001). “City form and natural process”—indicators for the ecological performance of urban areas and their application to Merseyside, UK. Landscape and Urban Planning, 57, 91–103.

    Article  Google Scholar 

  • Xiao, H., & Weng, Q. (2007). The impact of land use and land cover changes on land surface temperature in a karst area of China. Journal of Environmental Management, 85, 245–257.

    Article  Google Scholar 

  • Xiao, R., et al. (2008). Land surface temperature variation and major factors in Beijing, China. Photogrammetric Engineering and Remote Sensing, 74, 451–481.

    Google Scholar 

  • Yuan, F., & Bauer, M. E. (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, 375–386.

    Article  Google Scholar 

  • Zha, Y., Gao, J., & Ni, S. (2003). Use of normalised difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24, 583–594.

    Article  Google Scholar 

  • Zhang, Y., Odeh, I. O. A., & Han, C. (2009). Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis. International Journal of Applied Earth Observation and Geoinformation, 11, 256–264.

    Article  Google Scholar 

  • Zhou, L., et al. (2004). Evidence for a significant urbanization effect on climate in China. PNAS Geophysics, 101, 9540–9544.

    Article  CAS  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(1), 54–63.

    Article  Google Scholar 

Download references

Acknowledgments

The authors are thankful to anonymous reviewers for the suggestions. RS and PKJ thank the Department of Science and Technology (DST), Ministry of Science and Technology, Government of India, and AG acknowledges the Council of Scientific and Industrial Research (CSIR), Government of India for the support.

Author information

Authors and Affiliations

  1. TERI University, New Delhi, India, 110070

    Richa Sharma, Aniruddha Ghosh & Pawan Kumar Joshi

Authors
  1. Richa Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aniruddha Ghosh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pawan Kumar Joshi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pawan Kumar Joshi.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Sharma, R., Ghosh, A. & Joshi, P.K. Spatio-temporal footprints of urbanisation in Surat, the Diamond City of India (1990–2009). Environ Monit Assess 185, 3313–3325 (2013). https://doi.org/10.1007/s10661-012-2792-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10661-012-2792-9

Keywords

  • Biophysical parameters
  • Expert classification
  • LST
  • LULC changes
  • Urbanisation