Skip to main content

Advertisement

SpringerLink
Log in

Linkage of urban expansion and land surface temperature using geospatial techniques for Jaipur City, India

  • Original Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

The aim of this study is to understand the land use change and urban expansion of Jaipur City of Rajasthan (India). Landsat 5 TM and Landsat 8 OLI satellite data of 4 years, i.e., 1993, 2000, 2010, and 2015 are used for land use and land surface temperature (LST) analysis. ERDAS Imagine and ArcGIS software are used to conduct the analysis. Urban settlement increased from 13.5 to 57.3% in the study period. Open land is mainly changed to urban areas. Urban settlement is also expanded to peri-urban area of Jaipur City. Jaipur City expanded along three directions i.e., north, west, and south and less development is found in the east direction. Based on radial analysis, it is observed there is not much development within the periphery of 2 km (close to city center) but maximum growth is observed within the distance from 4 to 6 km radius of city center. Expansion intensity was observed highest in the period 2015–2010 from 6 km onwards and reached to a maximum value close to 17 km2/year. In LST analysis, there is less change in extreme temperature, but more areal increase in average temperature range (30–35 °C). Urbanization is the main driving process of land cover changes and consequently changes in LST.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Abdel Rahman MAE, Natarajan A, Hegde R (2016) Assessment of land suitability and capability by integrating remote sensing and GIS for agriculture in Chamarajanagar district, Karnataka, India. Egypt J Remote Sens Space Sci 19:125–141

    Google Scholar 

  • Bahi H, Rhinane H, Bensalmia A, Fehrenbach U, Scherer D (2016) Effects of urbanization and seasonal cycle on the surface urban heat island patterns in the coastal growing cities: a case study of Casablanca, Morocco. Remote Sen 8(10):829. https://doi.org/10.3390/rs8100829

    Article  Google Scholar 

  • Cao X, Bao A, Chen X, Xia Y (2008) Land surface temperature in response to land use/cover change based on remote sensing data in Sangong River. In: Gao W, Wang H (eds) Remote Sensing and Modeling of Ecosystems for Sustainability V, vol 7083, p 70830K. https://doi.org/10.1117/12.791576

  • Chen XL, Zhao HM, Li PX, Yin ZY (2006) Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens Environ 104(2):133–146. https://doi.org/10.1016/j.rse.2005.11.016

    Article  Google Scholar 

  • Deep S, Saklani S (2014) Urban sprawl modeling using cellular automata. Egypt J Remote Sens Space Sci 17:179–187

    Google Scholar 

  • Foody GM (1992) On the compensation for chance agreement in image classification accuracy assessment. Photogramm Eng Remote Sens 58:1459–1460

    Google Scholar 

  • General R (2001) Census of India, 2001. Provisional Population Totals, Rajasthan

  • Grover A, Singh RB (2015) Analysis of urban heat island (UHI) in relation to normalized difference vegetation index (NDVI): a comparative study of Delhi and Mumbai. Environments 2015(2):125–138

    Article  Google Scholar 

  • Hussain A, Bhalla P, Palria S (2014) Remote sensing based analysis of the role of land use/land cover on surface temperature and temporal changes in temperature; a case study of Ajmer District, Rajasthan. The International Archives of Photogrammetry, Remote Sen and Spatial Info Sci 40(8):1447

    Article  Google Scholar 

  • Jaipur Development Authority (2011) Master development plan. http://virtual.jaipurjda.org/page.aspx?pid=34

  • Jalan S, Sharma K (2014) Spatio-temporal assessment of land use/land cover dynamics and urban heat island of Jaipur city using satellite data. The International Archives of Photogrammetry, Remote Sen and Spatial Info Sci 40(8):767

    Article  Google Scholar 

  • Kawashima S, Ishida T, Minomura M, Miwa T (2000) Relations between surface temperature and air temperature on a local scale during winter nights. J Appl Meteorol 39(9):1570–1779. https://doi.org/10.1175/1520-0450(2000)039<1570:RBSTAA>2.0.CO;2

    Article  Google Scholar 

  • Khandelwal S, Goyal R, Kaul N, Singhal V (2011) Study of land surface temperature variations with distance from hot spots for urban heat island analysis. In: Proceedings of the Geospatial World Forum: Dimensions and Directions of Geospatial Industry, Hyderabad, pp 18–21

  • Kikon N, Singh P, Singh SK, Vyas A (2016) Assessment of urban heat islands (UHI) of Noida City, India using multi-temporal satellite data. Sustainable Cities and Society 22:19–28. https://doi.org/10.1016/j.scs.2016.01.005

    Article  Google Scholar 

  • Kumar KS, Bhaskar PU, Padmakumari K (2012) Estimation of land surface temperature to study urban heat island effect using LANDSAT ETM+ image. Inter J of Eng Sci and Tech 4(2):771–778

    Google Scholar 

  • Lilly Rose A, Devadas MD (2009) Analysis of Land surface temperature and land use/land cover types using remote sensing imagery—a case in Chennai City, India, The seventh International Conference on Urban Clim held on 29 June–3 July 2009, Yokohama, Japan

  • Liu G, Zhang Q, Li G, Doronzo DM (2016) Response of land cover types to land surface temperature derived from Landsat-5 TM in Nanjing Metropolitan Region, China. Environ Earth Sci 75(20):1386. https://doi.org/10.1007/s12665-016-6202-4

    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 Sen 3(7):1535–1552. https://doi.org/10.3390/rs3071535

    Article  Google Scholar 

  • Ma Z, Redmond RL (1995) Tau coefficients for accuracy assessment of classification of remote sensing data. Photogramm Eng Remote Sens 61:435–439

    Google Scholar 

  • Mallick J, Kant Y, Bharath BD (2008) Estimation of land surface temperature over Delhi using Landsat-7 ETM+. J Ind Geophys Union 12(3):131–140

    Google Scholar 

  • Mallick J, Rahman A, Singh CK (2013) Modeling urban heat islands in heterogeneous land surface and its correlation with impervious surface area by using night-time ASTER satellite data in highly urbanizing city, Delhi-India. Adv Space Res 52(4):639–655. https://doi.org/10.1016/j.asr.2013.04.025

    Article  Google Scholar 

  • Markham BL, Barker, JL (1986) Landsat MSS and TM post-calibration dynamic rangers, exoatmospheric reflectance and at-satellite temperatures. EOSAT Landsat Tech. Notes 1:3–8

  • Monserud RA, Leemans R (1992) Comparing global vegetation maps with the Kappa statistic. Ecol Model 62:275e293

    Article  Google Scholar 

  • Oke TR (1987) Boundary layer climates (2nd ed). London: Methuen (435 pp)

  • Owen TW, Carlson TN, Gillies RR (1998) An assessment of satellite remotely sensed land cover parameters in quantitatively describing the climatic effect of urbanization. Int J Remote Sens 19(9):1663–1681. https://doi.org/10.1080/014311698215171

    Article  Google Scholar 

  • Pal S, Ziaul S (2017) Detection of land use and land cover change and land surface temperature in English Bazar urban centre. Egypt J Remote Sens and Space Sci 20(1):125–145

    Google Scholar 

  • Pandya MR, Shah DB, Trivedi HJ, Darji NP, Ramakrishnan R, Panigrahy S, Kirankumar AS (2014) Retrieval of land surface temperature from the Kalpana-1 VHRR data using a single-channel algorithm and its validation over western India. ISPRS Journal of Photogramm Eng Remote Sens 94:160–168. https://doi.org/10.1016/j.isprsjprs.2014.05.004

    Article  Google Scholar 

  • Ramachandra TV, Bharath AH, Sowmyashree MV (2015) Monitoring urbanization and its implications in a mega city from space: spatiotemporal patterns and its indicators. J Environ Manag 148:67–81. https://doi.org/10.1016/j.jenvman.2014.02.015

    Article  Google Scholar 

  • Sahana M, Ahmed R, Sajjad H (2016) Analyzing land surface temperature distribution in response to land use/land cover change using split window algorithm and spectral radiance model in Sundarban Biosphere Reserve, India. Modeling Earth Syst and Environ 2(2):1–11

    Google Scholar 

  • Senanayake IP, Welivitiya WDDP, Nadeeka PM (2013) Remote sensing based analysis of urban heat islands with vegetation cover in Colombo City, Sri Lanka using Landsat-7 ETM+ data. Urban Clim 5:19–35. https://doi.org/10.1016/j.uclim.2013.07.004

    Article  Google Scholar 

  • Sharma R, Chakraborty A, Joshi PK (2015) Geospatial quantification and analysis of environmental changes in urbanizing city of Kolkata (India). Environ Monit Assess 187(1):4206. https://doi.org/10.1007/s10661-014-4206-7

    Article  Google Scholar 

  • Sharma R, Joshi PK (2014) Identifying seasonal heat islands in urban settings of Delhi (India) using remotely sensed data—an anomaly based approach. Urban Clim 9:19–34. https://doi.org/10.1016/j.uclim.2014.05.003

    Article  Google Scholar 

  • Srivastava PK, Majumdar TJ, Bhattacharya AK (2009) Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Adv Space Res 43(10):1563–1574. https://doi.org/10.1016/j.asr.2009.01.023

    Article  Google Scholar 

  • Weng Q (2001) A remote sensing? GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. Int J of Remote Sens 22(10):1999–2014

    Google Scholar 

  • Weng Q, Yang S (2004) Managing the adverse thermal effects of urban development in a densely populated Chinese city. J Environ Manag 70(2):145–156. https://doi.org/10.1016/j.jenvman.2003.11.006

    Article  Google Scholar 

  • 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. Int J of Remote Sens 28(15):3205–3226. https://doi.org/10.1080/01431160500306906

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Environmental Science, School of Earth Sciences, Central University of Rajasthan, Ajmer, India

    Suresh Chandra, Devesh Sharma & Swatantra Kumar Dubey

Authors
  1. Suresh Chandra
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Devesh Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Swatantra Kumar Dubey
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Devesh Sharma.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chandra, S., Sharma, D. & Dubey, S.K. Linkage of urban expansion and land surface temperature using geospatial techniques for Jaipur City, India. Arab J Geosci 11, 31 (2018). https://doi.org/10.1007/s12517-017-3357-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-017-3357-6

Keywords

Search

Navigation