Tilottama Ghosh

A global poverty map derived from satellite data

A global poverty map has been produced at 30arcsec resolution using a poverty index calculated by dividing population count (LandScan 2004) by the brightness of satellite observed lighting (DMSP nighttime lights). Inputs to the LandScan product include satellite-derived land cover and topography, plus human settlement outlines derived from high-resolution imagery. The poverty estimates have been calibrated using national level poverty data from the World Development Indicators (WDI) 2006 edition. The total estimate of the numbers of individuals living in poverty is 2.2 billion, slightly under the WDI estimate of 2.6 billion. We have demonstrated a new class of poverty map that should improve over time through the inclusion of new reference data for calibration of poverty estimates and as improvements are made in the satellite observation of human activities related to economic activity and technology access.

Estimation of Mexico’s Informal Economy and Remittances Using Nighttime Imagery

Abstract: Accurate estimates of the magnitude and spatial distribution of both formal and informal economic activity have many useful applications. Developing alternative methods for making estimates of these economic activities may prove to be useful when other measures are of suspect accuracy or unavailable. This research explores the potential for estimating the formal and informal economy for Mexico using known relationships between the spatial patterns of nighttime satellite imagery and economic activity in the United States (U.S.). Regression models have been developed between spatial patterns of nighttime imagery and Adjusted Official Gross State Product ( AGSP ) for the U.S. states. These regression parameters derived from the regression models of the U.S. were ‘blindly’ applied to Mexico to estimate the Estimated Gross State Income ( EGSI ) at the sub-national level and the Estimated Gross Domestic Income ( EGDI ) at the national level. Comparison of the EGDI estimate of Mexico against the official Gross National Income (

Paving the planet: impervious surface as proxy measure of the human ecological footprint

Fundamental questions regarding the human-environment-sustainability problematic remain contested. What are the relative roles of population, consumption, and technology with respect to sustainability? How can sustainability be measured? Numerous metrics have been developed to address these controversial questions including ideas of carrying capacity, environmental sustainability indices, and ecological footprints. This work explores the question: is pavement a proxy measure of human impact on the environment? We explore and evaluate the use of satellite derived density grids of constructed area (aka ‘pavement’ or ‘impervious surface’) in the calculation of national and subnational ‘ecological footprints’. We generated a global constructed area density grid for the 2000—2001 period using satellite observed nighttime lights and a population count grid from the US Department of Energy. Satellite data inputs to the population product include MODIS landcover, SRTM topography and high-resolution imagery. Calibration of the global constructed area density product was derived from high-resolution aerial photographs. We demonstrate that a satellite derived constructed area per person index can serve as a proxy measure of ecological footprints at both the national and subnational level. This relatively simple and globally uniform measure of human impact on the environment correlates strongly with other more difficult to obtain measures.

Overview of DMSP nightime lights and future possibilities

The Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) has a unique capability to collect low-light imaging data of the earth at night. The OLS and its predecessors have collected this style of data on a nightly global basis since 1972. The digital archive of OLS data extends back to 1992. Over the years several global nighttime lights products have been generated. NGDC has now produced a set of global cloud-free nighttime lights products, specifically processed for the detection of changes in lighting emitted by human settlements, spanning 1992-93 to 2008. While the OLS is far from ideal for observing nighttime lights, the DMSP nighttime lights products have been successfully used in modeling the spatial distribution of population density, carbon emissions, and economic activity.

Darkness on the edge of town : mapping urban and Peri-Urban Australia using nighttime satellite imagery

This article explores the use of nighttime satellite imagery for mapping urban and peri-urban areas of Australia. A population-weighted measure of urban sprawl is used to characterize relative levels of sprawl for Australias urban areas. In addition, the expansive areas of low light surrounding most major metropolitan areas are used to map the urban–bush interface of exurban land use. Our findings suggest that 82 percent of the Australian population lives in urban areas, 15 percent live in peri-urban or exurban areas, and 3 percent live in rural areas. This represents a significantly more concentrated human settlement pattern than presently exists in the United States.

DMSP-OLS Radiance Calibrated Nighttime Lights Time Series with Intercalibration

The Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) stable lights products are made using operational OLS data collected at high gain settings, resulting in sensor saturation on brightly lit areas, such as city centers. This has been a paramount shortcoming of the DMSP-OLS stable lights time series. This study outlines a methodology that greatly expands the dynamic range of the OLS data using observations made at different fixed-gain settings, and by incorporating the areas not affected by saturation from the stable lights product. The radiances for the fixed-gain data are computed based on each OLS sensor’s pre-flight calibration. The result is a product known as the OLS radiance calibrated nighttime lights. A total of eight global datasets have been produced, representing years from 1996 to 2010. To further facilitate the usefulness of these data for time-series analyses, corrections have been made to counter the sensitivity differences of the sensors, and coefficients are provided to adjust the datasets to allow inter-comparison.

VIIRS night-time lights

ABSTRACT The Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) collects global low-light imaging data that have significant improvements over comparable data collected for 40 years by the DMSP Operational Linescan System. One of the prominent features of DNB data is the detection of electric lighting present on the Earth’s surface. Most of these lights are from human settlements. VIIRS collects source data that could be used to generate monthly and annual science grade global radiance maps of human settlements with electric lighting. There are a substantial number of steps involved in producing a product that has been cleaned to exclude background noise, solar and lunar contamination, data degraded by cloud cover, and features unrelated to electric lighting (e.g. fires, flares, volcanoes). This article describes the algorithms developed for the production of high-quality global VIIRS night-time lights. There is a broad base of science users for VIIRS night-time lights products, ranging from land-use scientists, urban geographers, ecologists, carbon modellers, astronomers, demographers, economists, and social scientists.

Estimation of Mexico's informal economy using DMSP nighttime lights data

In many countries of the world governments are unable to accurately track the true magnitude of economic activity due to the large number of transactions upon which taxes are not paid. It is particularly easy to avoid paying taxes on cash transactions and on remittances transferred from outside of the country. In some cases the so called “informal economy” is believed to be a substantial fraction of a nations total gross domestic product (GDP). Using DMSP satellite observed nighttime lights we developed a calibration for estimating reported GDP for the 48 contiguous states of the USA, where the informal economy is rated as relatively low. We applied this calibration to estimate the GDP for the states of Mexico and compared these values to officially reported GDP and Gross National Income (GNI) values. We found that most states in Mexico have a surplus in lighting relative to their officially reported GDP. We attribute this surplus in lighting to the informal economy and have made estimates of the magnitude of this unreported component to the true GDP. The results are encouraging and suggest that this technique could be used in other countries where accurate GDP reporting is problematic.

Assessing Income Distribution at the District Level for India Using Nighttime Satellite Imagery

Several studies have been carried out relating nighttime lights with economic activity. But most studies relating nighttime lights with economic activity have focused on associating higher totals in economic activity with higher sum of lights across regions. The question addressed in this paper is how best to model the relationship of nighttime lights with not just the wealthy but also the relatively worse-off within a region. The implications of such an exercise are immense with respect to ascertaining income distribution aspects of any area. The methods developed in this paper explore the relation between households in different income brackets at the district level for India, and the radiance-calibrated nighttime image of 2004. Besides the radiance-calibrated data of 2004, estimates of household incomes and number of households in different income brackets, made by Indicus Analytics (specialized economic research firm, based in New Delhi, India) were used. The results were mapped and insights were drawn for all districts based on their socio-economic profile. These results illustrate the advantage of using this easily available data for determining income inequalities, especially in information-deficient countries such as India.

Estimating the Information and Technology Development Index (IDI) Using Nighttime Satellite Imagery

The International Telecommunication Union (ITU) has developed a tool known as the Information and Communication Technology Development Index (IDI) for measuring the development of countries as information societies. They found a close correlation between IDI and the Gross Domestic Product (GDP) per capita of countries. In this paper on the basis of this relationship we have tried to create a 30 arc-second grid of IDI. At first a disaggregated map of total economic activity was created from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) merged radiance-calibrated nighttime image of 2006 and the LandScan population grid of 2006. The GDP per capita was then calculated and an attempt was made to create the IDI grid. However, at the 30 arc-second resolution the GDP per capita was found to be less in the city centers than in the areas surrounding the city centers. Thus an estimated IDI grid at 30 arc-second resolution could not be created based on the relationship between GDP per capita and official IDI. Therefore, the finest resolution at which the estimated IDI map was created was at the state level for the South-East Asian countries. In a future endeavor, we intend to create an IDI grid of much finer resolution.