Skip to main content

Advertisement

Log in

Assessment of impervious surface growth in urban environment through remote sensing estimates

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

The fast growth in population and expansion of urban built area has led to the transformation of the natural landscape into impervious surfaces. Remote sensing-based estimate of impervious surface area (ISA) has emerged as an important indicator for the assessment of water resources depletion in urban areas and developed a correlation between land-use change and their potential impact on urban hydrology. In the present work, a remote sensing-based Impervious Surface Area (ISA) was carried out for New Okhla Industrial Development Authority (NOIDA) city, one of the fastest growing cities in National Capital Region (NCR) of India. The impervious surface area (ISA) of NOIDA was calculated for the years 2001, 2007 and 2014 using multi-temporal LANDSAT thermal data by applying linear spectral mixing analysis (LSMA) techniques to monitor the growth rate of impervious surface. The results observed by analysis of multi-temporal satellite images show an extreme temporal change in the growth of ISA in the city. The ISA observed for the year 2001 is 28 sq.km; in 2007, its increase was 48 sq.km and was 132 in 2014. The results were observed from this work through the use of satellite data which is very important for water resource management, planning and prediction of ISA impact on hydrology.

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

Access this article

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

  • Adams JB, Sabol DE, Kapos V, Filho RA, Roberts DA, Smith MO et al (1995) Classification of multispectral images based on fractions of endmembers: application to land cover change in the Brazilian Amazon. Remote Sens Environ 52:137–154

    Article  Google Scholar 

  • Boardman JM, Kruse FA, Green RO (1995) Mapping target signature via partial unmixing of AVIRIS data. Summaries of the Fifth JPL Airborne Earth Science Workshop, vol 95(1). JPL Publication, pp 23–26

  • Braud I, Breil P, Thollet F, Lagouy M, Branger F, Jacqueminet C, Kermadi S, Michel K (2013) Evidence of the impact of urbanization on the hydrological regime of a medium-sized periurban catchment in France. J Hydrol 485:5–23

    Article  Google Scholar 

  • Deng Y, Fan F, Chen R (2012) Extraction and analysis of impervious surfaces based on a spectral un-mixing method using Pearl River Delta of China Landsat TM/ETM+ imagery from 1998 to 2008. Sensors 12:1846–1862

    Article  Google Scholar 

  • Fletcher TD, Andrieu H, Hamel P (2013) Understanding, management and modelling of urban hydrology and its consequences for receiving waters; a state of the art review. Adv Water Resour 51:261–279

    Article  Google Scholar 

  • Green AA, Berman M, Switzer P, Craig MD (1988) A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Trans Geosci Remote Sens 26:65–74

    Article  Google Scholar 

  • Hardison EC, Michael A, John PD, Robert JH, Mark MB (2009) Urban land use, channelincision, and riparian water table decline along inner coastal plain streams, North Carolina. J Am Water Resour Assoc 45(4):1032–1046

    Article  Google Scholar 

  • Jacobson CR (2011) Identification and quantification of the hydrological impacts of imperviousness in urban catchments: a review. J Environ Manage 92:1438–1448

    Article  Google Scholar 

  • Kikon N, Singh P, Singh SK, Vyas A (2016) Assessment of urban heat islands (UHI) of Noida City, India using multi-temporal satellite data. Sustain Cities Soc 22:19–28

    Article  Google Scholar 

  • Lu D, Mausel P, Brondízio E, Moran E (2002) Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research. Int J Remote Sens 23(13):2651–2671

    Article  Google Scholar 

  • Lu D, Song K, Zeng L, Liu D, Khan S, Zhang B, Wang Z, Jin C (2008a) Estimating impervious surface for the urban area expansion: examples from changchun, northeast china. In: The international archives of the photogrammetry, remote sensing and spatial information sciences, 36( Part B8), pp 385–391

  • Lu D, Batistella M, Moran E, de Miranda EE (2008b) A comparative study of Landsat TM and SPOT HRG images for vegetation classification in the Brazilian Amazon. Photogram Eng Remote Sens 74(3):311– 321

    Article  Google Scholar 

  • Markham BL, Barker JL (1986) Landsat MSS and TM post-calibration dynamic ranges, exoatmospheric reflectances and at-satellite temperatures. EOSAT Landsat Technical Notes, No. 1

  • Mustard JF, Sunshine JM (1999) Spectral analysis for earth science investigations. In: Manual of remote sensing. Remote sensing for the earth sciences, vol 3. Wiley, New York pp 251–307

  • Rai SC, Saha A (2015) Impact of urban sprawl on groundwater quality: a case study of Faridabad city, National Capital Region of Delhi. Arab J Geosci 8(10):8039–8045

    Article  Google Scholar 

  • Ridd MK (1995) Exploring a VIS (vegetation-impervious surface soil) model for urban ecosystem analysis through remote sensing: comparative anatomy for cities. Int J Remote Sens 16(12):2165–2185

    Article  Google Scholar 

  • Roberts DA, Gardner M, Church R, Ustin S, Scheer G, Green RO (1998) Mapping chaparral in the Santa Monica mountains using multiple endmember spectral mixture models. Remote Sens Environ 65:267–279

    Article  Google Scholar 

  • Shuster WD, Bonta J, Thurston H, Warnemuende E, Smith DR (2005) Impacts of impervioussurface on watershed hydrology: a review. Urban Water J 2(4):263–275. doi:10.1080/15730620500386529

    Article  Google Scholar 

  • Singh P, Thakur JK, Kumar S, Singh UC (2012) Assessment of land use/land cover using geospatial techniques in a semi-arid region of Madhya Pradesh, India. In: Thakur Singh, Prasad Gossel (eds) Geospatial techniques for managing environmental resources. Springer, Heidelberg, pp 152–163

    Google Scholar 

  • Small C (2001) Estimation of urban vegetation abundance by spectral mixture analysis. Int J Remote Sens 22(7):1305–1334

    Article  Google Scholar 

  • Srinivasan V, Karen CS, Emerson R, Steven MG (2013) The impact of urbanization on water vulnerability: a coupled human–environment system approach for Chennai, India. Glob Environ Change 23:229–239

    Article  Google Scholar 

  • Sugg ZP, Finke P, Goodrich DC, Moran MS, Yool SR (2014) Mapping impervious surfaces using object-oriented classification in a semiarid urban region. Photogramm Eng Remote Sens 80(4):343–352

    Article  Google Scholar 

  • United Nations (2008) United Nations expert group meeting on population distribution, urbanization, internal migration and development. United Nations Population Division

  • Van Der Meer F, De Jong SM (2000) Improving the results of spectral un-mixing of Landsat Thematic Mapper imagery by enhancing the orthogonality of end-members. Int J Remote Sens 21:2781–2797

    Article  Google Scholar 

  • Weng Q (2012) Remote sensing of impervious surfaces in the urban areas: requirements, methods, and trends. Remote Sens Environ 117:34–49

    Article  Google Scholar 

  • Wu C (2004) Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery. Remote Sens Environ 93:480–492

    Article  Google Scholar 

  •  Wu C,  Murray AT (2003) Estimating impervious surface distribution by spectral mixture analysis. Remote Sensi Environ 84(4):493–505

    Article  Google Scholar 

  • Xu H (2005) A study on information extraction of water body with the modified normalized difference water index (MNDWI). J Remote Sens 9(5):511–517

    Google Scholar 

  • Xu H (2007) Etraction of urban built-up land features from Landsat imagery using a thematicoriented index combination technique. Photogram Eng Remote Sens 73(12):1381–1391

    Article  Google Scholar 

  • Xu H, Wang X, Xiao G (2000) A remote sensing and GIS integrated study on urbanization with its impact on arable lands: Fuqing City, Fujian Province, China. Land Degrad Dev 11(4):301–314

    Article  Google Scholar 

  • Zhang Y, Ma X, Chen L (2007) Hybrid change detection for watershed impervious surface using multi-time remotely sensed data. In Proceedings of IEEE international geoscience and remote sensing symposium, IGARSS 2007, vol 23(28), Barcelona, Spain, pp 1939–1942

Download references

Acknowledgements

The authors express his gratefulness to the Amity University for providing facility and constant encouragement for carried out this research work. Authors are very thankful to the anonymous reviewers for their meaningful comments for improvement of the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Prafull Singh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sarkar Chaudhuri, A., Singh, P. & Rai, S.C. Assessment of impervious surface growth in urban environment through remote sensing estimates. Environ Earth Sci 76, 541 (2017). https://doi.org/10.1007/s12665-017-6877-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-017-6877-1

Keywords

Navigation