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Author Richter, A.; Ng, K.T.W.; Karimi, N.
Title A data driven technique applying GIS, and remote sensing to rank locations for waste disposal site expansion Type Journal Article
Year 2019 Publication Resources, Conservation and Recycling Abbreviated Journal (down) Resources, Conservation and Recycling
Volume 149 Issue Pages 352-362
Keywords Remote Sensing
Abstract Landfilling is the most common method for final treatment of municipal solid waste worldwide. Canadians generated 973 kg/cap of waste in 2016, and 73% of that was sent to landfills or incinerators. This study proposes a novel method which combines remote sensing and vector data to rank the suitability of current landfill sites and their area of influence for expansion in Saskatchewan, Canada; where there are currently more than 500 active landfills. This study found that using average normalized data, 55.3% of the land in the study area was suitable or moderately suitable for landfill expansion while 45% of the area was unsuitable for landfill expansion. Polygon 32, an area dominated by agriculture and pasture land, is the most suitable for landfill expansion based on the mean normalized rank and was ranked 9th (out of 39) in terms of standard deviation. Polygon 27 is the least suitable for landfill expansion, having the largest mean normalized rank, and was ranked 38th (out of 39) in terms of standard deviation. This method is advantageous compared to other decision-making tools which rely on expert opinion. This method relies solely on remote sensing and vector data; but is flexible enough that weighting of data sets can be applied by policy makers if so desired. Results show that using remote sensing data and vector data together are capable of capturing distinctly different aspects of the study area, and that vector data can be used as a proxy for imagery where cloud cover is present.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0921-3449 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2582
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Author Zhang, W.; Jiang, L.; Cui, Y.; Xu, Y.; Wang, C.; Yu, J.; Streets, D.G.; Lin, B.
Title Effects of urbanization on airport CO2 emissions: A geographically weighted approach using nighttime light data in China Type Journal Article
Year 2019 Publication Resources, Conservation and Recycling Abbreviated Journal (down) Resources, Conservation and Recycling
Volume 150 Issue Pages 104454
Keywords Remote Sensing
Abstract Regional disparities in carbon dioxide (CO2) emissions from airports at the city level are of increasing importance for low-carbon development of the civil aviation sector. However, CO2 emissions from airport operations have rarely been estimated and discussed. We investigate the main driving forces of airport CO2 emissions by using Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) models, separately, to investigate whether urbanization drives airport CO2 emissions and to investigate spatial heterogeneity at the city level. Nighttime light (NTL) data from satellite observations are adopted as a proxy for urbanization. We obtained energy consumption data by end-use purpose for 70 airports in China and calculated the CO2 emissions from on-ground airport operations. The median CO2 emissions of the 70 sample airports are estimated to be 15.9 million tonnes for 2015. Results from the GWR model indicate that airport CO2 emissions are affected by five main factors: urbanization, foreign direct investment, the share of tertiary industry in gross domestic output, passenger turnover of civil aviation and passenger turnover of railways. The elasticity of urbanization shows an increasing trend from the east of China to the west. The spatial heterogeneity of the CO2 emissions of the five airport clusters that are located in five urban agglomerations is discussed. In order to achieve effective reductions of CO2 emissions from airports, policy-makers should consider the spatial heterogeneity of the major driving factors of carbon emissions in different regions to avoid carbon lock-in.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0921-3449 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2657
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Author Waddill, D.G.; Chaney, C.H.; Dutt, R.H.
Title Ovulation Rate In Gilts After Short-Time Exposure To Continuous Light Type Journal Article
Year 1968 Publication Reproduction Abbreviated Journal (down) Reproduction
Volume 15 Issue 1 Pages 123-125
Keywords Animals
Abstract Ovulation rate in gilts maintained under continuous light (daylight plus 118 to 130 lux of artificial light at night) for a complete oestrous cycle during the spring months was not significantly different from that in gilts maintained under normal daylight. Average ovulation rates were 13·4 for controls and 13·1 for treated gilts. A significant (P<0·01) difference in ovulation rate was found between years.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1470-1626 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2468
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Author Bennett, M.M.; Smith, L.C.
Title Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics Type Journal Article
Year 2017 Publication Remote Sensing of Environment Abbreviated Journal (down) Remote Sensing of Environment
Volume 192 Issue Pages 176-197
Keywords Remote Sensing
Abstract Since the late 1990s, remotely sensed night-time lights (NTL) satellite imagery has been shown to correlate with socioeconomic parameters including urbanization, economic activity, and population. More recent research demonstrates that multitemporal NTL data can serve as a reliable proxy for change over time in these variables whether they are increasing or decreasing. Time series analysis of NTL data is especially valuable for detecting, estimating, and monitoring socioeconomic dynamics in countries and subnational regions where reliable official statistics may be lacking. Until 2012, multitemporal NTL imagery came primarily from the Defense Meteorological Satellite Program – Operational Linescan System (DMSP-OLS), for which digital imagery is available from 1992 to 2013. In October 2011, the launch of NASA/NOAA's Suomi National Polar-orbiting Partnership satellite, whose Visible Infrared Imaging Radiometer Suite (VIIRS) sensor has a Day/Night Band (DNB) specifically designed for capturing radiance from the Earth at night, marked the start of a new era in NTL data collection and applications. In light of these advances, this paper reviews progress in using multitemporal DMSP-OLS and VIIRS imagery to analyze urbanization, economic, and population dynamics across a range of geographic scales. An overview of data corrections and processing for comparison of multitemporal NTL imagery is provided, followed by a meta-analysis and integrative synthesis of these studies. Figures are included that visualize the capabilities of DMSP-OLS and VIIRS to capture socioeconomic change in the post-Soviet Russian Far East and war-torn Syria, respectively. Finally, future directions for NTL research are suggested, particularly in the areas of determining the fundamental causes of observed light and in leveraging VIIRS' superior sensitivity and spatial and radiometric resolution.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0034-4257 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2024
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Author Cao, X.; Chen, J.; Imura, H.; Higashi, O.
Title A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data Type Journal Article
Year 2009 Publication Remote Sensing of Environment Abbreviated Journal (down) Remote Sensing of Environment
Volume 113 Issue 10 Pages 2205-2209
Keywords Remote Sensing
Abstract Mapping urban areas at regional and global scales has become an urgent task because of the increasing pressures from rapid urbanization and associated environmental problems. Satellite imaging of stable anthropogenic lights from DMSP-OLS provides an accurate, economical, and straightforward way to map the global distribution of urban areas. To address problems in the thresholding methods that use empirical strategies or manual trial-and-error procedures, we proposed a support vector machine (SVM)-based region-growing algorithm to semi-automatically extract urban areas from DMSP-OLS and SPOT NDVI data. Several simple criteria were used to select SVM training sets of urban and non-urban pixels, and an iterative classification and training procedure was adopted to identify the urban pixels through region growing. The new method was validated using the extents of 25 Chinese cities, as classified by Landsat ETM+ images, and then compared with two common thresholding methods. The results showed that the SVM-based algorithm could not only achieve comparable results to the local-optimized threshold method, but also avoid its tedious trial-and-error procedure, suggesting that the new method is an easy and simple alternative for extracting urban extent from DMSP-OLS and SPOT NDVI data.
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 0034-4257 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2041
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