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Author (up) Chen, H.; Zhang, X.; Wu, R.; Cai, T.
Title Revisiting the environmental Kuznets curve for city-level CO2 emissions: based on corrected NPP-VIIRS nighttime light data in China Type Journal Article
Year 2020 Publication Journal of Cleaner Production Abbreviated Journal Journal of Cleaner Production
Volume Issue Pages 121575
Keywords Remore Sensing; China; carbon emissions; CO2 emissions; night lights; NPP-VIIRS; VIIRS-DNB; VIIRS-DNB; Kuznets curve
Abstract With the increasing trend of global warming, the Chinese government faces tremendous pressure to reduce CO2 emissions. The purpose of this study is to accurately measure CO2 emissions at the city scale in China and examine the environmental Kuznets curve, thereby providing a reference for decision-making. Corrected NPP-VIIRS nighttime light data were used to accurately estimate carbon dioxide emissions at the provincial and city scales in China. Then, based on the STRIPAT model, 291 cities in China were used to verify the environmental Kuznets curve. Our results show that on the provincial scale, the R2 between the estimated value and the statistical value of carbon dioxide reaches 0.85. Western cities in China emit more CO2, as do economically developed cities and industry- and mining-dominated cities. There are two CO2 emission hot spots in the north and one cold spot in the south. It was found that the environmental Kuznets curve on the city scale exists. This study has practical value in utilizing NPP-VIIRS data for the estimation of city CO2 emissions. The results also have academic value for determining factors that contribute to carbon dioxide emissions and can provide a reference for relevant decision makers. This study could be considered the first to simulate CO2 emissions at the provincial and city levels in China based on a NPP-VIIRS nighttime light model to explore the associated geographical distribution characteristics and potential influencing factors.
Address State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0959-6526 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ john @ Serial 2917
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Author (up) Chen, J., & Li, L.
Title Regional Economic Activity Derived From MODIS Data: A Comparison With DMSP/OLS and NPP/VIIRS Nighttime Light Data Type Journal Article
Year 2019 Publication IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Abbreviated Journal
Volume Issue Pages 1-11
Keywords Remote Sensing; Economics
Abstract Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) and Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light data are the two most commonly used indicators of gross domestic product (GDP) estimation. Few studies explore the potential of daytime satellite data for estimating GDP. This study demonstrates a linear support vector machine (Linear-SVM) model to estimate GDP over Hubei province and Guangdong province, China, in 2013 from Moderate Resolution Imaging Spectroradiometer (MODIS) data. Also, a comparison of MODIS data with DMSP/OLS and NPP/VIIRS nighttime light data was conducted. Results show that the Linear-SVM model (Hubei: R2 = 0.66, 0.71, 0.92; Guangdong: R2 = 0.37, 0.32, 0.67) has better model performance than simple linear regression (R2 = 0.54, 0.59, 0.86; R2 = 0.23, 0.23, 0.63) based on DMSP/OLS nighttime lights, DMSP/OLS corrected nighttime lights, and NPP/VIIRS nighttime lights, respectively, while MODIS data has model performance of R2 = 0.77 (Hubei) and R2 = 0.55 (Guangdong) based on the Linear-SVM model, further indicating that MODIS data improves the accuracy of GDP estimation compared to DMSP/OLS nighttime lights. In addition, MODIS data produced finer GDP estimation than DMSP/OLS nighttime lights, especially in dark and light saturated areas. Although MODIS data is not as accurate as the NPP/VIIRS nighttime lights for estimating GDP, the proposed method could be applicable to other daytime satellite data and has broad prospects for improving the spatial and temporal resolution of regional economic activity and improving estimation accuracy.
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 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ intern @ Serial 2630
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Author (up) Chen, J.; Fan, W.; Li, K.; Liu, X.; Song, M.
Title Fitting Chinese cities’ population distributions using remote sensing satellite data Type Journal Article
Year 2019 Publication Ecological Indicators Abbreviated Journal Ecological Indicators
Volume 98 Issue Pages 327-333
Keywords Remote Sensing
Abstract Remote sensing satellite data from 2012 to 2013 are used to fit the Chinese cities’ population distributions over the same period in order to verify the population distribution in China from a relatively objective perspective. Most scholars have used nighttime light data and vegetation indexes to fit the population distribution, but the fitting effect has not been satisfactory. In this paper, processed Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light data, net primary productivity of vegetation (NPP), and average slope data were used to fit the population distribution from the three dimensions of economic growth, ecological environment, and topographic factors, respectively. The fitting effect was significantly improved compared with other studies (R2 values of 0.9244 and 0.9253 in 2012 and 2013, respectively). Therefore, this method provides a practical and effective way to fit the population distribution for remote cities or areas lacking census data. Furthermore, there is important practical significance for the government to formulate its population policies rationally, optimize the spatial distribution of population, and improve the ecological quality of the city.
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 1470160X ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2071
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Author (up) 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 2929
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Author (up) 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 2936
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