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  • 2020-2022  (1)
  • 2000-2004  (4)
  • 1
    Publication Date: 2020-02-12
    Keywords: 550 - Earth sciences
    Type: info:eu-repo/semantics/article
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  • 2
    Publication Date: 2020-12-10
    Description: Remote 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.
    Type: info:eu-repo/semantics/article
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  • 3
    Publication Date: 2024-01-12
    Description: Sulawesi comprises of about 182,870 km\xc2\xb2 of land and fewer botanical specimens (about 23 specimens per 100 km\xc2\xb2, Whitten et al., 1987) have been collected here than in any other major island in Indonesia. This island is up to date botanically poorly explored and according to Van Steenis (1950) about 32,500 specimens of plants were recorded, the number is probably only a rough estimation and certainly in the precomputer era not based on real specimens. Within the framework of STORMA (Stability of Rainforest Margins) we analyzed the vegetation in several plots of one hectare of different land use systems at the Lore Lindu National Park, Central Sulawesi, Indonesia. Rapidly we were faced with the problem that the identification of the mostly sterile trees would be almost impossible without a sound basic checklist. Because previous hardcopies (Hildebrand, 1950; Soewanda & Tantra, 1973; Whitmore et al., 1989) were either outdated or incomplete (especially for the small diameter trees) we decided to create a new one using data of actual plant specimens housed at the National Herbarium of the Netherlands, Universiteit Leiden branch (with duplicate specimens in several other herbaria like BO, E, K and others), and enter them in the BRAHMS (Botanical Research and Herbarium Management Systems) database developed by Denis Filer, University of Oxford.\nMore than 120 woody families have been screened and the label information of all specimens (c. 13,000) checked and partly analysed. The density index calculated from our figures is very low (7) but for the first time underpinned by hard, retrievable data. As we did not include species \xe2\x80\x94 and specimens rich herbaceous families in our calculations (Orchidaceae, Poaceae, Zingiberaceae, ferns, etc.) the much lower collection index can be at least partially explained.
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 4
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    Rheinischen Friedrich–Wilhelms–Universität
    In:  EPIC3Bonn, Rheinischen Friedrich–Wilhelms–Universität
    Publication Date: 2019-07-17
    Repository Name: EPIC Alfred Wegener Institut
    Type: PANGAEA Documentation , notRev
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  • 5
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    IUGG Secretariat, CIRES Cooperative Institute for Research in Environmental Sciences
    Publication Date: 2020-02-12
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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