38, 2012 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
NIGHT-TIME LIGHTS AND LEVELS OF DEVELOPMENT: A STUDY USING DMSP- 
OLS NIGHT TIME IMAGES AT THE SUB-NATIONAL LEVEL 
Koel Roychowdhury, Simon J ones”, Karin Reinke, Colin Arrowsmith 
School of Mathematical and Geospatial Sciences 
RMIT University 
Melbourne, Australia 
simon.jones € rmit.edu.au 
Commission VIII, WG VIIU2 
KEY WORDS: DMSP-OLS, night-time lights, census, scale effects, socio-economic metrics, development 
ABSTRACT: 
This paper investigates the association between night-time lights and socio-economic metrics at the regional level. This regional 
level of understanding is critical as it underpins much economic monitoring and policy-making for sustainable development. Stable 
light data obtained from night time images of 2001, captured by Defense Meteorological Satellite Program — Operational Linescan 
System (DMSP-OLS) satellite, are used in the study. The data records artificial lights from human habitations from the earth surface 
and is a surrogate of the level of development of an area. Data on socio economic metrics at the sub-national level for the year 2001 
for the state of Maharashtra in India have been sourced from Primary Census Abstract of India, 2001. However, most of the socio 
economic variables are not available at the village level. This paper describes the process of deriving maps of census metrics not 
collected by Indian census for small regions (such as villages) using DMSP-OLS images that are otherwise unavailable. Linear 
regression models with correlation coefficients ranging from 0.75 to 0.90 (p « 0.05) at the district and the taluk level from the night- 
time satellite images were used to predict these census metrics for villages. Maps are produced for villages. Errors associated with 
the Modifiable Areal Unit Problem (MAUP) and ecological fallacies are also discussed. The paper concludes with an overall 
assessment of the results at these various spatial scales. 
1. INTRODUCTION 
Night-time satellite images of the earth are recorded by the 
Operational  Linescan System onboard the Defense 
Meteorological Satellite Programme (DMSP-OLS) group of 
satellites. This is a passive sun synchronous satellite capable of 
capturing artificial lights at nights from the earth surface in the 
visible and near-infrared regions of the electromagnetic 
spectrum. Initially the satellite was launched with the purpose 
of recording cloud covers and cloud — top temperatures over the 
earth surface by the US Department of Defense (DoD). 
However, in late 1970s it was discovered that the data obtained 
from the OLS sensor can record lights from cities at night (Croft 
1978; Welch & Zupko 1980). The digital archives of the 
datasets are available since 1992. From that time, this dataset 
had been used for a wide range of applications. The data was 
used to estimate the population of the countries of the world 
(Elvidge, CD et al. 1997) and estimating population without 
access to electricity (Doll, C. N. H. & Pachauri 2010). The first 
global map of the GDP purchasing Power Parity (GDP-PPP) 
(Doll, C. N. H., Muller & Elvidge 2000) and economies (Ghosh 
et al. 2009) were mapped using DMSP-OLS night-time images. 
Gas flares on the earth surface (Elvidge, C et al. 2009) were also 
mapped using this data product. Radiance calibrated DMSP- 
OLS data were used to map urban and suburban extent around 
cities (Roychowdhury, K, Jones, SD & Arrowsmith, C 2009; 
Roychowdhury, Taubenboeck & Jones 2011) and for modelling 
socio-economic parameters as well as urban population data 
(Doll, C. N. H. 2008; Doll, C. N. H, Muller & 
  
Morley 2006; Doll, C. N. H., Muller & Elvidge 2000; Sutton 
2003). However, most of these works were carried out at the 
global and national level. In the past few years, the utility of the 
night-time datasets were assessed at the sub-national level. At 
the smaller spatial scale, radiance calibrated DMSP-OLS 
dataset was used to estimate population and other socio 
economic metrics for the state of Maharashtra in India 
(Roychowdhury, K, Jones, S & Arrowsmith, C 2009). High and 
low gain radiance calibrated data was used separately for 
predicting census metrics at different spatial scales 
(Roychowdhury et al. 2011a). The association between night 
lights and GDP estimates for India at the district level was 
carried out using DMSP-OLS night-time images from 2008 
(Bhandari & Roychowdhury 2012). 
This paper builds on the previous works of the authors. Satellite 
images captured by DMSP-OLS were used by the authors to 
propose a surrogate census method for small administrative 
regions (that is, districts and taluks) (Roychowdhury et al. 
2011b; Roychowdhury et al. 2010). The satellite images are 
used in association with the data from last completed Indian 
census (also conducted in 2001). The study focuses on the state 
of Maharashtra in western India (fig 1). This paper examines the 
application of the models proposed to predict and map the 
metrics for the villages that are unavailable from traditional 
census statistics. These metrics include: number of female 
literates per square kilometre; 
* 
Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author. 
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