Aladdin's Magic Lamp: Developing Methods for Calibration and Geolocation Accuracy Assessment of the DMSP OLS

Nighttime satellite imagery from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) has a unique capability to observe nocturnal light emissions from sources including cities, wild fires, and gas flares. Data from the DMSP OLS is used in a wide range of studies including mapping urban areas, estimating informal economies, and estimating urban populations. Given the extensive and increasing list of applications a repeatable method for assessing geolocation accuracy, performing inter-calibration, and defining the minimum detectable brightness would be beneficial. An array of portable lights was designed and taken to multiple field sites known to have no other light sources. The lights were operated during nighttime overpasses by the DMSP OLS and observed in the imagery. A first estimate of the minimum detectable brightness is presented based on the field experiments conducted. An assessment of the geolocation accuracy was performed by measuring the distance between the GPS measured location of the lights and the observed location in the imagery. A systematic shift was observed and the mean distance was measured at 2.9km. A method for in situ radiance calibration of the DMSP OLS using a ground based light source as an active target is presented. The wattage of light used by the active target strongly correlates with the signal measured by the DMSP OLS. This approach can be used to enhance our ability to make inter-temporal and inter-satellite comparisons of DMSP OLS imagery. Exploring the possibility of establishing a permanent active target for the calibration of nocturnal imaging systems is recommended. The methods used to assess the minimum detectable brightness, assess the geolocation accuracy, and build inter-calibration models lay the ground work for assessing the energy expended on light emitted into the sky at night. An estimate of the total energy consumed to light the night sky globally is presented.

Governance and Uncertainty

Government actors create law against a backdrop of uncertainty. Limited information, unpredictable events, and lack of understanding interfere with accurately predicting a legal regime’s costs, benefits, and effects on other legal and social programs and institutions. Does the availability of no-fault divorce increase the number of terminated marriages? Will bulk-collection of telecommunications information about American citizens reveal terrorist plots? Can a sensitive species breed in the presence of oil and gas wells? The answers to these questions are far from clear, but lawmakers must act nonetheless. The problems posed by uncertainty cut across legal fields. Scholars and regulators in a variety of contexts recognize the importance of uncertainty, but no systematic, generally-applicable framework exists for determining how law should account for gaps in information. This Article suggests such a framework and develops a novel typology of strategies for accounting for uncertainty in governance. This typology includes “static law,” as well as three varieties of “dynamic law.” “Static law” is a legal rule initially intended to last in perpetuity. “Dynamic law” is intended to change, and includes: (1) durational regulation, or fixed legal rules with periodic opportunities for amendment or repeal; (2) adaptive regulation, or malleable legal rules with procedural mechanisms allowing rules to change; and (3) contingent regulation, or malleable legal rules with triggering mechanisms to substantively change to the rules. Each of these strategies, alone or in combination, may best address the uncertainty inherent in a particular lawmaking effort. This Article provides a diagnostic framework that lawmakers can use to identify optimal strategies. Ultimately, this approach to uncertainty yields immediate practical benefits by enabling lawmakers to better structure governance.