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Author Chang, Y.; Wang, S.; Zhou, Y.; Wang, L.; Wang, F.
Title (up) A Novel Method of Evaluating Highway Traffic Prosperity Based on Nighttime Light Remote Sensing Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 1 Pages 102
Keywords Remote Sensing
Abstract As the backbone and arteries of a comprehensive transportation network, highways play an important role in improving people’s living standards and promoting economic growth. However, globally, there is limited quantifiable data evaluating the highway traffic state, characteristics, and performance. From the 1960s to the present, remote sensing has been regarded as the most effective technology for long-term and large-scale monitoring of surface information. However, how to reflect the dynamic “flow” information of traffic with a static remote sensing image has always been a difficult problem that is hard to solve in the field. This study aims to construct a method of evaluating highway traffic prosperity using nighttime remote sensing. First, based on nighttime light data that indicate social and economic activities, a highway-oriented method was proposed to extract highway nighttime light data from 2015 annual nighttime light data of the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite sensor (SNPP-VIIRS). Subsequently, Pearson correlation analysis was used to fit the relationship between freeway traffic flow volume and freeway nighttime light at the provincial level. The results showed that Pearson Correlation Coefficient of freeway nighttime light and freeway traffic flow volume for coach and truck are 0.905 and 0.731, respectively, which are higher than between freeway traffic flow volume for coach and truck and total nighttime light (0.593 and 0.516, respectively). A new index—Highway Nighttime Traffic Prosperity Index (HNTPI)—was proposed to evaluate highway traffic across China. The results showed that HNTPI has a strong correspondence with socio-economic parameters. The Pearson Correlation Coefficient of HNTPI and gross domestic product (GDP) per capita, consumption per capita, and population are 0.772, 0.895, and 0.968, respectively. There is a huge spatial heterogeneity in China nighttime traffic, the prosperity degree of highway traffic in developed coastal areas is obviously higher than that inland. The national general highway is the most prosperous highway at night and the national general highway nighttime prosperity of Shanghai reached 22.34%. This research provides basic data for the long-term monitoring and evaluation of regional traffic operation at night and research on the correlation between regional highway construction and the economy.
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ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2801
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Author Ashford, O.M.
Title (up) A portable cloud searchlight Type Journal Article
Year 1947 Publication Weather Abbreviated Journal
Volume 2 Issue Pages 103-104
Keywords Remote Sensing
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Notes Approved no
Call Number GFZ @ kyba @ Serial 2044
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Author Li, X.; Li, X.; Li, D.; He, X.; Jendryke, M.
Title (up) A preliminary investigation of Luojia-1 night-time light imagery Type Journal Article
Year 2019 Publication Remote Sensing Letters Abbreviated Journal Remote Sensing Letters
Volume 10 Issue 6 Pages 526-535
Keywords Remote Sensing; Instrumentation
Abstract Launched on 2 June 2018, Luojia-1 satellite records night-time light imagery at 130 m resolution, which is higher than most of the existing night-time light images to date. This study evaluated radiometric and spatial properties of the Luojia-1 satellite imagery for cities of Los Angeles, Wuhan and Rome as well as the change detection capability for Zunyi city. For the radiometric property, the analysis shows that the Luojia-1 images correlate well with the radiance of the Visible Infrared Imaging Radiometer Suite (VIIRS)’s Day and Night Band (DNB), and that the Luojia-1 images have a wider range of radiance values, as well as higher radiance values (e.g., 40%–90% higher) than the VIIRS DNB images. Using wavelet decomposition and change detection analysis to evaluate spatial property and change detection capability, it was found that the Luojia-1 images provide abundant spatial detail information, with about 20%–54% energy of wavelet component of the images stored in 100–400 m resolutions, and they can help to track the electrification of new roads and buildings at a fine resolution. This study shows that the Luojia-1 images are an effective data source for analysing spatiotemporal distribution of night-time light and its associated socioeconomic attributes.
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ISSN 2150-704X ISBN Medium
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Notes Approved no
Call Number GFZ @ kyba @ Serial 2199
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Author Letu, H.; Hara, M.; Tana, G.; Nishio, F.
Title (up) A Saturated Light Correction Method for DMSP/OLS Nighttime Satellite Imagery Type Journal Article
Year 2012 Publication IEEE Transactions on Geoscience and Remote Sensing Abbreviated Journal IEEE Trans. Geosci. Remote Sensing
Volume 50 Issue 2 Pages 389-396
Keywords DMSP-OLS; remote sensing; light at night; radiometry; calibration
Abstract Several studies have clarified that electric power consumption can be estimated from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) stable light imagery. As digital numbers (DNs) of stable light images are often saturated in the center of city areas, we developed a saturated light correction method for the DMSP/OLS stable light image using the nighttime radiance calibration image of the DMSP/OLS. The comparison between the nonsaturated part of the stable light image for 1999 and the radiance calibration image for 1996-1997 in major areas of Japan showed a strong linear correlation (R2 = 92.73) 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 evaluate the new saturated light correction method, a regression analysis is performed between statistic data of electric power consumption from lighting and the cumulative DNs of the stable light image before and after correcting for the saturation effects by the new method, in comparison to the conventional method, which is, the cubic regression equation method. The results show a stronger improvement in the determination coefficient with the new saturated light correction method (R2 = 0.91, P = 1.7 ·10-6 <; 0.05) than with the conventional method (R2 = 0.81, P = 2.6 ·10-6 <; 0.05) from the initial correlation with the uncorrected data (R2 = 0.70, P = 4.5 · 10-6 <; 0.05). The new method proves therefore to be very efficient for saturated light correction.
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ISSN 0196-2892 ISBN Medium
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Notes Approved no
Call Number IDA @ john @ Serial 204
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Author Sutton, P.C.
Title (up) A scale-adjusted measure of “Urban sprawl” using nighttime satellite imagery Type Journal Article
Year 2003 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment
Volume 86 Issue 3 Pages 353-369
Keywords Urban sprawl; Sprawl Line; Nighttime satellite imagery; DMSP-OLS; remote sensing; satellite; llight at night
Abstract “Urban Sprawl” is a growing concern of citizens, environmental organizations, and governments. Negative impacts often attributed to urban sprawl are traffic congestion, loss of open space, and increased pollutant runoff into natural waterways. Definitions of “Urban Sprawl” range from local patterns of land use and development to aggregate measures of per capita land consumption for given contiguous urban areas (UA). This research creates a measure of per capita land use consumption as an aggregate index for the spatially contiguous urban areas of the conterminous United States with population of 50,000 or greater. Nighttime satellite imagery obtained by the Defense Meteorological Satellite Program's Operational Linescan System (DMSP OLS) is used as a proxy measure of urban extent. The corresponding population of these urban areas is derived from a grid of the block group level data from the 1990 U.S. Census. These numbers are used to develop a regression equation between Ln(Urban Area) and Ln(Urban Population). The ‘scale-adjustment’ mentioned in the title characterizes the “Urban Sprawl” of each of the urban areas by how far above or below they are on the “Sprawl Line” determined by this regression. This “Sprawl Line” allows for a more fair comparison of “Urban Sprawl” between larger and smaller metropolitan areas because a simple measure of per capita land consumption or population density does not account for the natural increase in aggregate population density that occurs as cities grow in population. Cities that have more “Urban Sprawl” by this measure tended to be inland and Midwestern cities such as Minneapolis–St. Paul, Atlanta, Dallas–Ft. Worth, St. Louis, and Kansas City. Surprisingly, west coast cities including Los Angeles had some of the lowest levels of “Urban Sprawl” by this measure. There were many low light levels seen in the nighttime imagery around these major urban areas that were not included in either of the two definitions of urban extent used in this study. These areas may represent a growing commuter-shed of urban workers who do not live in the urban core but nonetheless contribute to many of the impacts typically attributed to “Urban Sprawl”. “Urban Sprawl” is difficult to define precisely partly because public perception of sprawl is likely derived from local land use planning decisions, spatio-demographic change in growing urban areas, and changing values and social mores resulting from differential rates of international migration to the urban areas of the United States. Nonetheless, the aggregate measures derived here are somewhat different than similar previously used measures in that they are ‘scale-adjusted’; also, the spatial patterns of “Urban Sprawl” shown here shed some insight and raise interesting questions about how the dynamics of “Urban Sprawl” are changing.
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ISSN 0034-4257 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ john @ Serial 233
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