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2 May 2012 Using GIS databases for simulated nightlight imagery
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Proposed is a new technique for simulating nighttime scenes with realistically-modelled urban radiance. While nightlight imagery is commonly used to measure urban sprawl,1 it is uncommon to use urbanization as metric to develop synthetic nighttime scenes. In the developed methodology, the open-source Open Street Map (OSM) Geographic Information System (GIS) database is used. The database is comprised of many nodes, which are used to dene the position of dierent types of streets, buildings, and other features. These nodes are the driver used to model urban nightlights, given several assumptions. The rst assumption is that the spatial distribution of nodes is closely related to the spatial distribution of nightlights. Work by Roychowdhury et al has demonstrated the relationship between urban lights and development. 2 So, the real assumption being made is that the density of nodes corresponds to development, which is reasonable. Secondly, the local density of nodes must relate directly to the upwelled radiance within the given locality. Testing these assumptions using Albuquerque and Indianapolis as example cities revealed that dierent types of nodes produce more realistic results than others. Residential street nodes oered the best performance for any single node type, among the types tested in this investigation. Other node types, however, still provide useful supplementary data. Using streets and buildings dened in the OSM database allowed automated generation of simulated nighttime scenes of Albuquerque and Indianapolis in the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. The simulation was compared to real data from the recently deployed National Polar-orbiting Operational Environmental Satellite System(NPOESS) Visible Infrared Imager Radiometer Suite (VIIRS) platform. As a result of the comparison, correction functions were used to correct for discrepancies between simulated and observed radiance. Future work will include investigating more advanced approaches for mapping the spatial extent of nightlights, based on the distribution of dierent node types in local neighbourhoods. This will allow the spectral prole of each region to be dynamically adjusted, in addition to simply modifying the magnitude of a single source type.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joshua D. Zollweg, Michael Gartley, John Roskovensky, and Jeffery Mercier "Using GIS databases for simulated nightlight imagery", Proc. SPIE 8396, Geospatial InfoFusion II, 83960C (2 May 2012);


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