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自然资源遥感  2022, Vol. 34 Issue (2): 289-295    DOI: 10.6046/zrzyyg.2020380
  技术应用 本期目录 | 过刊浏览 | 高级检索 |
基于珞珈一号夜光遥感数据的南京市夜间光污染监测
李家艺(), 徐永明(), 崔炜萍, 吴雨阳, 王晶, 苏博阳, 吉蒙
南京信息工程大学遥感与测绘工程学院,南京 210044
Monitoring of nighttime light pollution in Nanjing City based on Luojia 1-01 remote sensing data
LI Jiayi(), XU Yongming(), CUI Weiping, WU Yuyang, WANG Jing, SU Boyang, JI Meng
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
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摘要 

为获取城市内部精细的光污染分布特征,基于珞珈一号夜光遥感影像对南京市的夜间光污染进行监测。利用地表反射率与建筑覆盖度将珞珈一号的表观辐射亮度修正为地表入射亮度,结合实地观测照度构建多种经验模型计算南京市夜间照度,并基于计算得到的夜间照度分析南京市的夜间光污染分布状况。结果表明,三阶多项式模型精度最高,判定系数R2为0.87,平均绝对误差为4.71 lx。南京市夜间照度在0~55 lx之间,空间分布差异性明显。总体而言,照度高值区域主要集中在主城区,由主城区向四周呈递减趋势; 其中鼓楼区与秦淮区光污染最严重,超过70%的面积比例存在轻度以上光污染; 郊区的光污染程度较弱,光污染最弱的三个区依次是高淳区、溧水区与六合区,存在光污染的面积比例不足4%。南京市部分区域表现出极高的照度(30 lx以上),这些区域包括大型商场、大型工厂、交通枢纽、道路以及部分住宅区,需要注意的是,除了交通枢纽和大型工厂附近几乎无居民区外,其他区域附近都存在较多的居民区。文章探索了基于珞珈一号遥感影像监测城市夜间光污染的方法,为南京市的光污染整治工作提供了数据支撑,也为其他地区的光污染监测提供了科学参考。

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李家艺
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吴雨阳
王晶
苏博阳
吉蒙
关键词 珞珈一号卫星夜间光污染照度南京市    
Abstract

To obtain the distribution of nighttime light pollution on a city scale, this study monitors the nighttime light pollution in Nanjing City based on Luojia 1-01 nighttime light remote sensing images. The apparent radiance of the remote sensing images was converted into the surface incident luminance according to surface reflectance and building coverage ratio. Based on this and the illuminance values observed in the field, various empirical models were established to calculate the nighttime illuminance of Nanjing City. Finally, the distribution of nighttime light pollution in Nanjing City was analyzed according to the calculated nighttime illuminance. The results show that the third-order polynomial regression model had the highest accuracy, with a determination coefficient of 0.87 and a mean absolute error (MAE) of 4.71 lx. The nighttime illuminance in Nanjing City varied in the range of 0~55 lx, with obvious spatial distribution differences. In general, the areas with high illuminance were mainly concentrated in the main urban area and the illuminance showed a decreasing trend from the main urban area to the surrounding area. Light pollution was the most serious in Gulou and Qinhuai districts, where light pollution covered more than 70% in terms of area. The light pollution in the suburb was relatively weak, and the three districts with the weakest light pollution included Gaochun, Lishui, and Liuhe districts successively, where light pollution covered less than 4% in terms of area. Some areas in Nanjing City showed extremely high illuminance (> 30 lx), including large shopping malls, large factories, traffic hubs, roads, and some residential areas. It should be noted that there are many residential areas near these places except for traffic hubs and large factories. This study explored a method of monitoring urban light pollution at night based on Luojia 1-01 remote sensing data. It will provide data support for the light pollution control and management in Nanjing City and a scientific reference for the light pollution monitoring in other areas.

Key wordsLuojia 1-01data    nighttime light pollution    illuminance    Nanjing City
收稿日期: 2020-12-01      出版日期: 2022-06-20
ZTFLH:  TP79  
  X87  
基金资助:江苏省青蓝工程优秀青年骨干教师资助项目(R2019Q03);教育部人文社会科学研究青年基金项目“基于夜光遥感和机器学习的连片特困区贫困空间识别研究”(17YJCZH205);江苏省环境监测科研基金项目“夜光遥感与社会经济关联分析及其在环境监测中的初步应用”(1903)
通讯作者: 徐永明
作者简介: 李家艺(1998-),男,本科,研究方向为环境遥感。Email: jiayi_li4015@qq.com
引用本文:   
李家艺, 徐永明, 崔炜萍, 吴雨阳, 王晶, 苏博阳, 吉蒙. 基于珞珈一号夜光遥感数据的南京市夜间光污染监测[J]. 自然资源遥感, 2022, 34(2): 289-295.
LI Jiayi, XU Yongming, CUI Weiping, WU Yuyang, WANG Jing, SU Boyang, JI Meng. Monitoring of nighttime light pollution in Nanjing City based on Luojia 1-01 remote sensing data. Remote Sensing for Natural Resources, 2022, 34(2): 289-295.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2020380      或      https://www.gtzyyg.com/CN/Y2022/V34/I2/289
Fig.1  南京市行政区划图
(底图为高分一号WFV B3(R),B2(G),B1(B)合成影像)
Fig.2  2018年11月23日LJ 1-01夜光遥感影像
Fig.3  实测照度与表观辐射亮度和修正后地表入射亮度散点图
回归模型 回归方程
一元线性回归模型 Ev=aL+b
二阶多项式回归模型 Ev=a1 L 2+a2L+b
三阶多项式回归模型 Ev=a1 L 3+a2 L 2+a3L+b
指数回归模型 E v = e ( a L + b )
对数回归模型 Ev=aln(L)+b
Tab.1  统计模型形式
Fig.4  不同模型估算值和实地观测值之间散点图
Fig.5  南京夜间照度空间分布图
等级 光污染程度 照度值/lx
0级 无光污染 < 2.00
1级 轻度光污染 [2.00,5.00)
2级 中度光污染 [5.00,10.00)
3级 重度光污染 [10.00,25.00]
4级 严重光污染 >25.00
Tab.2  不同等级光污染分级标准
Fig.6  各区不同等级夜间光污染面积占比
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