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Tsukuba, Japan

Letu H.,Tokai University | Letu H.,Inner Mongolia Normal University | Hara M.,VisionTech Inc. | Tana G.,Chiba University | And 3 more authors.
Environmental Science and Technology

Nighttime lights of the human settlements (hereafter, "stable lights") are seen as a valuable proxy of social economic activity and greenhouse gas emissions at the subnational level. In this study, we propose an improved method to generate the stable lights from Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) daily nighttime light data for 1999. The study area includes Japan, China, India, and other 10 countries in East Asia. A noise reduction filter (NRF) was employed to generate a stable light from DMSP/OLS time-series daily nighttime light data. It was found that noise from amplitude of the 1-year periodic component is included in the stable light. To remove the amplitude of the 1-year periodic component noise included in the stable light, the NRF method was improved to extract the periodic component. Then, new stable light was generated by removing the amplitude of the 1-year periodic component using the improved NRF method. The resulting stable light was evaluated by comparing it with the conventional nighttime stable light provided by the National Oceanic and Atmosphere Administration/National Geophysical Data Center (NOAA/NGDC). It is indicated that DNs of the NOAA stable light image are lower than those of the new stable light image. This might be attributable to the influence of attenuation effects from thin warm water clouds. However, due to overglow effect of the thin cloud, light area in new stable light is larger than NOAA stable light. Furthermore, the cumulative digital numbers (CDNs) and number of light area pixels (NLAP) of the generated stable light and NOAA/NGDC stable light were applied to estimate socioeconomic variables of population, electric power consumption, gross domestic product, and CO2 emissions from fossil fuel consumption. It is shown that the correlations of the population and CO2FF with new stable light data are higher than those in NOAA stable light data; correlations of the EPC and GDP with NOAA stable light data are higher those in the new stable light data. (Figure Presented). © 2015 American Chemical Society. Source

Chen H.,University of Tokyo | Chen H.,Zhejiang GongShang University | Ito Y.,University of Tokyo | Sawamukai M.,VisionTech Inc. | Tokunaga T.,University of Tokyo
Natural Hazards

A simple flood hazard assessment based on GIS and multicriteria decision analysis was presented, and the sensitivity analysis was applied to evaluate the uncertainty of input factors. The location chosen for the study is the Kujukuri Plain, Chiba Prefecture, Japan. The model incorporates six factors: river system, elevation, depression area, ratio of impermeable area, detention ponds, and precipitation. A hazard map for the year 2004, as an example, was obtained. The method of analytic hierarchy process was applied to calculate the weighting values of each factor. The hazard map was compared with the actual flood area, and good coincidence was found between them. The relative importance and uncertainty of the six input factors and weights were evaluated by using the global sensitivity analysis, i.e., extended FAST method, and the results showed a robust behavior of the model. The flood hazard assessment method presented here is meaningful for the flood management and environment protection in the area under the similar condition as this study. © 2015 Springer Science+Business Media Dordrecht Source

Letu H.,Tokai University | Tana G.,Chiba University | Bagan H.,Japan National Institute of Environmental Studies | Hara M.,VisionTech Inc. | Nishio F.,Chiba University
International Journal of Environmental Studies

A stable light image for south-eastern Asia was extracted from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) night-time imagery for 1999. The accuracy assessment of the stable light image has been completed using two methods: a reference data-based comparison and a stratified random sampling method. The stable light image was compared with the conventional stable light image for 1999 and the Landsat ETM+ 2000 image for the Kanto region of Japan. The results show that the digital numbers of the new stable light image (almost <20) in the non-urban area are much lower than those of the conventional stable light image (almost >60) because the new stable light image includes little noise. The stratified random sampling method could assess the accuracy for both the new stable light image and the conventional stable light image in Asia by classifying the images into stable and non-stable light areas. © 2010 Taylor & Francis. Source

Letu H.,Tokai University | Tana G.,Chiba University | Hara M.,VisionTech Inc. | Nishio F.,Chiba University
International Geoscience and Remote Sensing Symposium (IGARSS)

In this study, we attempted to estimate the electric power consumption using the Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) stable light imagery after correction for saturation effected. Digital numbers (DNs) of a stable light image are saturated in the center of city areas. Thus, we developed a saturated light correction method for the DMSP/OLS stable light image using the radiance calibration image of DMSP/OLS nighttime imagery. The comparison between the stable light image for 1999 and the radiance calibration image for 1996-1997 in major areas of Japan showed a strong linear correlation (Ysta = 17Xrad - 102) between the DNs of both images. Saturated DNs of the stable light image could therefore be corrected based on the correlation equation between the two images. To estimate the electric power consumption, regression analysis was performed between statistic data of electric power consumption from lighting and cumulative DNs of the stable light image before and after correcting for the saturation effects using the new and the conventional methods of the cubic regression equation (CRE). There is a stronger improvement of the determination coefficient with the new saturated light correction method (R2=0.91, P=4.5•106<0.05) than with the conventional method (R 2=0.81, P=2.6•106<0.05) from the initial correlation with the uncorrected data (R2=0.70, P=1.7•10 6<0.05). © 2011 IEEE. Source

VISIONTECH Corporation | Date: 2012-07-31

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