| Records |
| 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 |
2020 |
Publication |
Landscape and Urban Planning |
Abbreviated Journal |
Landscape and Urban Planning |
| Volume |
193 |
Issue |
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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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0169-2046 |
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GFZ @ kyba @ |
Serial |
2697 |
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| Author |
Li, X.; Duarte, F.; Ratti, C. |
| Title |
Analyzing the obstruction effects of obstacles on light pollution caused by street lighting system in Cambridge, Massachusetts |
Type |
Journal Article |
| Year |
2019 |
Publication |
Environment and Planning B: Urban Analytics and City Science |
Abbreviated Journal |
Environment and Planning B: Urban Analytics and City Science |
| Volume |
in press |
Issue |
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Pages |
2399808319861645 |
| Keywords |
Skyglow; Lighting; upward light |
| Abstract |
Artificial light has transformed urban life, enhancing visibility, aesthetics, and increasing safety in public areas. However, too much unwanted artificial light leads to light pollution, which has a negative effect on public health and urban ecosystems, as well as on the aesthetic and cultural meanings of the night sky. Some of the factors interfering with the estimation of light pollution in cities are urban features, such as the presence of trees, road dimensions, and the physical characteristics of buildings. In this study, we proposed a simplified model for unwanted upward light coming from street luminaires based on a building height model and the publicly accessible Google Street View images. We simulated and analyzed the obstruction effects of different street features on the light pollution caused by the street lighting system in Cambridge, Massachusetts. By providing quantitative information about the connections between the streetscape features and the amount of unwanted upward artificial light, this study provides reference values to inform policies aimed at curbing light pollution. |
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2399-8083 |
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GFZ @ kyba @ |
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2587 |
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Kumar, P.; Rehman, S.; Sajjad, H.; Tripathy, B.R.; Rani, M.; Singh, S. |
| Title |
Analyzing trend in artificial light pollution pattern in India using NTL sensor's data |
Type |
Journal Article |
| Year |
2019 |
Publication |
Urban Climate |
Abbreviated Journal |
Urban Climate |
| Volume |
27 |
Issue |
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Pages |
272-283 |
| Keywords |
Remote Sensing; India; DMSP; DMSP-OLS |
| Abstract |
Exponential growth of population and the resultant rapid rate of urbanization and industrialization in India have significantly transformed its nighttime light environment. The study makes an attempt to analyze the spatio-temporal pattern of light pollution and its causative actors in a fast-developing economy. We utilized nighttime light data from 1993 to 2013 and calibrated through linear regression. Ten patches of major changes from the whole study area were selected to assess the intensity of light pollution at regional scale. Spatial analysis of light pollution in selected patches revealed that New Delhi, Telangana, Maharashtra, Karnataka and Uttar Pradesh experienced increase in very high light pollution intensity. West Bengal, Gujarat and Tamil Nadu witnessed a remarkable change from low to high light pollution. Urban expansion, industrial development and air pollution are main drivers for increasing light pollution. Strong correlation was found between light pollution and digital numbers (DN) values at regional scale. The maps generated through Defense Meteorological Satellite Program Operational Line Scanner Night Time Light data not only helped in assessing the intensity of light pollution but also identified its causative actors.The results of study can effectively be utilized for setting priorities of environmental protection in different geographical regions at various scales. |
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2212-0955 |
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GFZ @ kyba @ |
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2144 |
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Li, X.; Ma, R.; Zhang, Q.; Li, D.; Liu, S.; He, T.; Zhao, L. |
| Title |
Anisotropic characteristic of artificial light at night – Systematic investigation with VIIRS DNB multi-temporal observations |
Type |
Journal Article |
| Year |
2019 |
Publication |
Remote Sensing of Environment |
Abbreviated Journal |
Remote Sensing of Environment |
| Volume |
233 |
Issue |
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Pages |
111357 |
| Keywords |
Remote Sensing; Instrumentation |
| Abstract |
The released VIIRS DNB nightly images, also known as VIIRS DNB daily nighttime images, provide rich information for time series analysis of global socioeconomic dynamics. Anisotropic characteristic is a possible factor that influences the VIIRS DNB radiance at night and its time series analysis. This study aims to investigate the relationship between viewing angles and VIIRS DNB radiance of Suomi NPP satellite in urban areas. First, twenty-nine points were selected globally to explore the angle variation of Suomi NPP satellite views at night. We found that the variation of the satellite viewing zenith angle (VZA) is consistent (e.g. between 0° and 70°) since the range of VZA is fixed depending on the sensor design, and the range of viewing azimuth angle (VAA) increases with the increase of latitude. Second, thirty points in cities of Beijing, Houston, Los Angeles, Moscow, Quito and Sydney, were used to investigate the angle-radiance relationship. We proposed a zenith-radiance quadratic (ZRQ) model and a zenith-azimuth-radiance binary quadratic (ZARBQ) model to quantify the relationship between satellite viewing angles and artificial light radiance, which has been corrected by removing the moonlight and atmospheric impact from VIIRS DNB radiance products. For all the thirty points, the ZRQ and ZARBQ analysis have averaged R2 of 0.50 and 0.53, respectively, which indicates that the viewing angles are important factors influencing the variation of the artificial light radiance, but extending zenith to zenith-azimuth does not much better explain the variation of the observed artificial light. Importantly, based on the data analysis, we can make the hypothesis that building height may affect the relationship between VZA and artificial light, and cold and hot spot effects are clearly found in tall building areas. These findings are potentially useful to reconstruct more stable time series VIIRS DNB images for socioeconomic applications by removing the angular effects. |
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0034-4257 |
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GFZ @ kyba @ |
Serial |
2621 |
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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 |
2020 |
Publication |
Remote Sensing of Environment |
Abbreviated Journal |
Remote Sensing of Environment |
| Volume |
236 |
Issue |
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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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0034-4257 |
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GFZ @ kyba @ |
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2756 |
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