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Author Ren, Z.; Liu, Y.; Chen, B.; Xu, B.
Title Where Does Nighttime Light Come From? Insights from Source Detection and Error Attribution Type Journal Article
Year (down) 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 12 Pages 1922
Keywords Remote Sensing
Abstract Nighttime light remote sensing has aroused great popularity because of its advantage in estimating socioeconomic indicators and quantifying human activities in response to the changing world. Despite many advances that have been made in method development and implementation of nighttime light remote sensing over the past decades, limited studies have dived into answering the question: Where does nighttime light come from? This hinders our capability of identifying specific sources of nighttime light in urbanized regions. Addressing this shortcoming, here we proposed a parcel-oriented temporal linear unmixing method (POTLUM) to identify specific nighttime light sources with the integration of land use data. Ratio of root mean square error was used as the measure to assess the unmixing accuracy, and parcel purity index and source sufficiency index were proposed to attribute unmixing errors. Using the Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light dataset from the Suomi National Polar-Orbiting Partnership (NPP) satellite and the newly released Essential Urban Land Use Categories in China (EULUC-China) product, we applied the proposed method and conducted experiments in two China cities with different sizes, Shanghai and Quzhou. Results of the POTLUM showed its relatively robust applicability of detecting specific nighttime light sources, achieving an rRMSE of 3.38% and 1.04% in Shanghai and Quzhou, respectively. The major unmixing errors resulted from using impure land parcels as endmembers (i.e., parcel purity index for Shanghai and Quzhou: 54.48%, 64.09%, respectively), but it also showed that predefined light sources are sufficient (i.e., source sufficiency index for Shanghai and Quzhou: 96.53%, 99.55%, respectively). The method presented in this study makes it possible to identify specific sources of nighttime light and is expected to enrich the estimation of structural socioeconomic indicators, as well as better support various applications in urban planning and management.
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Corporate Author Thesis
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 3032
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Author Xia, C.; Yeh, A.G.-O.; Zhang, A.
Title Analyzing spatial relationships between urban land use intensity and urban vitality at street block level: A case study of five Chinese megacities Type Journal Article
Year (down) 2020 Publication Landscape and Urban Planning Abbreviated Journal Landscape and Urban Planning
Volume 193 Issue Pages 103669
Keywords Remote Sensing
Abstract Urban sprawl in urbanizing China has resulted in a series of ecological and environmental problems. Urban planners have been committed to promoting compact development through high-density and mixed land use. However, a problem brought by such compact urban form is the mismatch between physical spaces and socio-economic activities. To date, minimal research has been conducted using spatial statistics to study this issue at the local scales. Moreover, urban night-time vitality has been consistently ignored in existing studies. In the current work, urban land use intensity was analyzed on the basis of street block density and typology, and urban daytime and night-time vitality were measured using small catering business and night-time light data, respectively. The spatial relationships between urban land use intensity and urban vitality were investigated using a local indicator of spatial association (LISA), and five megacities in China were taken as a case study to examine whether variations exist between different cities. Results showed a significant positive spatial autocorrelation between urban land use intensity and urban vitality according to global statistics. Therefore, socio-economic activities are more likely to be abundant in densely developed urban areas. However, local spatial mismatches were found in the five megacities, indicating overcrowded or underutilized urban spaces in all the cities. These relationships were associated with different urban areas (urbanized before 1995 and during 1995–2015), land use conditions (function and mixture) and time periods (day and night). The results of this work will provide a comprehensive understanding of compact city and sustainability.
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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 0169-2046 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2697
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Author Beresford, A.E.; Donald, P.F.; Buchanan, G.M.
Title Repeatable and standardised monitoring of threats to Key Biodiversity Areas in Africa using Google Earth Engine Type Journal Article
Year (down) 2020 Publication Ecological Indicators Abbreviated Journal Ecological Indicators
Volume 109 Issue Pages 105763
Keywords Remote Sensing
Abstract Key Biodiversity Areas (KBAs) are sites that make significant contributions to the global persistence of biodiversity, but identification of sites alone is not sufficient to ensure their conservation. Monitoring is essential if pressures on these sites are to be identified, priorities set and appropriate responses developed. Here, we describe how analysis of freely available data on a cloud-processing platform (Google Earth Engine) can be used to assess changes in three example remotely sensed threat indicators (fire frequency, tree loss and night-time lights) over time on KBAs in Africa. We develop easily repeatable methods with shared code that could be applied across any geographic area and could be adapted and applied to other datasets as they become available. Fire frequency was found to have increased significantly on 12.4% of KBAs and 15.9% of ecoregions, whilst rates of forest loss increased significantly on 24.3% of KBAs and 22.6% of ecoregions. There was also evidence of significant increases in night-time lights on over half (53.3%) of KBAs and 39.6% of ecoregions between 1992 and 2013, and on 11.6% of KBAs and 53.0% of ecoregions between 2014 and 2018.
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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 1470160X ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2707
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Author Wang, C.; Chen, Z.; Yang, C.; Li, Q.; Wu, Q.; Wu, J.; Zhang, G.; Yu, B.
Title Analyzing parcel-level relationships between Luojia 1-01 nighttime light intensity and artificial surface features across Shanghai, China: A comparison with NPP-VIIRS data Type Journal Article
Year (down) 2020 Publication International Journal of Applied Earth Observation and Geoinformation Abbreviated Journal International Journal of Applied Earth Observation and Geoinformation
Volume 85 Issue Pages 101989
Keywords Remote Sensing
Abstract Nighttime light (NTL) remote sensing data have been widely used to derive socioeconomic indices at national and regional scales. However, few studies analyzed the factors that may explain NTL variations at a fine scale due to the limited resolution of existing NTL data. As a new generation NTL satellite, Luojia 1-01 provides NTL data with a finer spatial resolution of ∼130 m and can be used to assess the relationship between NTL intensity and artificial surface features on an unprecedented scale. This study represents the first efforts to assess the relationship between Luojia 1-01 NTL intensity and artificial surface features at the parcel level in comparison to the Suomi National Polar-orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data. Points-of-interest (POIs) and land-use/land-cover (LULC) data were used in random forest (RF) regression models for both Luojia 1-01 and NPP-VIIRS to analyze the feature contribution of artificial surface features to NTL intensity. The results show that luminosity variations in Luojia 1-01 data for different land-use types were more significant than those in NPP-VIIRS data because of the finer spatial resolution and wider measurement range. Seventeen variables extracted from POI and LULC data explained the Luojia 1-01 and NPP-VIIRS NTL intensity, with a good out-of-bag score of 0.62 and 0.76, respectively. Moreover, Luojia 1-01 data had fewer “blooming” phenomena than NPP-VIIRS data, especially for cropland, water body, and rural area. Luojia 1-01 is more suitable for estimating socioeconomic activities and can attain more comprehensive information on human activities, since the feature contribution of POI variables is more sensitive to NTL intensity in the Luojia 1-01 RF regression model than that in the NPP-VIIRS RF regression model.
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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 0303-2434 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2745
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Author Gong, P.; Li, X.; Wang, J.; Bai, Y.; Chen, B.; Hu, T.; Liu, X.; Xu, B.; Yang, J.; Zhang, W.; Zhou, Y.
Title Annual maps of global artificial impervious area (GAIA) between 1985 and 2018 Type Journal Article
Year (down) 2020 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment
Volume 236 Issue Pages in press
Keywords Remote Sensing
Abstract Artificial impervious areas are predominant indicators of human settlements. Timely, accurate, and frequent information on artificial impervious areas is critical to understanding the process of urbanization and land use/cover change, as well as of their impacts on the environment and biodiversity. Despite their importance, there still lack annual maps of high-resolution Global Artificial Impervious Areas (GAIA) with longer than 30-year records, due to the high demand of high performance computation and the lack of effective mapping algorithms. In this paper, we mapped annual GAIA from 1985 to 2018 using the full archive of 30-m resolution Landsat images on the Google Earth Engine platform. With ancillary datasets, including the nighttime light data and the Sentinel-1 Synthetic Aperture Radar data, we improved the performance of our previously developed algorithm in arid areas. We evaluated the GAIA data for 1985, 1990, 1995, 2000, 2005, 2010, and 2015, and the mean overall accuracy is higher than 90%. A cross-product comparison indicates the GAIA data are the only dataset spanning over 30 years. The temporal trend in GAIA agrees well with other datasets at the local, regional, and global scales. Our results indicate that the GAIA reached 797,076 km2 in 2018, which is 1.5 times more than that in 1990. China and the United States (US) rank among the top two in artificial impervious area, accounting for approximately 50% of the world's total in 2018. The artificial impervious area of China surpassed that of the US in 2015. By 2018, the remaining eight among the top ten countries are India, Russia, Brazil, France, Italy, Germany, Japan, and Canada. The GAIA dataset can be freely downloaded from http://data.ess.tsinghua.edu.cn.
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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 2756
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