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Temporal variations of artificial nighttime lights and their implications for urbanization in the conterminous United States, 2013-2017

机译:人工夜间灯的时间变化及其对Conterlinound美国城市化的影响,2013-2017

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Artificial nighttime lights (NTL) generated by human activities offer a unique opportunity to understand urban environments. Although previous studies have widely used NTL images to map urban extent at multiple scales, it remains a challenging task to address how NTL respond exactly to urbanization and thus to map urbanization from NTL. In this study, using monthly Suomi National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) NTL images between 2013 and 2017, we developed a method to decompose time-series NTL signal into annual and seasonal components. Further, we proposed an NTL-based indicator for the detection of impervious surfaces change (ISC) by integrating annual increment and seasonal variation of NTL brightness. The indicator was then used to identify ISC by using a thresholding method. The application of the methodology in the conterminous United States (CONUS) revealed a more rapid urbanization in the southern CONUS than the northern states and a northeastern-southwestern gradient of NTL seasonality. It was also found that NTL of November and December provided the most accurate characterization of urban extent for most areas in the CONUS. The detection of ISC in four representative regions (i.e. Dallas-Fort Worth-Arlington, greater Washington D.C., Denver-Aurora, and Atlanta) resulted in a moderate to high accuracy with the overall accuracy of similar to 80% and the Kappa value ranging from 0.56 to 0.73. Despite of this, the results showed a low accuracy of NTL-derived changing year of ISC (Kappa: 0.28) because of the existence of temporal inconsistency between NTL increase and ISC. The proposed method has the potential to timely map urban expansion at large geographical scales (e.g., continental and global) in a cost-efficient manner.
机译:人工夜间灯(NTL)由人类活动产生提供了理解城市环境的独特机会。尽管以前的研究广泛使用了NTL图像以在多个尺度上映射城市范围,但是解决了NTL如何完全响应城市化并从NTL映射城市化而仍然有挑战性的任务。在这项研究中,使用2013年和2017年之间的月度苏米国家极性轨道伙伴关系/可见红外成像辐射计套件(NPP / VIIRS)NTL图像,我们开发了一种将时间序列NTL信号分解为年度和季节组件的方法。此外,我们提出了一种基于NTL的指标,用于通过整合每年增量和NTL亮度的季节性变化来检测不透水表面变化(ISC)。然后使用指示剂来识别ISC通过使用阈值方法。该方法在康塞尔(Conus)在南部南部展开了比NTL季节性的北方国家和东北部梯度更快的城市化。还发现11月和12月的NTL为康斯大多数地区提供了城市范围最准确的城市程度。在四个代表区(即Dallas-Fort-Arlington,大华盛顿DC,Denver-Aurora和亚特兰大的ISC检测导致中度至高精度,其总体精度与80%相似,kappa值范围0.56至0.73。尽管如此,结果表明,由于NTL增加和ISC之间的时间不一致存在时间不一致,结果表明了NTL衍生的变化年的精度低。该拟议的方法有可能以成本效益的方式在大型地理标度(例如,大陆和全球)上及时地地图城市扩张。

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