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Author Li, S.; Cheng, L.; Liu, X.; Mao, J.; Wu, J.; Li, M.
Title City type-oriented modeling electric power consumption in China using NPP-VIIRS nighttime stable light data Type Journal Article
Year 2019 Publication Energy Abbreviated Journal Energy
Volume in press Issue Pages
Keywords Energy; Remote Sensing
Abstract (up) Accelerating urbanization has created tremendous pressure on the global environment and energy supply, making accurate estimates of energy use of great importance. Most current models for estimating electric power consumption (EPC) from nighttime light (NTL) imagery are oversimplified, ignoring influential social and economic factors. Here we propose first classifying cities by economic focus and then separately estimating each category’s EPC using NTL data. We tested this approach using statistical employment data for 198 Chinese cities, 2015 NTL data from the Visible Infrared Imaging Radiometer Suite (VIIRS), and annual electricity consumption statistics. We used cluster analysis of employment by sector to divide the cities into three types (industrial, service, and technology and education), then established a linear regression model for each city's NTL and EPC. Compared with the estimation results before city classification (R2: 0.785), the R2 of the separately modeled service cities and technology and education cities increased to 0.866 and 0.830, respectively. However, the results for industrial cities were less consistent due to their more complex energy consumption structure. In general, using classification before modeling helps reflect factors affecting the relationship between EPC and NTL, making the estimation process more reasonable and improving the accuracy of the results.
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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 0360-5442 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2672
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Author Li, K.; Chen, Y.
Title A Genetic Algorithm-Based Urban Cluster Automatic Threshold Method by Combining VIIRS DNB, NDVI, and NDBI to Monitor Urbanization Type Journal Article
Year 2018 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 10 Issue 2 Pages 277
Keywords Remote Sensing
Abstract (up) Accurate and timely information related to quantitative descriptions and spatial distributions of urban areas is crucial to understand urbanization dynamics and is also helpful to address environmental issues associated with rapid urban land-cover changes. Thresholding is acknowledged as the most popular and practical way to extract urban information from nighttime lights. However, the difficulty of determining optimal threshold remains challenging to applications of this method. In order to address the problem of selecting thresholds, a Genetic Algorithm-based urban cluster automatic threshold (GA-UCAT) method by combining Visible-Infrared Imager-Radiometer Suite Day/Night band (VIIRS DNB), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI) is proposed to distinguish urban areas from dark rural background in NTL images. The key point of this proposed method is to design an appropriate fitness function of GA by means of integrating between-class variance and inter-class variance with all these three data sources to determine optimal thresholds. In accuracy assessments by comparing with ground truth—Landsat 8 OLI images, this new method has been validated and results with OA (Overall Accuracy) ranging from 0.854 to 0.913 and Kappa ranging from 0.699 to 0.722 show that the GA-UCAT approach is capable of describing spatial distributions and giving detailed information of urban extents. Additionally, there is discussion on different classifications of rural residential spots in Landsat remote sensing images and nighttime light (NTL) and evaluations of spatial-temporal development patterns of five selected Chinese urban clusters from 2012 to 2017 on utilizing this proposed method. The new method shows great potential to map global urban information in a simple and accurate way and to help address urban environmental issues.
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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 2340
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Author Tilottama, G., Sutton, P. C., & Elvidge, C. D.
Title Informal Economy and Remittance Estimates of India Using Nighttime Imagery Type Journal Article
Year 2010 Publication International Journal of Ecological Economics & Statistics Abbreviated Journal
Volume 17 Issue Pages
Keywords Remote Sensing; Economics
Abstract (up) Accurate estimates of the magnitude and spatial distribution of both formal and informal economic activity have many useful applications. Developing alternative methods for making estimates of these economic activities may prove to be useful when other measures are of suspect accuracy or unavailable. This research explores the potential for estimating the formal and informal economy for India using known relationships between the spatial patterns of nighttime satellite imagery and economic activity in the United States (U.S.). Regression models have been developed between spatial patterns of nighttime imagery and Adjusted Official Gross State Product (AGSP) for the states of the U.S. The slope and intercept parameters derived from the regression models of the U.S. were blindly applied to India, resulting in an underestimation of Gross State Income (GSI) for each state and Union Territory (UT) of India because of the lower level of urbanization in India in comparison to the U.S. However, a comparison of estimated GSI from the nighttime lights image and the official Gross State Product (GSP) of the states and UTs of India indicates a high correlation between them (r = 0.93). The different levels of urbanization (i.e. percent of population in urban areas) in the U.S. and India are used to adjust the Estimated Gross Domestic Income (EGDI) by multiplying by the ratio of the percentage of the population in urban areas for the two countries. This gives the Adjusted Estimated Gross Domestic Income of India (AEGDI), which is compared with the official Gross National Income (GNI) estimates of India’s states and UTs. The results suggest that the magnitude of India’s informal economy and the inflow of remittances are 150 percent larger than their existing official estimates in the GNI.
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Language Summary Language Original Title
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Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ intern @ Serial 2554
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Author Chen, X.; Jia, X.; Pickering, M.
Title A Nighttime Lights Adjusted Impervious Surface Index (NAISI) with Integration of Landsat Imagery and Nighttime Lights Data from International Space Station Type Journal Article
Year 2019 Publication International Journal of Applied Earth Observation and Geoinformation Abbreviated Journal International Journal of Applied Earth Observation and Geoinformation
Volume 83 Issue Pages 101889
Keywords Remote Sensing
Abstract (up) Accurate mapping of impervious surface is essential for both urbanization monitoring and micro-ecosystem research. However, the confusion between impervious surface and bare soil is the major concern due to their high spectral similarity in optical imagery. Integration of multi-sensor images is considered to offer a better capacity for distinguishing impervious surface from background. In this paper, a new impervious surface index namely nighttime light adjusted impervious surface index (NAISI), which integrates information from Landsat and nighttime lights (NTL) data from International Space Station (NTL-ISS), is proposed. Parallel to baseline subtraction approaches, NAISI integrate the information from the first component of principal component (PC) transformation of NTL-ISS, the Soil Adjusted Vegetation Index (SAVI) and the third component of tasseled cap transform (TC3) of the Landsat data. Visual interpretation and quantitative indices (SDI, Kappa and overall accuracy) were adopted to elevate the accuracy and separability of NAISI. Comparative analysis with NTL derived light intensity, optical indices, as well as existing optical-NTL indices were conducted to examine the performance of NAISI. Results indicate that NAISI achieves a more promising capability in impervious surface mapping. This demonstrates the superiority of integration of optical and nighttime lights information for imperviousness detection.
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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 2658
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Author Liang, H.; Guo, Z.; Wu, J.; Chen, Z.
Title GDP spatialization in Ningbo City based on NPP/VIIRS night-time light and auxiliary data using random forest regression Type Journal Article
Year 2019 Publication Advances in Space Research Abbreviated Journal Advances in Space Research
Volume in press Issue Pages
Keywords Remote Sensing
Abstract (up) Accurate spatial distribution information on gross domestic product (GDP) is of great importance for the analysis of economic development, industrial distribution and urbanization processes. Traditional administrative unit-based GDP statistics cannot depict the detailed spatial differences in GDP within each administrative unit. This paper presents a study of GDP spatialization in Ningbo City, China based on National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL) data and town-level GDP statistical data. The Landsat image, land cover, road network and topographic data were also employed as auxiliary data to derive independent variables for GDP modelling. Multivariate linear regression (MLR) and random forest (RF) regression were used to estimate GDP at the town scale and were assessed by cross-validation. The results show that the RF model achieved significantly higher accuracy, with a mean absolute error (MAE) of 109.46 million China Yuan (CNY)·km-2 and a determinate coefficient (R2=0.77) than the MLR model (MAE=161.8 million CNY·km-2, R2=0.59). Meanwhile, by comparing with the estimated GDP data at the county level, the town-level estimated data showed a better performance in mapping GDP distribution (MAE decreased from 115.1 million CNY·km-2 to 74.8 million CNY·km-2). Among all of the independent variables, NTL, land surface temperature (Ts) and plot ratio (PR) showed higher impacts on the GDP estimation accuracy than the other variables. The GDP density map generated by the RF model depicted the detailed spatial distribution of the economy in Ningbo City. By interpreting the spatial distribution of the GDP, we found that the GDP of Ningbo was high in the northeast and low in the southwest and formed continuous clusters in the north. In addition, the GDP of Ningbo also gradually decreased from the urban centre to its surrounding areas. The produced GDP map provides a good reference for the future urban planning and socio-economic development strategies.
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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 0273-1177 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2680
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