Radiance Calibration of DMSP-OLS Low-Light Imaging Data of Human Settlements

doi:10.1016/S0034-4257(98)00098-4

Remote Sensing of Environment

Volume 68, Issue 1, April 1999, Pages 77-88

https://doi.org/10.1016/S0034-4257(98)00098-4 Get rights and content

Abstract

Nocturnal lighting is a primary method for enabling human activity. Outdoor lighting is used extensively worldwide in residential, commercial, industrial, public facilities, and roadways. A radiance calibrated nighttime lights image of the United States has been assembled from Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). The satellite observation of the location and intensity of nocturnal lighting provide a unique view of humanities presence and can be used as a spatial indicator for other variables that are more difficult to observe at a global scale. Examples include the modeling of population density and energy related greenhouse gas emissions.

Introduction

Much of global change research is dedicated to discerning and documenting the impacts of human activities on natural systems. Human population numbers have expanded from ∼750 million in the mid-1700s, will reach 6 billion in 1999, and could double in the next 49 years if current growth continues (Haub and Cornelius, 1998). Human activities which are known to be cumulatively altering the global environment include greenhouse gas emissions from fossil fuel consumption, air and water pollution, and land cover/land use change.

Far from being evenly distributed across the land surface, to a great extent human activities with environmental consequences are concentrated in or near human population centers. One approach to modeling the spatial distribution of human activities is to use population density as an indicator for the phenomenon of interest (e.g., the percent coverage of impermeable surfaces). There are two primary disadvantages to using population density as an indicator for human activities with environmental consequences. At a global level, population density is not well characterized. Currently available global population density grids cover approximately 60 sq km per data cell (Tobler et al., 1995), far too coarse for many environmental applications. In areas where high spatial resolution population density data sets are available, the environmental applicability of the data suffer due to the fact that population density is defined as a residential parameter. As a result transportation corridors, public, commercial, and industrial zones have very low population density. In many cases these areas have much higher densities of people present 8–12 h/day than the associated residential zones. Thus the use of population density as an indicator for percent of land area covered by impermeable surface (roads, roofs, parking lots) would result in a substantial skewing of the results towards residential areas.

Having a capability for direct global observation of a widespread and distinctly human activity that varies in intensity could substantially improve understanding of the magnitude of humanities presence and modeling human impacts on the environment. Available satellites sensors with global data acquisition capabilities have all focused on the observation of natural systems as their design criteria. If global observation of human activity was set as a design criteria, what wavelength(s) would be investigated? Radio frequencies emitted by power lines, electrical devices, and cellular telephones might be a good starting point! As an alternative, we have been investigating the nocturnal observation of artificial lighting as a measure or indicator of human activity using data collected by the U.S. Air Force Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). This instrument has a low-light imaging capability, which was designed for the observation of clouds illuminated by moonlight. In addition to moonlit clouds, the data can be used to detect light sources present at the Earth’s surface.

We have explored the gain control of the OLS and discovered that it is possible to adjust the gain to cover the range of radiances encountered from brightly lit commercial centers in the largest cities down to residential areas in urban, suburban, and many rural settings. The OLS low-light imaging data can be converted to brightness values based on the preflight calibration of the OLS sensor. The objective of this article is to review the low-light imaging features of the OLS, to describe methods used for the assembly of radiance calibrated nighttime lights products of the United States, and to compare this product to several other data types.

Section snippets

Background

Since 1970 the DMSP has operated polar orbiting satellite sensors capable of low-light imaging the Earth at night. Using light intensifying photomultiplier tube technology, these sensors were designed to observe clouds illuminated by moonlight using a single broad spectral band (Fig. 1). With sunlight eliminated, it possible to also detect city lights, gas flares, and fires. From 1970 to 1975 DMSP Blocks 5A, B, and C flew equipped with the SAP (Sensor Aerospace Vehicle Electronics Package). The

Ols low-light imaging gain control

An optical instrument’s gain can be thought of as the amplification of the incoming signal, from the front end of the telescope to the output of the digital number data stream. The full system contains both gains and losses; however, the overall system amplifies the original signal. The OLS has analog preamplifiers and postamplifier with fixed gains as well as VDGA (Variable Digital Gain Amplifier) gain. The gain of the photomultiplier tube (PMT) also contributes to the overall system gain for

Data acquisition

In early 1996, NGDC requested and received permission from the DMSP program office to acquire OLS data at reduced gain settings, with onboard ASGC (along scan gain control) and BDRF functions turned off. The “low-gain” data acquisition was requested for an 8-night period, corresponding to the darkest nights in March 1996, with a start date of 16 March. In order to avoid interference with ongoing observations of the leading edge of the aurora at high northern latitudes, the NGDC request was for

Data processing

As a first step in the processing, sections (suborbits) of usable nighttime lights data were extracted from the original full orbit files. The data processing then involved the following primary steps: 1) establishment of a reference grid; 2) identification and geolocation of lights, clouds, and coverage areas; 3) establishing a digital number to radiance scale for the final product; 4) cloud-free compositing within two overlapping gain ranges (high and low); 5) threshold to eliminate isolated

Results and discussion

Figure 8 is a color-coded image of the radiance calibrated nighttime lights of the United States from 1996–1997. For comparison, the 1994–1995 stable lights product of the United States (Elvidge et al., 1997a), is shown in Figure 9. As with the 1994–1995 stable lights data, the radiance calibrated product shows the cities and many of the smaller towns of the United States. Two major differences have been identified in the spatial information content of the radiance calibrated lights when

Conclusion

Nocturnal lighting could be regarded as one of the defining features of concentrated human activity. The spatial linkage between nocturnal lighting and the locations of concentrated human activity suggests the possibility that observations of the extent or brightness of nocturnal lighting may be used to make spatially explicit estimates population numbers, levels of economic activity, power consumption, or even greenhouse gas emissions.

We have produced a radiance calibrated nighttime lights

Acknowledgements

The authors gratefully acknowledge the Defense Meteorological Satellite Program (DMSP) and the Air Force Weather Agency for their cooperation in the acquisition of the reduced gain OLS data used in this study. This research was supported in part by the NASA EOS Interdiciplinary Science (IDS) Project: Assessing the Impact of Expanding Urban Land Use on Agricultural Productivity Using Remote Sensing Data and Physically-Based Soil Productivity Models.

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Radiance Calibration of DMSP-OLS Low-Light Imaging Data of Human Settlements

Abstract

Introduction

Section snippets

Background

Ols low-light imaging gain control

Data acquisition

Data processing

Results and discussion

Conclusion

Acknowledgements

Atmos. Res.

Remote Sens. Environ.

Remote Sens. Environ.

Burning waste gas in oil fields

Nature

Nighttime images of the earth from space

Sci. Am.

The brightness of lights on Earth at night, digitally recorded by DMSP satellite, Stanford Research Institute Final Report

The 1-km AVHRR global land data setfirst stages in implementation

Int. J. Remote Sens.

Mapping of city lights using DMSP Operational Linescan System data

Photogramm. Eng. Remote Sens.

Relation between satellite observed visible–near infrared emissions, population, and energy consumption

Int. J. Remote Sens.