Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Inter-calibration and Urban Light Index of DMSP-OLS Night-Time Data for Evaluating the Urbanization Process in Australian Capital Territory

  • Chapter
  • First Online:
Applications and Challenges of Geospatial Technology

Abstract

The magnification mechanism of human settlement is called urbanization, involving various other activities such as population transition, resource consumption, etc. leading to various growing patterns of urban augmentation. The assessment of such spatial pattern is crucial in developing a sustainable urban agglomeration. Night-time light (NTL) data is an important machination for such assessment and detailed monitoring. In this paper, DMSP-OLS (the Defence Meteorological Satellite Program/Operational Linescan Program) datasets have been used to assess the urban straggle of Australian Capital Territory (ACT) and to delineate the urban extent from 1992 to 2012, at an interval of 3 years. DMSP-OLS has the unique capability to detect synthetic lights from cities, towns, industrial sites, ports, etc. Moreover, using ARC GIS calligraphies, 20 random points were selected from the extracted area of interest (AOI). Pixels values of those 20 random points are derived from the given time series dataset (1992–2012). A regression value was extracted from each year by using a second-order polynomial equation. A polynomial regression model is also constructed by taking the regression values and the time series as the two variables, respectively. Urban light index (ULI) is also constructed for analysing the progression of urbanization in ACT from 1992 to 2012 with the help of a derived formula. Furthermore, a unit circle buffer zone having a radius of 20 km is established by taking the centre of each built-up zone as the focal point of the constructed buffer, to compare easily the rate of expansion of urbanization. The present paper indicates the growing potential of the DMSP-OLS night-time satellite data to define the urban light space information, which truly describes the attributes of urban sprawl, and to delineate the evolution of urban morphology and urban extension.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Australian Bureau of Statistics (ABS) (2017) Population projections, Australia, 2016 (base) to 2101. ABS cat. no. 3222.0. Canberra: ABS

    Google Scholar 

  • Cinzano P, Falchi F, Elvidge CD, Baugh KE (2001) The artificial sky brightness in Europe derived from DMSP satellite data. Preserving the astronomical sky, pp 95–102

    Google Scholar 

  • Dewan AM, Yamaguchi Y (2009) Land use and land cover change in Greater Dhaka, Bangladesh: using remote sensing to promote sustainable urbanization. Appl Geogr 29:390–401

    Article  Google Scholar 

  • Elvidge CD, Baugh KE, Kihn EA, Kroehl HW, Davis ER (1997) Mapping city lights with nighttime data from the DMSP operational linescan system. Photogramm Eng Remote Sens 63(6):727–734

    Google Scholar 

  • Elvidge CD, Baugh KE, Dietz JB, Bland T, Sutton PC, Kroehl HW (1999) Radiance calibration of Dmsp-Ols low-light imaging data of human settlements. Remote Sens Environ 68(1):77–88

    Article  Google Scholar 

  • Elvidge CD, Tuttle BT, Sutton PC, Baugh KE, Howard AT, Milesi C, Bhaduri B, Nemani R (2007) Global distribution and density of constructed impervious surfaces. Sensors 7(9):1962–1979

    Article  Google Scholar 

  • Elvidge C, Ziskin D, Baugh K, Tuttle B, Ghosh T, Pack D, Erwin E, Zhizhin M (2009) A fifteen year record of global natural gas flaring derived from satellite data. Energies 2:595–622

    Article  Google Scholar 

  • Feng Y, Kugler J, Zak PJ (2002) Population growth, urbanisation and the role of government in China: a political economic model of demographic change. Urban Stud 39:2329–2343

    Article  Google Scholar 

  • Fujita M, Krugman P, Mori T (1999) On the evolution of hierarchical urban systems. Eur Econ Rev 43(2):209–251

    Article  Google Scholar 

  • Han J, Hayashi Y, Cao X, Imura H (2009) Application of an integrated system dynamics and cellular automata model for urban growth assessment: a case study of Shanghai, China. Landsc Urban Plan 91:133–141

    Article  Google Scholar 

  • He CY, Shi PJ, Li JG, Chen J, Pan YZ, Li J, Zhuo L, Toshiaki I (2006) Restoring urbanization process in China in the 1990s by using non-radiance calibrated DMSP/OLS nighttime light imagery and statistical data. Chin Sci Bull 51:1614–1620

    Article  Google Scholar 

  • He CY, Ma Q, Li T, Yang Y, Liu ZF (2012) Spatiotemporal dynamics of electric power consumption in Chinese Mainland from 1995 to 2008 modeled using DMSP/OLS stable nighttime lights data. J Geogr Sci 22:125–136

    Article  Google Scholar 

  • Henderson M, Yeh ET, Gong P, Elvidge C, Baugh K (2003) Validation of urban boundaries derived from global night-time satellite imagery. Int J Remote Sens 24(3):595–609

    Article  Google Scholar 

  • Huang X, Schneider A, Friedl MA (2016) Mapping sub-pixel urban expansion in China using Modis and Dmsp/Ols nighttime lights. Remote Sens Environ 175:92–108

    Article  Google Scholar 

  • Imhoff ML, Lawrence WT, Stutzer DC, Elvidge CD (1997) A technique for using composite DMSP/OLS ‘City Lights’ satellite data to map urban area. Remote Sens Environ 61:361–370

    Article  Google Scholar 

  • Letu H, Hara M, Tana G, Nishio F (2012) A saturated light correction method for Dmsp/Ols nighttime satellite imagery. IEEE Trans Geosci Remote Sens 50(2):389–396

    Article  Google Scholar 

  • Li SM (2004) Population migration and urbanization in China: a comparative analysis of the 1990 population census and the 1995 national one percent sample population survey. Int Migr Rev 38:655–685

    Article  Google Scholar 

  • Li Q, Linlin L, Weng Q, Xie Y, Guo H (2016) Monitoring urban dynamics in the Southeast U.S.A. using time-series Dmsp/Ols nightlight imagery. Remote Sens 8(7):578

    Article  Google Scholar 

  • Liu ZF, He CY, Zhang QF, Huang QX, Yang Y (2012) Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008. Landsc Urban Plan 106:62–72

    Article  Google Scholar 

  • Liu X, Guohua H, Bin A, Xia L, Shi Q (2015) A normalized urban areas composite index (Nuaci) based on combination of Dmsp-Ols and Modis for mapping impervious surface area. Remote Sens 7(12):17168–17189

    Article  Google Scholar 

  • Lo CP (2001) Modelling the population of China using DMSP operational line scan system nighttime data. Photogramm Eng Remote Sens 67:1037–1047

    Google Scholar 

  • Lo CP (2002) Urban indicators of China from radiance-calibrated digital DMSP-OLS nighttime images. Ann Assoc Am Geogr 92:225–240

    Article  Google Scholar 

  • Lo CP (2010) Urban indicators of China from radiance-calibrated digital DMSP-OLS nighttime images. Ann Assoc Am Geogr 92(2):225–240

    Article  Google Scholar 

  • Lu D, Tian H, Zhou G, Ge H (2008) Regional mapping of human settlements in southeastern China with multisensor remotely sensed data. Remote Sens Environ 112(9):3668–3679

    Article  Google Scholar 

  • Ma T, Zhou C, Pei T, Haynie S, Fan J (2012) Quantitative estimation of urbanization dynamics using time series of Dmsp/Ols nighttime light data: a comparative case study from China’s cities. Remote Sens Environ 124:99–107

    Article  Google Scholar 

  • Mertes CM, Schneider A, Sulla-Menashe D, Tatem AJ, Tan B (2015) Detecting change in urban areas at continental scales with Modis data. Remote Sens Environ 158(0):331–347

    Article  Google Scholar 

  • Milesi C, Elvidge CD, Nemani RR, Running SW (2003) Assessing the impact of urban land development on net primary productivity in the southeastern United States. Remote Sens Environ 86:401–410

    Article  Google Scholar 

  • Miller JD, Knapp EE, Key CH, Skinner CN, Isbell CJ, Creasy RM, Sherlock JW (2009) Calibration and validation of the Relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA. Remote Sens Environ 113:645–656

    Article  Google Scholar 

  • Owen TW (1998) Using DMSP-OLS light frequency data to categorize urban environments associated with US climate observing stations. Int J Remote Sens 19:3451–3456

    Article  Google Scholar 

  • Pandey B, Joshi PK, Seto KC (2013) Monitoring urbanization dynamics in India using DMSP/OLS night time lights and SPOT-VGT data. Int J Appl Earth Obs Geoinf 23:49–61

    Article  Google Scholar 

  • Runkui L, Zhipeng L, Wenju G, Wenjun D, Qun X, Xianfeng S (2014) Diurnal, seasonal, and spatial variation of PM2.5 in Beijing. Sci Bull 60(3):387–395

    Google Scholar 

  • Schneider A, Friedl MA, Potere D (2010) Mapping global urban areas using Modis 500-M data: new methods and datasets based on ‘urban ecoregions’. Remote Sens Environ 114(8):1733–1746

    Article  Google Scholar 

  • Shi K, Huang C, Yu B, Yin B, Huang Y, Wu J (2014) Evaluation of NPP-VIIRS night-time light composite data for extracting built-up urban areas. Remote Sens Lett 5(4):358–366

    Article  Google Scholar 

  • Shu S, Yu B, Wu J, Liu H (2011) Methods for deriving urban built-up area using night- light data: assessment and application. Remote Sens Technol Appl 26:169–176

    Google Scholar 

  • Small C (2002) A global analysis of urban reflectance. In: D.M.a.F.S.-E.C. Jurgens (ed) Proceedings of the third international symposium on remote sensing of urban areas. Istanbul, Turkey

    Google Scholar 

  • Small, C. (2003). High spatial resolution spectral mixture analysis of urban reflectance. Remote Sens Environ, 88(1–2), 170–186

    Article  Google Scholar 

  • Small C (2005) A global analysis of urban reflectance. Int J Remote Sens 26(4):661–681

    Article  Google Scholar 

  • Small C, Pozzi F, Elvidge CD (2005) Spatial analysis of global urban extent from DMSPOLS night lights. Remote Sens Environ 96:277–291

    Article  Google Scholar 

  • Small C, Elvidge CD, Balk D, Montgomery M (2011) Spatial scaling of stable night lights. Remote Sens Environ 115:269–280

    Article  Google Scholar 

  • Su Y, Chen X, Wang C, Zhang H, Liao J, Yuyao Y, Wang C (2015) A new method for extracting built-up urban areas using Dmsp-Ols nighttime stable lights: a case study in the Pearl River Delta, Southern China. Gisci Remote Sens 52(2):218–238

    Article  Google Scholar 

  • Sutton PC (2003) A scale-adjusted measure of “Urban sprawl” using nighttime satellite imagery. Remote Sens Environ 86:353–369

    Article  Google Scholar 

  • Sutton P, Roberts D, Elvidge C, Baugh K (2001) Census from Heaven: an estimate of the global human population using night-time satellite imagery. Int J Remote Sens 22(16):3061–3076

    Article  Google Scholar 

  • Tan L (2017) Australian states and territories: New South Wales, 2017, Geography & Environment/Geo/Env: Countries/Continents/Geo/Env: CC – Australia/Oceani. ISBN 9780994624710

    Google Scholar 

  • Welch R (1980) Monitoring urban-population and energy-utilization patterns from satellite data. Remote Sens Environ 9(1):1–9

    Article  Google Scholar 

  • Welch R, Zupko S (1980) Urbanized area energy-utilization patterns from Dmsp data. Photogramm Eng Remote Sens 46(2):201–207

    Google Scholar 

  • Wigmore L (1971) Canberra: history of Australia’s national capital. Dalton Publishing Company. ISBN 0-909906-06-8

  • Yi K, Tani H, Li Q, Zhang J, Guo M, Bao Y, Wang X, Li J (2014) Mapping and evaluating the urbanization process in Northeast China using DMSP/OLS nighttime light data. Sensors 14(2):3207–3226

    Article  Google Scholar 

  • Zhang J, Zhu T, Kipen H, Wang G, Huang W, Rich D et al (2013) Cardiorespiratory biomarker responses in healthy young adults to drastic air quality changes surrounding the 2008 Beijing Olympics. Res Rep Health Eff Inst 174:5–174

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Applied Earth Sciences, National Oceanic and Atmospheric Administration, Stanford University, Boulder, CO, USA

    Christopher D. Elvidge

  2. Remote Sensing and GIS, Kumaun University, Almora, Uttarakhand, India

    Himangshu Kalita, Upasana Choudhury & Bismay Ranjan Tripathy

  3. Department of Geography, Jamia Millia Islamia, New Delhi, India

    Sufia Rehman & Pavan Kumar

Authors
  1. Christopher D. Elvidge
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Himangshu Kalita
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Upasana Choudhury
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sufia Rehman
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Bismay Ranjan Tripathy
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Pavan Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Geography, Jamia Millia Islamia, New Delhi, India

    Pavan Kumar

  2. Department of Geography, DSB Campus, Kumaun University, Nainital, Uttarakhand, India

    Meenu Rani

  3. Institute of Environment and Sustainable Development (IESD), Banaras Hindu University, Varanasi, Uttar Pradesh, India

    Prem Chandra Pandey

  4. Department of Geography, Jamia Millia Islamia, New Delhi, India

    Haroon Sajjad

  5. Department of Geophysics, Kurukshetra University, Kurukshetra, Haryana, India

    Bhagwan Singh Chaudhary

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Elvidge, C.D., Kalita, H., Choudhury, U., Rehman, S., Tripathy, B.R., Kumar, P. (2019). Inter-calibration and Urban Light Index of DMSP-OLS Night-Time Data for Evaluating the Urbanization Process in Australian Capital Territory. In: Kumar, P., Rani, M., Chandra Pandey , P., Sajjad, H., Chaudhary, B. (eds) Applications and Challenges of Geospatial Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-99882-4_10

Download citation

Publish with us

Policies and ethics

Search

Navigation