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遥感技术与应用  2020, Vol. 35 Issue (6): 1348-1359    DOI: 10.11873/j.issn.1004-0323.2020.6.1348
灯光遥感专栏     
基于VIIRS夜间灯光数据的山东半岛城市群发展特征研究
李桂华1(),范俊甫1(),周玉科2,张悦1
1.山东理工大学 建筑工程学院 测绘工程系,山东 淄博 255049
2.中国科学院地理科学与资源研究所 生态系统网络观测与模拟院重点实验室,北京 100101
Development Characteristics Estimation of Shandong Peninsula Urban Agglomeration Using VIIRS Night Light Data
Guihua Li1(),Junfu Fan1(),Yuke Zhou2,Yue Zhang1
1.School of Civil and Architectural Engineering,Shandong University of Technology,Zibo 255049,China
2.Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Nature Resources Research,CAS,Beijing 100101,China
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摘要:

NPP-VIIRS夜间灯光数据是在中大尺度上开展城市发展变化研究的稳定数据源。基于2012~2018年NPP-VIIRS夜间灯光数据,以山东半岛城市群为研究对象,采用参考比较法提取城市建成区图斑,选取9个景观格局指数对山东半岛城市群的城市化发展特征进行定量分析。结果表明:①整体上,域内斑块总面积以4.5%的速度增长,边缘总长度和边缘密度年均增长3.15%,斑块数量和密度增长较快(分别为1.95%和1.98%),表明山东半岛城市群整体城市面积增长迅速,城市范围持续扩张;②从不同指标变化趋势来看,各城市斑块总面积增长最快的是青岛市和东营市(分别为9.66%和6.01%);青岛市的斑块数量和密度增速最快(分别为9.54%和8.55%),日照市的斑块数量和密度均以3.65%的速率显著降低;景观形状指数整体增速缓慢;平均回旋半径在日照市具有较高的年均增长速度(5.99%);③从各城市发展特征的差异性来看,青岛市的平均斑块面积和回旋半径分别以0.56%和1.53%的速度降低,其他各指标均显著增加,表明青岛市出现了较多的新兴城镇,城区面积不断扩大;济南、日照和东营市的城区面积增长较快,斑块数量、景观形状指数等指标增长缓慢,城市发展以旧城区的扩张为主;潍坊、淄博和烟台市在2015年和2016年前后经历了新兴城镇出现,城镇融合的阶段,城市发展较快。总体而言,山东半岛城市群城市化发展较快,但空间差异性明显。

关键词: NPP?VIIRS山东半岛城市群参考比较法景观格局指数    
Abstract:

NPP-VIIRS night lighting data is a stable data source for the study of urban development and change on medium and large scale. Based on the night lighting data of NPP-VIIRS from 2012 to 2018, taking Shandong Peninsula urban agglomeration as the research object, extracting urban built-up area patches by reference comparison method and selecting nine landscape pattern indices to quantitatively analyze the urbanization development characteristics of Shandong Peninsula urban agglomeration. The results showed that: ①As a whole, the total area of patches in Shandong Peninsula increased at a rate of 4.5%, the total length and density of the edges increased by 3.15% annually, and the number and density of patches increased rapidly (1.95% and 1.98%, respectively), indicating that the overall urban area of Shandong Peninsula urban agglomeration increased rapidly and the urban area continued to expand. ②According to the changing trend of different indicators, qingdao and dongying cities (9.66% and 6.01% respectively) had the fastest growth in the total area of patches; qingdao had the fastest increase in the number and density of patches (9.54% and 8.55% respectively), and rizhao had a significant decrease in the number and density of patches at the rate of 3.65%; the overall growth rate of landscape shape index was slow; the average radius of gyration had a high annual growth rate in rizhao city (5.99%). ③From the differences in the development characteristics of various cities, the average patch area and gyration radius of qingdao decreased by 0.56% and 1.53% respectively, while other indicators increased significantly, indicating that there were more emerging towns in qingdao and the urban area continued to expand. Urban areas in jinan, rizhao and dongying cities growed rapidly, and the number of patches, landscape shape index and other indicators grow slowly. The urban development of jinan, rizhao and dongying cities is dominated by the expansion of old urban areas. Around 2015 and 2016, weifang, zibo and yantai experienced the emergence of emerging towns and urban integration, with rapid urban development. Generally speaking, the urbanization of Shandong Peninsula urban agglomeration develops rapidly, but the spatial difference is obvious.

Key words: NPP-VIIRS    Shandong Peninsula Urban Agglomeration    Reference comparison method    Landscape pattern indices
收稿日期: 2019-08-31 出版日期: 2021-01-26
ZTFLH:  TP79  
基金资助: 国家重点研发计划项目(2017YFB0503500);山东省自然科学基金项目(ZR2020MD0115);国家自然科学基金项目(41601478);山东理工大学青年教师发展支持计划项目(4072-115016)
通讯作者: 范俊甫     E-mail: ligh_sdut@163.com;fanjf@sdut.edu.cn
作者简介: 李桂华(1994-),女,山东聊城人,硕士研究生,主要从事GIS开发与城市遥感应用研究。E?mail:ligh_sdut@163.com
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引用本文:

李桂华,范俊甫,周玉科,张悦. 基于VIIRS夜间灯光数据的山东半岛城市群发展特征研究[J]. 遥感技术与应用, 2020, 35(6): 1348-1359.

Guihua Li,Junfu Fan,Yuke Zhou,Yue Zhang. Development Characteristics Estimation of Shandong Peninsula Urban Agglomeration Using VIIRS Night Light Data. Remote Sensing Technology and Application, 2020, 35(6): 1348-1359.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2020.6.1348        http://www.rsta.ac.cn/CN/Y2020/V35/I6/1348

城市2012年2013年2014年2015年2016年2017年2018年
济南485.3533.7546.4557567.7583.6606
青岛554.8660.3688.8770.1811846.3921
烟台501.8508.2549560.5569.8580.2603.7
潍坊399.7417.9434.5451.6459.8470.2488.5
威海258.2266.2272.3277.1279.6285291
淄博237.9250262.3267270.6275.5286
日照95.897.199.6100.8103.7107.1108.4
东营111113114.8118.7151.2152.8159.7
表1  2012~2017年山东半岛城市群各城市建成区面积(km2)
图1  技术流程图
图2  2016年济南市原始年度数据与合成年数据亮度差值图
数据统计年鉴数据原始年度数据合成年数据
面积/km2567.7567.81568.36
绝对误差/km200.110.66
相对误差/%00.020.11
表2  2016年济南市原始年度数据与合成年数据下建成区面积对比
图3  淄博市历年最佳阈值组合及建成区面积提取误差
图4  Landsat 8和NPP-VIIRS数据提取2018年张店区城区结果对比
景观指数缩写公式单位描述信息
斑块数量NPNP=n城镇斑块数量,该值与景观的破碎化程度成正比
斑块总面积CACA=i=1nAi104hm2所有城镇斑块的面积
总边界长度TETE=k=1meikm城镇斑块的所有边缘长度之和
平均边界密度EDED=TETA×10??000m/hm2单位面积上,城镇斑块的边缘长度。ED值与景观破碎化程度成正比,实现不同景观之间的比较
斑块密度PDPD=NPTA×10??000个/hm2单位面积上的城镇斑块数量。PD表示不同斑块之间相互影响的强度,反映景观整体的复杂程度
平均斑块面积MPAMPA=TANP×10??000hm2城镇斑块的平均面积,反映了城镇斑块的破碎程度
最大斑块指数LPILPI=max(A1,?,An)TA×100%最大城镇斑块面积占总斑块面积的百分比
景观形状指数LSILSI=0.25×TETALSI表示斑块边界的复杂性和不规则性,反映斑块的聚合或离散程度,LSI值越大,斑块越离散
平均回旋半径GYRATEGYRATE=i=1nj=1zhijzNPm斑块中各点到斑块中心的平均距离的平均值,用于表示斑块的扩展模式
表3  各景观指数及其描述
图5  山东半岛城市群景观格局指数变化趋势图
图6  青岛市景观格局指数变化趋势及建成区面积扩张
图7  旧城区扩张型城市景观格局指数变化趋势及建成区面积扩张
图8  新兴城镇出现—融合型城市景观格局指数变化趋势及建成区面积扩张
图9  烟台市景观格局指数变化趋势及建成区面积扩张
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