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Author Chen, X.; Nordhaus, W.
Title (up) A Test of the New VIIRS Lights Data Set: Population and Economic Output in Africa Type Journal Article
Year 2015 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 7 Issue 4 Pages 4937-4947
Keywords Remote Sensing
Abstract The present study analyses the new Visible Infrared Imaging Radiometer Suite (VIIRS) lights data to determine whether it can provide more accurate proxies for socioeconomic data in areas with poor quality data than proxies based on stable lights. Our analysis indicates that VIIRS lights are a promising supplementary source for standard measures on population and economic output at a small scale, especially for low population and economic density areas in Africa. The current analysis also suggests that in comparison to stable lights generated by the DMSP-OLS system, data generated by the VIIRS system provide more information to estimate population than output index. However, further analysis and formal statistical models are needed to evaluate the usefulness of VIIRS lights versus other lights products. With more advanced methods, there is also a potential to generate a synthetic index by combining different lights products to produce a better proxy measure for other indexes.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1534
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Author You, X.; Monahan, K.M.
Title (up) A thirst for development: mapping water stress using night-time stable lights as predictors of province-level water stress in China Type Journal Article
Year 2017 Publication Area Abbreviated Journal Area
Volume 49 Issue 4 Pages 477-485
Keywords Remote Sensing
Abstract Given the rapid development within China, the inequality of available water resources has been increasingly of interest. Current methods for assessing water stress are inadequate for province‐scale rapid monitoring. A more responsive indicator at a finer scale is needed to understand the distribution of water stress in China. This paper selected Defense Meteorological Satellite Program Operational Line‐scan System night‐time stable lights as a proxy for water stress at the province level in China from 2004 to 2012, as night‐time lights are closely linked with population density, electricity consumption and other social, economic and environmental indicators associated with water stress. The linear regression results showed the intensity of night‐time lights can serve as a predictive tool to assess water stress across provinces with an R2 from 0.797 to 0.854. The model worked especially well in some regions, such as East China, North China and South West China. Nonetheless, confounding factors interfered with the predictive relationship, including population density, level of economic development, natural resource endowment and industrial structures, etc. The model was not greatly improved by building a multi‐variable linear regression including agricultural and industrial indicators. A straightforward predictor of water stress using remotely sensed data was developed.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0004-0894 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2030
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Author Yao, Y.; Chen, D.; Chen, L.; Wang, H.; Guan, Q.
Title (up) A time series of urban extent in China using DSMP/OLS nighttime light data Type Journal Article
Year 2018 Publication PloS one Abbreviated Journal PLoS One
Volume 13 Issue 5 Pages e0198189
Keywords Remote Sensing
Abstract Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifications using remote sensing images, and these methods have such problems as large costs in labor and time and low precision. This study proposes an improved, simplified and flexible method for extracting urban extents over multiple scales and the construction of spatiotemporal models using DMSP/OLS nighttime light (NTL) for practical situations. This method eliminates the regional temporal and spatial inconsistency of thresholding NTL in large-scale and multi-temporal scenes. Using this method, we have extracted the urban extents and calculated the corresponding areas on the county, municipal and provincial scales in China from 2000 to 2012. In addition, validation with the data of reference data shows that the overall accuracy (OA), Kappa and F1 Scores were 0.996, 0.793, and 0.782, respectively. We increased the spatial resolution of the urban extent to 500 m (approximately four times finer than the results of previous studies). Based on the urban extent dataset proposed above, we analyzed changes in urban extents over time and observed that urban sprawl has grown in all of the counties of China. We also identified three patterns of urban sprawl: Early Urban Growth, Constant Urban Growth and Recent Urban Growth. In addition, these trends of urban sprawl are consistent with the western, eastern and central cities of China, respectively, in terms of their spatial distribution, socioeconomic characteristics and historical background. Additionally, the urban extents display the spatial configurations of urban areas intuitively. The proposed urban extent dataset is available for download and can provide reference data and support for future studies of urbanization and urban planning.
Address School of Information Engineering, China University of Geosciences, Wuhan, Hubei province, China
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1932-6203 ISBN Medium
Area Expedition Conference
Notes PMID:29795685 Approved no
Call Number GFZ @ kyba @ Serial 1924
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Author Pack, D. W., Coffman, C. M., & Santiago, J. R.
Title (up) A Year in Space for the CUbesat MULtispectral Observing System: CUMULOS Type Conference Article
Year 2019 Publication 33rd Annual AIAA/USU Conference on Small Satellites Abbreviated Journal
Volume SSC19-XI-01 Issue Pages
Keywords Remote Sensing
Abstract CUMULOS is a three-camera system flying as a secondary payload on the Integrated Solar Array and Reflectarray Antenna (ISARA) mission with the goals of researching the use of uncooled commercial infrared cameras for Earth

remote sensing and demonstrating unique nighttime remote sensing capabilities. Three separate cameras comprise the CUMULOS payload: 1) a visible (VIS) Si CMOS camera, 2) a shortwave infrared (SWIR) InGaAs camera, and 3) a longwave infrared (LWIR) vanadium oxide microbolometer. This paper reviews on-orbit operations during the past year, in-space calibration observations and techniques, and Earth remote sensing highlights from the first year of space

operations. CUMULOS operations commenced on 8 June 2018 following the successful completion of the primary ISARA mission. Some of the unique contributions from the CUMULOS payloads include: 1) demonstrating the use of bright stars for on-orbit radiometric calibration of CubeSat payloads, 2) acquisition of science-quality nighttime lights data at 130-m resolution, and 3) operating the first simple Earth observing infrared payloads successfully flown on a CubeSat. Sample remote sensing results include images of: cities at night, ship lights (including fishing vessels), oil industry gas flares, serious wildfires, volcanic activity, and daytime and nighttime clouds. The CUMULOS VIS camera has measured calibrated nightlights imagery of major cities such as Los Angeles, Singapore, Shanghai, Tokyo, Kuwait City, Abu Dhabi, Jeddah, Istanbul, and London at more than 5x the resolution of VIIRS. The utility of these data for measuring light pollution, and mapping urban growth and infrastructure development at higher resolution than

VIIRS is being studied, with an emphasis placed on Los Angeles. The “Carr”, “Camp” and “Woolsey” fires from the 2018 California fire season were imaged with all three cameras and results highlight the excellent wildfire imaging

performance that can be achieved by small sensors. The SWIR camera has exhibited extreme sensitivity to flare and fire hotspots, and was even capable of detecting airglow-illuminated nighttime cloud structures by taking advantage of the strong OH emissions within its 0.9-1.7 micron bandpass. The LWIR microbolometer has proven successful at providing cloud context imagery for our nightlights mapping experiments, can detect very large fires and the brightest flare hotspots, and can also image terrain temperature variation and urban heat islands at 300-m resolution. CUMULOS capabilities show the potential of CubeSats and small sensors to perform several VIIRS-like nighttime mission areas in which wide area coverage can be traded for greater resolution over a smaller field of view. The sensor

has been used in collaboration with VIIRS researchers to explore these mission areas and side-by-side results will be presented illustrating the capabilities as well as the limitations of small aperture LEO CubeSat systems.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ intern @ Serial 2736
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Author Wu, W.; Zhao, H.; Jiang, S.
Title (up) A Zipf's Law-Based Method for Mapping Urban Areas Using NPP-VIIRS Nighttime Light Data Type Journal Article
Year 2018 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 10 Issue 1 Pages 130
Keywords Remote Sensing
Abstract A significant difficulty in urban studies is obtaining urban areas. Nighttime light (NTL) data provide efficient approaches to map urban areas. Previous methods have utilized visual particularities of cities with ancillary data to obtain the optimal thresholds. How cities behave differently from rural areas should be considered. A Zipf’s law-based method is proposed to bootstrap the optimal threshold based on the statistical properties of a Zipf’s law model on continuous thresholds at the country scale. In our method, the Zipf’s law model is utilized to quantify fractal, self-organized, and agglomeration behaviors of cities. The three-phase cluster dynamics are discovered and the abrupt transition between Phase 1 and Phase 2 denotes the rural-urban demarcation point. The urban areas are derived by the proposed method from the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data in 2013 in China. An accuracy assessment is conducted to compare it with the GlobeLand30-2010 data and the overall accuracy has directly confirmed the effectiveness of the method. The validation using point of interest (POI) data verifies that the urban areas show strong responses to social interactions and production with R2 values of 0.91 and 0.92, respectively, implying that the city areas extracted by our method can be a proxy for human activities. Comparisons with existing methods validate the effectiveness and high degree of automation of the proposed method in mapping urban areas at the country level. According to our analyses, the Zipf’s law-based method shows great potential to provide a universal criterion to map urban areas from the perspective of the behaviors of urban systems without ancillary data, and a valuable tool for spatial and temporal urban studies.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1797
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