Estimating energy consumption from night-time DMPS/OLS imagery after correcting for saturation effects
Top Cited Papers
- 20 August 2010
- journal article
- research article
- Published by Taylor & Francis Ltd in International Journal of Remote Sensing
- Vol. 31 (16), 4443-4458
- https://doi.org/10.1080/01431160903277464
Abstract
A methodology is presented to accurately estimate electric power consumption from saturated night-time Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) imagery using a stable light correction. An area correction for the stable light image of DMSP/OLS for the year 1999 was performed and the build-up area rate data were used to clarify the intensity distribution characteristics of the stable light. Based on the spatial distribution characteristics of the stable light, the saturation light of the electric power supply area of Japan was corrected using a cubic regression equation. The regression between the correction calculations by the cubic regression equation and the statistical electric power consumption data was applied in Japan and also in China, India and 10 other Asian countries. The correction method was then evaluated. This study confirms that electric power consumption can be estimated with high precision from the stable light.Keywords
This publication has 17 references indexed in Scilit:
- Global Distribution and Density of Constructed Impervious SurfacesSensors, 2007
- Mapping regional economic activity from night-time light satellite imageryEcological Economics, 2006
- U.S. constructed area approaches the size of OhioEos, 2004
- Trends in night-time city lights and vegetation indices associated with urbanization within the conterminous USAInternational Journal of Remote Sensing, 2004
- Validation of urban boundaries derived from global night-time satellite imageryInternational Journal of Remote Sensing, 2003
- Night-time Imagery as a Tool for Global Mapping of Socioeconomic Parameters and Greenhouse Gas EmissionsAMBIO, 2000
- Radiance Calibration of DMSP-OLS Low-Light Imaging Data of Human SettlementsRemote Sensing of Environment, 1999
- Using DMSP-OLS light frequency data to categorize urban environments associated with US climate observing stationsInternational Journal of Remote Sensing, 1998
- Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumptionInternational Journal of Remote Sensing, 1997
- Using nighttime DMSP/OLS images of city lights to estimate the impact of urban land use on soil resources in the United StatesRemote Sensing of Environment, 1997