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Author Zangeneh, P.; Hamledari, H.; McCabe, B.
Title Quantifying Remoteness for Risk and Resilience Assessment Using Nighttime Satellite Imagery Type Journal Article
Year 2020 Publication Journal of Computing in Civil Engineering Abbreviated Journal J. Comput. Civ. Eng.
Volume 34 Issue 5 Pages 04020026
Keywords Remote Sensing
Abstract Remoteness has a crucial role in risk assessments of megaprojects, resilience assessments of communities and infrastructure, and a wide range of public policymaking. The existing measures of remoteness require an extensive amount of population census and of road and infrastructure network data, and often are limited to narrow scopes. This paper presents a methodology to quantify remoteness using nighttime satellite imagery. The light clusters of nighttime satellite imagery are direct yet unintended consequences of human settled populations and urbanization; therefore, the absence of illuminated clusters is considered as evidence of remoteness. The proposed nighttime remoteness index (NIRI) conceptualizes the remoteness based on the distribution of nighttime lights within radii of up to 1,000 km. A predictive model was created using machine learning techniques such as multivariate adaptive regression splines and support vector machines regressions to establish a reliable and accurate link between nighttime lights and the Accessibility/Remoteness Index of Australia (ARIA). The model was used to establish NIRI for the United States and Canada, and in different years. The index was compared with the Canadian remoteness indexes published by Statistics Canada.
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 0887-3801 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial (down) 2937
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Author Chen, M.; Zhang, S.
Title Measuring the regional non-observed economy in China with nighttime lights Type Journal Article
Year 2020 Publication International Journal of Emerging Markets Abbreviated Journal Ijoem
Volume in press Issue Pages
Keywords Remote Sensing
Abstract Purpose

The non-observed economy (NOE) is a pervasive phenomenon worldwide, especially in developing countries, but the size of the NOE and its contributions to the overall economy are usually unknown. This paper presents an estimation of the average size of the NOE for the 31 provincial regions in China between 1992 and 2013.

Design/methodology/approach

This study uses the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data combined with 11 existing surveys on or measurements of NOE for 191 countries or regions throughout the world, to measure the size of the NOE.

Findings

The results show that the NOE share is unevenly distributed among China's provincial regions, with the smallest being 3.19% for Beijing and the largest being 69.71% for Ningxia. The national average is 43.11%, while the figures for the eastern region, middle region, northeastern region and western region are 39.3%, 47.6%, 44.7% and 43.6%, respectively. The NOE estimates are negatively correlated with the measured gross domestic product (GDP) and GDP per capita, which suggests that developed regions tend to have less NOE.

Originality/value

The nighttime lights are used to measure the NOE for China's provincial regions. Compared with traditional databases, one of the prominent features of nighttime lights is its objectivity, as there is little human interference; therefore, it can be used to achieve more accurate results.
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 1746-8809 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial (down) 2936
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Author Lu, W.; Liu, Y.; Wang, J.; Xu, W.; Wu, W.; Liu, Y.; Zhao, B.; Li, H.; Li, P.
Title Global proliferation of offshore gas flaring areas Type Journal Article
Year 2020 Publication Journal of Maps Abbreviated Journal Journal of Maps
Volume 16 Issue 2 Pages 396-404
Keywords Remote Sensing
Abstract The long-term venting and combustion of offshore associated gas have substantial adverse effects on the ecological environment, so characterizing the global proliferation of offshore gas flaring areas is very important for marine environmental protection and climate change research. However, the use of a single fire/light remote sensing product makes it difficult to conduct long-term observations. In this study, we detected global offshore gas flaring areas during the 27-year interval from 1992 to 2018, using temporal and spatial complementarity of six different remote sensing data products, which are as follows: DMSP-OLS Nighttime Lights; (A)ATSRs; MODIS and VIIRS activefire products; and VIIRS Night Fire and NighttimeLight. Our aim was to achieve more comprehensive extraction results and to analyze a longer time-interval than has been attempted previously. In addition, the resulting map ofthe global proliferation of offshore gas flaring areas enables their locational and temporal characteristics to be visualized.
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 1744-5647 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial (down) 2930
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Author Chen, J.; Zhao, F.; Zeng, N.; Oda, T.
Title Comparing a global high-resolution downscaled fossil fuel CO2 emission dataset to local inventory-based estimates over 14 global cities Type Journal Article
Year 2020 Publication Carbon Balance and Management Abbreviated Journal Carbon Balance Manag
Volume 15 Issue 1 Pages 9
Keywords Remote Sensing; City CO2 emissions; Emission inventory; Fossil fuel CO2 emissions; In-boundary; Odiac
Abstract BACKGROUND: Compilation of emission inventories (EIs) for cities is a whole new challenge to assess the subnational climate mitigation effort under the Paris Climate Agreement. Some cities have started compiling EIs, often following a global community protocol. However, EIs are often difficult to systematically examine because of the ways they were compiled (data collection and emission calculation) and reported (sector definition and direct vs consumption). In addition, such EI estimates are not readily applicable to objective evaluation using modeling and observations due to the lack of spatial emission extents. City emission estimates used in the science community are often based on downscaled gridded EIs, while the accuracy of the downscaled emissions at city level is not fully assessed. RESULTS: This study attempts to assess the utility of the downscaled emissions at city level. We collected EIs from 14 major global cities and compare them to the estimates from a global high-resolution fossil fuel CO2 emission data product (ODIAC) commonly used in the science research community. We made necessary adjustments to the estimates to make our comparison as reasonable as possible. We found that the two methods produce very close area-wide emission estimates for Shanghai and Delhi (< 10% difference), and reach good consistency in half of the cities examined (< 30% difference). The ODIAC dataset exhibits a much higher emission compared to inventory estimates in Cape Town (+ 148%), Sao Paulo (+ 43%) and Beijing (+ 40%), possibly related to poor correlation between nightlight intensity with human activity, such as the high-emission and low-lighting industrial parks in developing countries. On the other hand, ODIAC shows lower estimates in Manhattan (- 62%), New York City (- 45%), Washington D.C. (- 42%) and Toronto (- 33%), all located in North America, which may be attributable to an underestimation of residential emissions from heating in ODIAC's nightlight-based approach, and an overestimation of emission from ground transportation in registered vehicles statistics of inventory estimates. CONCLUSIONS: The relatively good agreement suggests that the ODIAC data product could potentially be used as a first source for prior estimate of city-level CO2 emission, which is valuable for atmosphere CO2 inversion modeling and comparing with satellite CO2 observations. Our compilation of in-boundary emission estimates for 14 cities contributes towards establishing an accurate inventory in-boundary global city carbon emission dataset, necessary for accountable local climate mitigation policies in the future.
Address Goddard Earth Sciences Research and Technology, Universities Space Research Association, Columbia, MD, USA
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1750-0680 ISBN Medium
Area Expedition Conference
Notes PMID:32430547 Approved no
Call Number GFZ @ kyba @ Serial (down) 2929
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Author Yao, J.Q.; Zhai, H.R.; Tang, X.M.; Gao, X.M.; Yang, X.D.
Title Amazon Fire Monitoring and Analysis Based on Multi-source Remote Sensing Data Type Journal Article
Year 2020 Publication IOP Conference Series: Earth and Environmental Science Abbreviated Journal IOP Conf. Ser.: Earth Environ. Sci.
Volume 474 Issue Pages 042025
Keywords Remote Sensing
Abstract In August 2019, a large-scale fire broke out in the Amazon rainforest, bringing serious harm to the ecosystem and human beings. In order to accurately monitor the dynamic change of forest fire in Amazon rainforest and analyse the impact of fire spreading and extinction on the environment, firstly, based on NPP VIIRS data covering the Amazon fire area, the sliding window threshold method is adopted to extract the fire point, and the cause of fire change is monitored and analysed according to the time series. Secondly, based on the time series of CALIPSO data, the vertical distribution changes of atmospheric pollutants in the amazon fire area are analysed, and the comprehensive analysis is carried out by combining NPP VIIRS data. The experimental results show that only NPP VIIRS data is used to predict the fire, and the combination of CALIPSO data can better monitor the forest fire and predict the fire development trend. The combination of optical image and laser radar has greater advantages in dynamic fire monitoring and fire impact analysis. The method described in this paper can provide basic data reference for real-time and accurate prediction of forest fires and provide new ideas for dynamic fire monitoring.
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 1755-1315 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial (down) 2927
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