Night Lights and Economic Activity in India: A study using DMSP-OLS night time images

This paper investigates the association between night lights and GDP estimates for India at thedistrict level. While many studies are finding a high degree of association between economicactivity as measured through the Gross Domestic Product (GDP) and night lights internationally,there is a lack of understanding of whether and how night light data are correlated with economicactivity at the sub-national level in emerging economies. This achieves more significance ineconomic monitoring and policy-making as estimates of GDP are not available at geographicallydisaggregated level, and even if available there is a large time lag involved before they are released.Stable light data obtained from night time images of 2008 captured by Defense MeteorologicalSatellite 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 surrogateof the level of development of an area. The data on GDP at the district level for the year 2008have been sourced from Indicus Analytics that has used data from government sources and amethod of estimation suggested by the Central Statistical Office of the Government of India.Using multinomial non-linear regression techniques the paper finds that indeed GDP at thedistrict level is significantly explained by night lights in the area. It also finds that the non-linearityis much stronger for metropolitan cities where GDP levels are far higher than a linear model canexplain. Conversely, in areas where agriculture and forestry activities are higher, the use of nightlights in a linear model overestimates the GDP

Nexus of Health and Development: Modelling Crude Birth Rate and Maternal Mortality Ratio Using Nighttime Satellite Images

Health and development are intricately related. Although India has made significant progress in the last few decades in the health sector and overall growth in GDP, there are still large regional differences in both health and development. The main objective of this paper is to develop techniques for the prediction of health indicators for all the districts of India and examine the correlations between health and development. The level of electrification and district domestic product (DDP) are considered as two fundamental indicators of development in this research. These data, along with health metrics and the information from two nighttime satellite images, were used to propose the models. These successfully predicted the health indicators with less than a 7%–10% error. The chosen health metrics, such as crude birth rate (CBR) and maternal mortality rate (MMR), were mapped for the whole country at the district level. These metrics showed very strong correlation with development indicators (correlation coefficients ranging from 0.92 to 0.99 at the 99% confidence interval). This is the first attempt to use Visible Infrared Imaging Radiometer Suite (VIIRS) (satellite) imagery in a socio-economic study. This paper endorses the observation that areas with a higher DDP and level of electrification have overall better health conditions

Tracking the relationship between changing skyline and population growth of an Indian megacity using earth observation technology

Temporal analysis of Landsat-TM imageries reveals a saturated state of Kolkata (Calcutta) Metropolitan Area. However, the city has witnessed accelerated growth in real estate construction in recent past. This study applies digital photogrammetry to quantify the changes in Kolkata’s skyline. Recently, released SRTM DEM of 1 Arc Second and a digital surface model derived from WorldView-1 stereo images were used to account for the past and recent surface heights, respectively. Consequently, this paper examines whether the sustained addition in housing capacity has been necessarily driven by a growth in the urban population/number of households. Results show that 40.31% of the area experienced vertical growth, majorly by replacing older dwellings with taller apartment blocks. Further analysis reveals that part of these newly added residences has remained unoccupied as they were purchased by non-resident Indians for using as a second home or was never sold due to recent economic slowdown

The role of satellite data in census: Case study of an Indian State

Countries, such as India, conduct a census collection every ten years. Currently census in India is carried out manually, therefore suffering from a number of shortcomings including inconsistency issues, the Modifiable Areal Unit Problem (MAUP) and large temporal acquisition timeframes. This paper proposes a surrogate census method using satellite images captured at night by DMSP-OLS satellites to overcome some of these drawbacks. The lights on the earth surface captured by this satellite represent areas of human habitation. Correlations between stable lights and brightness information with available census metrics from the last Indian census (2001) were calculated using bootstrapping techniques. Linear regression and multivariate analyses were subsequently performed and models proposed for each of the selected census metrics (e.g population density, number of households per square Kilometre, percentage of households with cars, jeeps and vans, Per Capita District Domestic Product (PCDDP) and urban population density) with results ranging from r2 of 0.8 to 0.9 at the 95% confidence interval. Census metrics unavailable at spatial scales lower than districts were also predicted using the proposed models and maps were derived showing the predicted measures. The results demonstrate that DMSP-OLS night-time images may be successfully used to estimate census variables in real time