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  1. Article ; Online: Implications for Tracking SDG Indicator Metrics with Gridded Population Data

    Cascade Tuholske / Andrea E. Gaughan / Alessandro Sorichetta / Alex de Sherbinin / Agathe Bucherie / Carolynne Hultquist / Forrest Stevens / Andrew Kruczkiewicz / Charles Huyck / Greg Yetman

    Sustainability, Vol 13, Iss 7329, p

    2021  Volume 7329

    Abstract: Achieving the seventeen United Nations Sustainable Development Goals (SDGs) requires accurate, consistent, and accessible population data. Yet many low- and middle-income countries lack reliable or recent census data at the sufficiently fine spatial ... ...

    Abstract Achieving the seventeen United Nations Sustainable Development Goals (SDGs) requires accurate, consistent, and accessible population data. Yet many low- and middle-income countries lack reliable or recent census data at the sufficiently fine spatial scales needed to monitor SDG progress. While the increasing abundance of Earth observation-derived gridded population products provides analysis-ready population estimates, end users lack clear use criteria to track SDGs indicators. In fact, recent comparisons of gridded population products identify wide variation across gridded population products. Here we present three case studies to illuminate how gridded population datasets compare in measuring and monitoring SDGs to advance the “fitness for use” guidance. Our focus is on SDG 11.5, which aims to reduce the number of people impacted by disasters. We use five gridded population datasets to measure and map hazard exposure for three case studies: the 2015 earthquake in Nepal; Cyclone Idai in Mozambique, Malawi, and Zimbabwe (MMZ) in 2019; and flash flood susceptibility in Ecuador. First, we map and quantify geographic patterns of agreement/disagreement across gridded population products for Nepal, MMZ, and Ecuador, including delineating urban and rural populations estimates. Second, we quantify the populations exposed to each hazard. Across hazards and geographic contexts, there were marked differences in population estimates across the gridded population datasets. As such, it is key that researchers, practitioners, and end users utilize multiple gridded population datasets—an ensemble approach—to capture uncertainty and/or provide range estimates when using gridded population products to track SDG indicators. To this end, we made available code and globally comprehensive datasets that allows for the intercomparison of gridded population products.
    Keywords Sustainable Development Goals ; hazards ; Earth observations ; remote sensing ; demography ; urbanization ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Subject code 333
    Language English
    Publishing date 2021-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Isotropic and anisotropic kriging approaches for interpolating surface-level wind speeds across large, geographically diverse regions

    Carol J. Friedland / T. Andrew Joyner / Carol Massarra / Robert V. Rohli / Anna M. Treviño / Shubharoop Ghosh / Charles Huyck / Mark Weatherhead

    Geomatics, Natural Hazards & Risk, Vol 8, Iss 2, Pp 207-

    2017  Volume 224

    Abstract: Windstorms result in significant damage and economic loss and are a major recurring threat in many countries. Estimating surface-level wind speeds resulting from windstorms is a complicated problem, but geostatistical spatial interpolation methods ... ...

    Abstract Windstorms result in significant damage and economic loss and are a major recurring threat in many countries. Estimating surface-level wind speeds resulting from windstorms is a complicated problem, but geostatistical spatial interpolation methods present a potential solution. Maximum sustained and peak gust weather station data from two historic windstorms in Europe were analyzed to predict surface-level wind speed surfaces across a large and topographically varied landscape. Disjunctively sampled maximum sustained wind speeds were adjusted to represent equivalent continuously sampled 10-minute wind speeds and missing peak gust station data were estimated by applying a gust factor to the recorded maximum sustained wind speeds. Wind surfaces were estimated based on anisotropic and isotropic kriging interpolation methodologies. The study found that anisotropic kriging is well-suited for interpolating wind speeds in meso- and macro-scale areas because it accounts for wind direction and trends in wind speeds across a large, heterogeneous surface, and resulted in interpolation surface improvement in most models evaluated. Statistical testing of interpolation error for stations stratified by geographic classification revealed that stations in coastal and/or mountainous locations had significantly higher prediction errors when compared with stations in non-coastal/non-mountainous locations. These results may assist in mitigating losses to structures due to excessive wind events.
    Keywords windstorm ; sustained winds ; peak gust ; anisotropy ; kriging interpolation ; Environmental technology. Sanitary engineering ; TD1-1066 ; Environmental sciences ; GE1-350 ; Risk in industry. Risk management ; HD61
    Language English
    Publishing date 2017-12-01T00:00:00Z
    Publisher Taylor & Francis Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Crowdsourcing earthquake damage assessment using remote sensing imagery

    Stuart Gill / Jay Berger / Shay Har-Noy / Marjorie Greene / Shubharoop Ghosh / Luke Barrington / Albert Yu-Min Lin / Charles Huyck

    Annals of Geophysics, Vol 54, Iss

    2011  Volume 6

    Abstract: This paper describes the evolution of recent work on using crowdsourced analysis of remote sensing imagery, particularly high-resolution aerial imagery, to provide rapid, reliable assessments of damage caused by earthquakes and potentially other ... ...

    Abstract This paper describes the evolution of recent work on using crowdsourced analysis of remote sensing imagery, particularly high-resolution aerial imagery, to provide rapid, reliable assessments of damage caused by earthquakes and potentially other disasters. The initial effort examined online imagery taken after the 2008 Wenchuan, China, earthquake. A more recent response to the 2010 Haiti earthquake led to the formation of an international consortium: the Global Earth Observation Catastrophe Assessment Network (GEO-CAN). The success of GEO-CAN in contributing to the official damage assessments made by the Government of Haiti, the United Nations, and the World Bank led to further development of a web-based interface. A current initiative in Christchurch, New Zealand, is underway where remote sensing experts are analyzing satellite imagery, geotechnical engineers are marking liquefaction areas, and structural engineers are identifying building damage. The current site includes online training to improve the accuracy of the assessments and make it possible for even novice users to contribute to the crowdsourced solution. The paper discusses lessons learned from these initiatives and presents a way forward for using crowdsourced remote sensing as a tool for rapid assessment of damage caused by natural disasters around the world.
    Keywords Surveys ; measurements and monitoring ; Instruments and techniques ; Seismic risk ; Seismology ; Data dissemination generation or miscellaneous. ; Geophysics. Cosmic physics ; QC801-809 ; Physics ; QC1-999 ; Science ; Q ; DOAJ:Geophysics and Geomagnetism ; DOAJ:Earth and Environmental Sciences
    Subject code 710
    Language English
    Publishing date 2011-06-01T00:00:00Z
    Publisher Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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