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Author You, X.; Monahan, K.M.
Title 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 (up) GFZ @ kyba @ Serial 2030
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Author Kohiyama, M.; Hayashi, H.; Maki, N.; Higashida, M.; Kroehl, H.W.; Elvidge, C.D.; Hobson, V.R.
Title Early damaged area estimation system using DMSP-OLS night-time imagery Type Journal Article
Year 2004 Publication International Journal of Remote Sensing Abbreviated Journal International Journal of Remote Sensing
Volume 25 Issue 11 Pages 2015-2036
Keywords Remote Sensing
Abstract The disaster information system, the Early Damaged Area Estimation System (EDES), was developed to estimate damaged areas of natural disaster using the night-time imagery of the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS). The system employs two estimation methods to detect the city lights loss or reduction as possible impacted areas; one is the bi-temporal images (BTI) method and the other is the time-series images (TSI) method. Both methods are based on significance tests assuming that brightness of city lights fluctuates as normal random variables, and the BTI method is simplified by introducing the assumption that the standard deviation of city lights fluctuation is constant. The validity of the estimation method is discussed based on the result of the application to the 2001 Western India earthquake disaster. The estimation results identify the damaged areas distant from the epicentre fairly well, especially when using the TSI method. The system is designed to estimate the global urban damage and to provide geographic information through the Internet within 24 h after a severe disaster event. The information is expected to support the disaster response and relief activities of governments and non-governmental organizations.
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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 0143-1161 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number (up) GFZ @ kyba @ Serial 2031
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Author Geronimo, R.; Franklin, E.; Brainard, R.; Elvidge, C.; Santos, M.; Venegas, R.; Mora, C.
Title Mapping Fishing Activities and Suitable Fishing Grounds Using Nighttime Satellite Images and Maximum Entropy Modelling Type Journal Article
Year 2018 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 10 Issue 10 Pages 1604
Keywords Remote Sensing
Abstract Fisheries surveys over broad spatial areas are crucial in defining and delineating appropriate fisheries management areas. Yet accurate mapping and tracking of fishing activities remain largely restricted to developed countries with sufficient resources to use automated identification systems and vessel monitoring systems. For many countries, the spatial extent and boundaries of fishing grounds are not completely known. We used satellite images at night to detect fishing grounds in the Philippines for fishing gears that use powerful lights to attract coastal pelagic fishes. We used nightly boat detection data, extracted by U.S. NOAA from the Visible Infrared Imaging Radiometer Suite (VIIRS), for the Philippines from 2012 to 2016, covering 1713 nights, to examine spatio-temporal patterns of fishing activities in the country. Using density-based clustering, we identified 134 core fishing areas (CFAs) ranging in size from 6 to 23,215 km2 within the Philippines’ contiguous maritime zone. The CFAs had different seasonal patterns and range of intensities in total light output, possibly reflecting differences in multi-gear and multi-species signatures of fishing activities in each fishing ground. Using maximum entropy modeling, we identified bathymetry and chlorophyll as the main environmental predictors of spatial occurrence of these CFAs when analyzed together, highlighting the multi-gear nature of the CFAs. Applications of the model to specific CFAs identified different environmental drivers of fishing distribution, coinciding with known oceanographic associations for a CFA’s dominant target species. This case study highlights nighttime satellite images as a useful source of spatial fishing effort information for fisheries, especially in Southeast Asia.
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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 (up) GFZ @ kyba @ Serial 2033
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Author Li, K.; Chen, Y.; Li, Y.
Title The Random Forest-Based Method of Fine-Resolution Population Spatialization by Using the International Space Station Nighttime Photography and Social Sensing Data Type Journal Article
Year 2018 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 10 Issue 10 Pages 1650
Keywords Remote Sensing
Abstract Despite the importance of high-resolution population distribution in urban planning, disaster prevention and response, region economic development, and improvement of urban habitant environment, traditional urban investigations mainly focused on large-scale population spatialization by using coarse-resolution nighttime light (NTL) while few efforts were made to fine-resolution population mapping. To address problems of generating small-scale population distribution, this paper proposed a method based on the Random Forest Regression model to spatialize a 25 m population from the International Space Station (ISS) photography and urban function zones generated from social sensing data—point-of-interest (POI). There were three main steps, namely HSL (hue saturation lightness) transformation and saturation calibration of ISS, generating functional-zone maps based on point-of-interest, and spatializing population based on the Random Forest model. After accuracy assessments by comparing with WorldPop, the proposed method was validated as a qualified method to generate fine-resolution population spatial maps. In the discussion, this paper suggested that without help of auxiliary data, NTL cannot be directly employed as a population indicator at small scale. The Variable Importance Measure of the RF model confirmed the correlation between features and population and further demonstrated that urban functions performed better than LULC (Land Use and Land Cover) in small-scale population mapping. Urban height was also shown to improve the performance of population disaggregation due to its compensation of building volume. To sum up, this proposed method showed great potential to disaggregate fine-resolution population and other urban socio-economic attributes.
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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 (up) GFZ @ kyba @ Serial 2038
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Author Cao, C.; Shao, X.; Uprety, S.
Title Detecting Light Outages After Severe Storms Using the S-NPP/VIIRS Day/Night Band Radiances Type Journal Article
Year 2013 Publication IEEE Geoscience and Remote Sensing Letters Abbreviated Journal IEEE Geosci. Remote Sensing Lett.
Volume 10 Issue 6 Pages 1582-1586
Keywords Remote Sensing
Abstract Power outages after a major storm affect the lives of millions of people and cause massive light outages. The launch of the Suomi National Polar-orbiting Partnership satellite with the Visible Infrared Imaging Radiometer Suite (VIIRS) significantly enhances our capability to monitor and detect light outages with the well-calibrated day/night band (DNB) and to use light loss signatures as indication of regional power outages. This study explores the use of the DNB in quantifying light outages due to the derecho storm in the Washington DC metropolitan area in June 2012 and Hurricane Sandy at the end of October 2012 on the East Coast of U.S. The results show that the DNB data are very useful in detecting power outages by quantifying light loss, but it also has some challenges due to clouds, lunar illumination, and straylight effect. Comparison of light outage and recovery trend determined from DNB data with power company survey shows reasonable agreement, demonstrating the usefulness of DNB in independently verifying and complementing the statistics from power companies.
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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 1545-598X ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number (up) GFZ @ kyba @ Serial 2040
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