43 research outputs found

    Research theme reports from April 1, 2019 - March 31, 2020

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    New sources, opportunities and challenges

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    Images of the Earth at night are an exceptional source of human geographical data, because artificial light highlights human activity in a way that daytime scenes do not. The quality of such imagery dramatically improved in 2012 with two new spaceborne detectors. The higher resolution and precision of the data considerably expands the scope of possible applications. In this paper, we introduce the two new data sources and discuss their potential limitations using three case studies. Data from the Visible Infrared Imaging Radiometer Suite Day-Night Band (VIIRS DNB) is shown to have sufficient resolution to identify major sources of waste light, such as airports, and we find considerable variation in the peak radiance of the world’s largest airports. Nighttime imagery brings “cultural footprints” to light: DNB data reveals that American cities emit many times more light per capita than German cities and that cities in the former East of Germany emit more light per capita than those in the former West. Photographs from the International Space Station, the second new source of imagery, provide some limited spectral information, as well as street-level resolution. These images may be of greater use for epidemiological studies than the lower resolution DNB data

    CIRA annual report FY 2016/2017

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    Reporting period April 1, 2016-March 31, 2017

    CIRA annual report FY 2015/2016

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    Reporting period April 1, 2015-March 31, 2016

    CIRA annual report FY 2017/2018

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    Reporting period April 1, 2017-March 31, 2018

    CIRA annual report FY 2014/2015

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    Reporting period July 1, 2014-March 31, 2015

    CIRA annual report FY 2013/2014

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    Remote sensing of night lights: a review and an outlook for the future

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordRemote sensing of night light emissions in the visible band offers a unique opportunity to directly observe human activity from space. This has allowed a host of applications including mapping urban areas, estimating population and GDP, monitoring disasters and conflicts. More recently, remotely sensed night lights data have found use in understanding the environmental impacts of light emissions (light pollution), including their impacts on human health. In this review, we outline the historical development of night-time optical sensors up to the current state of the art sensors, highlight various applications of night light data, discuss the special challenges associated with remote sensing of night lights with a focus on the limitations of current sensors, and provide an outlook for the future of remote sensing of night lights. While the paper mainly focuses on space borne remote sensing, ground based sensing of night-time brightness for studies on astronomical and ecological light pollution, as well as for calibration and validation of space borne data, are also discussed. Although the development of night light sensors lags behind day-time sensors, we demonstrate that the field is in a stage of rapid development. The worldwide transition to LED lights poses a particular challenge for remote sensing of night lights, and strongly highlights the need for a new generation of space borne night lights instruments. This work shows that future sensors are needed to monitor temporal changes during the night (for example from a geostationary platform or constellation of satellites), and to better understand the angular patterns of light emission (roughly analogous to the BRDF in daylight sensing). Perhaps most importantly, we make the case that higher spatial resolution and multispectral sensors covering the range from blue to NIR are needed to more effectively identify lighting technologies, map urban functions, and monitor energy use.European Union Horizon 2020Helmholtz AssociationNatural Environment Research Council (NERC)Chinese Academy of ScienceLeibniz AssociationIGB Leibniz Institut

    Cloud Detection And Trace Gas Retrieval From The Next Generation Satellite Remote Sensing Instruments

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    Thesis (Ph.D.) University of Alaska Fairbanks, 2005The objective of this thesis is to develop a cloud detection algorithm suitable for the National Polar Orbiting Environmental Satellite System (NPOESS) Visible Infrared Imaging Radiometer Suite (VIIRS) and methods for atmospheric trace gas retrieval for future satellite remote sensing instruments. The development of this VIIRS cloud mask required a flowdown process of different sensor models in which a variety of sensor effects were simulated and evaluated. This included cloud simulations and cloud test development to investigate possible sensor effects, and a comprehensive flowdown analysis of the algorithm was conducted. In addition, a technique for total column water vapor retrieval using shadows was developed with the goal of enhancing water vapor retrievals under hazy atmospheric conditions. This is a new technique that relies on radiance differences between clear and shadowed surfaces, combined with ratios between water vapor absorbing and window regions. A novel method for retrieving methane amounts over water bodies, including lakes, rivers, and oceans, under conditions of sun glint has also been developed. The theoretical basis for the water vapor as well as the methane retrieval techniques is derived and simulated using a radiative transfer model

    Nighttime Lights as a Proxy for Economic Performance of Regions

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    Studying and managing regional economic development in the current globalization era demands prompt, reliable, and comparable estimates for a region’s economic performance. Night-time lights (NTL) emitted from residential areas, entertainment places, industrial facilities, etc., and captured by satellites have become an increasingly recognized proxy for on-ground human activities. Compared to traditional indicators supplied by statistical offices, NTLs may have several advantages. First, NTL data are available all over the world, providing researchers and official bodies with the opportunity to obtain estimates even for regions with extremely poor reporting practices. Second, in contrast to non-standardized traditional reporting procedures, the unified NTL data remove the problem of inter-regional comparability. Finally, NTL data are currently globally available on a daily basis, which makes it possible to obtain these estimates promptly. In this book, we provide the reader with the contributions demonstrating the potential and efficiency of using NTL data as a proxy for the performance of regions
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