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Chen, B., Shi, G., Wang, B., Zhao, J., & Tan, S. (2012). Estimation of the anthropogenic heat release distribution in China from 1992 to 2009. Acta Meteorol Sin, 26(4), 507–515.
Abstract: Stable light data from Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) satellites and authoritative energy consumption data distributed by National Bureau of Statistics of China were applied to estimating the distribution of anthropogenic heat release in China from 1992 to 2009. A strong linear relationship was found between DMSP/OLS digital number data and anthropogenic heat flux density (AHFD). The results indicate that anthropogenic heat release in China was geographically concentrated and was fundamentally correlated with economic activities. The anthropogenic heat release in economically developed areas in northern, eastern, and southern China was much larger than other regions, whereas it was very small in northwestern and southwestern China. The mean AHFD in China increased from 0.07 W m−2 in 1978 to 0.28 W m−2 in 2008. The results indicate that in the anthropogenic heat-concentrated regions of Beijing, the Yangtze River Delta, and the Pearl River Delta, the AHFD levels were much higher than the average. The effect of aggravating anthropogenic heat release on climate change deserves further investigation.
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Chen, H., Zhang, X., Wu, R., & Cai, T. (2020). Revisiting the environmental Kuznets curve for city-level CO2 emissions: based on corrected NPP-VIIRS nighttime light data in China. Journal of Cleaner Production, , 121575.
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.
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Deng, J., Che, T., Xiao, C., Wang, S., Dai, L., & Meerzhan, A. (2019). Suitability Analysis of Ski Areas in China: An Integrated Study Based on Natural and Socioeconomic Conditions. The Cryosphere, 13, 2149–2167.
Abstract: The successful bidding of the 2022 Winter Olympics (Beijing 2022, officially known as the XXIV Olympic Winter Games) has greatly stimulated Chinese enthusiasm to participate in winter sports. Consequently, the Chinese ski industry is rapidly booming driven by enormous market demand and government support. However, investing in ski area at an unreasonable location will cause problems both from economic perspective (in terms of operation and management) as well as geographical concerns (such as environmental degradation). To evaluate the suitability of a ski area based on scientific 20 metrics has since become a prerequisite to the sustainable development of ski industry. In this study, we evaluate the locational suitability of ski areas in China by integrating their natural and socioeconomic conditions using linear weighted method based on geographic information systems (GIS) spatial analysis combined with remote sensing, online and field survey data. Key indexes for evaluating the natural suitability include snow cover, air temperature, topographic conditions, groundwater, and vegetation, whereas socioeconomic suitability is evaluated based on economic conditions, accessibility of transportation, 25 distance to tourist attractions, and distance to cities. As such, an integrated metrics considering both natural and socioeconomic suitability is defined to be a threshold and used to identify the suitability of a candidate region for ski area development. The results show that 92% of existing ski areas are located in areas with an integrated index greater than 0.5. In contrary, a ski area is considered to be a dismal prospect when the locational integrated index is less than 0.5. Finally, corresponding development strategies for decision-makers are proposed based on the multi-criteria metrics, which will be extended to incorporate potential influences from future climate change and socioeconomic development.
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Fan, J., He, H., Hu, T., Zhang, P., Yu, X., & Zhou, Y. (2019). Estimation of Landscape Pattern Changes in BRICS from 1992 to 2013 Using DMSP-OLS NTL Images. J Ind Soc Rem Sens, 47(5), 725–735.
Abstract: Nighttime light data from the Defense Meteorological Satellite Program’s Operational Linescan System are widely used for monitoring urbanization development. Brazil, Russia, India, China and South Africa (BRICS) countries have global economic and cultural influence in the new era. It was the first time for the researches about BRICS countries adopting nighttime light data to analyze the urbanization process. In this paper, we calibrated and extracted annual urbanized area patches from cities in BRICS based on a quadratic polynomial model. Nine landscape indexes were calculated to analyze urbanization process characteristics in BRICS. The results suggested that China and India both expanded more rapidly than other countries, with urban areas that increased by more than 100%. The expansion of large core cities was dominant in the urbanization of China, while emerging and expanding small urban patches were major forces in the urbanization of India. Since 1992, urbanization declined and urban areas shrunk in Russia, but core cities still maintained strength of urbanization. Due to economic recovery, urban areas near large cities in Russia began to expand. From 1992 to 2013, the urbanization process in South Africa developed slowly, as evidenced by time series fluctuations, but overall the development remained stable. The degree of urbanization in Brazil was greater than that in South Africa but less than that in Russia. Large-sized cities expanded slowly and small-sized cities clearly expanded in BRICS from 1992 to 2013.
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Gong, P., Li, X., & Zhang, W. (2019). 40-year (1978-2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing. Science Bulletin, 64(11), 756–763.
Abstract: Impervious surfaces are the most significant feature of human settlements. Timely, accurate, and frequent information on impervious surfaces is critical in both social-economic and natural environment applications. Over the past 40 years, impervious surface areas in China have grown rapidly. However, annual maps of impervious areas in China with high spatial details do not exist during this period. In this paper, we made use of reliable impervious surface mapping algorithms that we published before and the Google Earth Engine (GEE) platform to address this data gap. With available data in GEE, we were able to map impervious surfaces over the entire country circa 1978, and during 1985-2017 at an annual frequency. The 1978 data were at 60 m resolution, while the 1985-2017 data were in 30 m resolution. For the 30 m resolution data, we evaluated the accuracies for 1985, 1990, 1995, 2000, 2005, 2010, and 2015. Overall accuracies reached more than 90%. Our results indicate that the growth of impervious surface in China was not only fast but also considerably exceeding the per capita impervious surface area in developed countries like Japan. The 40-year continuous and consistent impervious surface distribution data in China would generate widespread interests in the research and policy-making community. The impervious surface data can be freely downloaded from http://data.ess.tsinghua.edu.cn.
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Jin, X., Li, Y., Zhang, J., Zheng, J., & Liu, H. (2017). An Approach to Evaluating Light Pollution in Residential Zones: A Case Study of Beijing. Sustainability, 9(4), 652.
Abstract: Outdoor lighting is becoming increasingly widespread, and residents are suffering from serious light pollution as a result. Residentsâ awareness of their rights to protection has gradually increased. However, due to the sometimes-inaccessible nature of residential vertical light incidence intensity data and the high cost of obtaining specific measurements, there is no appropriate hierarchic compensation for residents suffering from different degrees of light pollution. It is therefore important to measure light pollution levels and their damage at the neighborhood scale to provide residents with basic materials for proper protection and to create more politically-suitable solutions. This article presents a light pollution assessment method that is easy to perform, is low-cost and has a short data-processing cycle. This method can be used to monitor residential zone light pollution in other cities. We chose three open areas to test the spatial variation pattern of light intensity. The results are in accordance with spatial interpolation patterns and can be fit, with high precision, using the inverse distance weighted interpolation (IDW) method. This approach can also be used in three dimensions to quantitatively evaluate the distribution of light intensity. We use a mixed-use zone in Beijing known as The Place as our case study area. The vertical illumination at the windows of residential buildings ranges from 2 lux to 23 lux; the illumination in some areas is far higher than the value recommended by CIE. Such severe light pollution can seriously interfere with peopleâs daily lives and has a serious influence on their rest and health. The results of this survey will serve as an important database to assess whether the planning of night-time lighting is scientific, and it will help protect the rights of residents and establish distinguished compensation mechanisms for light pollution.
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Li, S., Cheng, L., Liu, X., Mao, J., Wu, J., & Li, M. (2019). City type-oriented modeling electric power consumption in China using NPP-VIIRS nighttime stable light data. Energy, 189, 116040.
Abstract: 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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Liu, Z., He, C., Zhang, Q., Huang, Q., & Yang, Y. (2012). Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008. Landscape and Urban Planning, 106(1), 62–72.
Abstract: Timely and accurate information about the dynamics of urban expansion is vital to reveal the relationships between urban expansion and the ecosystem, to optimize land use patterns, and to promote the effective development of cities in China. Nighttime stable light data from the Defense Meteorological Satellite Program's Operational Line-scan System (DMSP-OLS) Nighttime Lights Time Series dataset provide a new source of information that can quickly reveal the dynamics of urban expansion. However, the DMSP-OLS sensor has no on-board calibration, which makes it difficult to directly compare time series data from multiple satellites. This study developed a new method for systematically correcting multi-year multi-satellite nighttime stable lights data and rapidly extracting the dynamics of urban expansion based on this corrected data for China from 1992 to 2008. The results revealed that the proposed method effectively reduced abnormal discrepancy within the nighttime stable light data and improved continuity and comparability. The dynamics of urban expansion in China from 1992 to 2008 were extracted with an average overall accuracy of 82.74% and an average Kappa of 0.40.
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Lopez-Ruiz, H., Nezamuddin, N., Al Hassan, R., & Muhsen, A. (2019). Estimating Freight Transport Activity Using Nighttime Lights Satellite Data in China, India and Saudi Arabia. EconPapers, ks--2019-mp07.
Abstract: This paper focuses on the methodology for estimating total freight transport activity (FTA) for three countries — China, India and Saudi Arabia — with the objective of building on current state-of-the-art transportation modeling in three key areas: Studying the relationship between nighttime lights (NTL) and FTA allows for an estimation of full transportation datasets for countries where only a few observation points exist or where data is unavailable. Establishing the foundation for future work on how to use this approach in transport flow estimation (origin-destination matrices). Determining whether this approach can be used globally, given the coverage of the satellite data used. The paper uses the KAPSARC Transport Analysis Framework (KTAF), which estimates transport activity from freely available global data sources, satellite images and NTL. It is a tool for estimating freight transport activity that can be used in models to measure the impact of an accelerated transport policy planning approach. The methodology offers a solution to inadequate data access and allows for scenario building in policy planning for transportation. This approach allows for quick estimation of the effects of policy measures and economic changes on transportation activities at a global level. The paper also includes a detailed guide on how to replicate the methodology used in this analysis.
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Ma, T., Zhou, C., Pei, T., Haynie, S., & Fan, J. (2012). Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: A comparative case study from China's cities. Remote Sensing of Environment, 124, 99–107.
Abstract: Urbanization process involving increased population size, spatially extended land cover and intensified economic activity plays a substantial role in anthropogenic environment changes. Remotely sensed nighttime lights datasets derived from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) provide a consistent measure for characterizing trends in urban sprawl over time (Sutton, 2003). The utility of DMSP/OLS imagery for monitoring dynamics in human settlement and economic activity at regional to global scales has been widely verified in previous studies through statistical correlations between nighttime light brightness and demographic and economic variables ( and ). The quantitative relationship between long-term nighttime light signals and urbanization variables, required for extensive application of DMSP/OLS data for estimating and projecting the trajectory of urban development, however, are not well addressed for individual cities at a local scale. We here present analysis results concerning quantitative responses of stable nighttime lights derived from time series of DMSP/OLS imagery to changes in urbanization variables during 1994â2009 for more than 200 prefectural-level cities and municipalities in China. To identify the best-fitting model for nighttime lights-based measurement of urbanization processes with different development patterns, we comparatively use three regression models: linear, power-law and exponential functions to quantify the long-term relationships between nighttime weighted light area and four urbanization variables: population, gross domestic product (GDP), built-up area and electric power consumption. Our results suggest that nighttime light brightness could be an explanatory indicator for estimating urbanization dynamics at the city level. Various quantitative relationships between urban nighttime lights and urbanization variables may indicate diverse responses of DMSP/OLS nighttime light signals to anthropogenic dynamics in urbanization process in terms of demographic and economic variables. At the city level, growth in weighted lit area may take either a linear, concave (exponential) or convex (power law) form responsive to expanding human population and economic activities during urbanization. Therefore, in practice, quantitative models for using DMSP/OLS data to estimate urbanization dynamics should vary with different patterns of urban development, particularly for cities experiencing rapid urban growth at a local scale.
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