地球科学进展 ›› 2024, Vol. 39 ›› Issue (7): 752 -765. doi: 10.11867/j.issn.1001-8166.2024.053

研究简报 上一篇    

典型山地城镇梯度开发与地面沉降空间关联特征
李政宏 1( ), 周亮 1 , 2 , 3( ), 高鸿 1 , 3, 王文达 1, 魏伟 4   
  1. 1.兰州交通大学 测绘与地理信息学院,甘肃 兰州 730030
    2.地理国情监测技术应用国家地方联合 工程研究中心,甘肃 兰州 730030
    3.甘肃省地理国情监测工程实验室,甘肃 兰州 730030
    4.西北师范大学 地理与环境科学学院,甘肃 兰州 730030
  • 收稿日期:2024-04-08 修回日期:2024-06-09 出版日期:2024-07-10
  • 通讯作者: 周亮 E-mail:3243799954@qq.com;zhougeo@126.com
  • 基金资助:
    国家自然科学基金项目(42271214);甘肃省自然科学基金重点项目(21JR7RA281);中国科学院西部之光人才培养计划项目(2020XBZG-XBQNXZ-A)

Spatial Correlation Characteristics Between Gradient Development and Land Subsidence in Typical Mountainous Towns

Zhenghong LI 1( ), Liang ZHOU 1 , 2 , 3( ), Hong GAO 1 , 3, Wenda WANG 1, Wei WEI 4   

  1. 1.School of Surveying and Geoinformation, Lanzhou Jiaotong University, Lanzhou 730030, China
    2.National and Local Joint Engineering Research Center for the Application of Geographic Monitoring Technology, Lanzhou 730030, China
    3.Gansu Provincial Geographic Monitoring Engineering Laboratory, Lanzhou 730030, China
    4.School of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730030, China
  • Received:2024-04-08 Revised:2024-06-09 Online:2024-07-10 Published:2024-07-29
  • Contact: Liang ZHOU E-mail:3243799954@qq.com;zhougeo@126.com
  • About author:LI Zhenghong, Master student, research area includes urban remote sensing. E-mail: 3243799954@qq.com
  • Supported by:
    the National Natural Science Foundation of China(42271214);Key Project of Natural Science Foundation of Gansu Province(21JR7RA281);Western Light Talent Training Program of the Chinese Academy of Sciences(2020XBZG-XBQNXZ-A)

山地城镇发展受限于地形地貌,出现了以新城建设为主的城市扩张模式。该模式地理空间表现为新城建设远离主城区,城市建设用地逐渐向更高的坡度上扩张(即建设用地梯度扩张)。梯度扩张虽解决了山地城镇土地资源紧缺问题,但也提高了诸如地面沉降等地质灾害风险,因而探究梯度扩张规律以及识别灾害风险是研究的重中之重。研究选取梯度扩张程度剧烈的3个新城区作为典型案例区域,利用数字高程模型获取了2017—2022年新区梯度扩张区域,基于2016—2020年Sentinel-1A SAR数据利用SBAS-InSAR技术得到地表形变信息,揭示新区梯度扩张与地面沉降之间的空间关联。结果表明: 2017—2022年,延安新区、两江新区和兰州新区的梯度扩张现象显著,梯度扩张区域占比分别为53.5%、51.0%和45.2%,受地形影响最严重的延安新区梯度扩张区域占比最高,梯度扩张速度与城市扩张速度趋势基本相符。 延安新区、两江新区和兰州新区最大沉降速率分别为28 mm/a、30 mm/a和29 mm/a,沉降多发生在新区扩张前沿且沉降区周围均存在不同规模梯度的扩张区域。 梯度扩张强度与地面沉降速率呈正相关,高梯度扩张强度和高地面沉降速率区域的集聚分布表明城市梯度扩张加速了扩张区域地面沉降的发生。研究对探究城市梯度扩张与地面沉降关联,推动山地城市可持续发展有着积极的作用。

The development of mountainous towns is limited by the terrain and landforms, resulting in an urban expansion model dominated by new city construction. The geographical spatial manifestation of this model is that the construction of new cities is far from the main urban area and urban construction land gradually expands toward higher slopes (i.e., gradient expansion of construction land). Although gradient expansion solves the problem of land resource scarcity in mountainous towns, it also increases the risk of geological disasters, such as land subsidence. Exploring the law of gradient expansion and identifying disaster risks are paramount. This study selected three new cities with severe gradient expansion as typical case areas and used DEM to obtain the gradient expansion areas of the new areas from 2017 to 2022. Based on Sentinel-1A SAR data from 2016 to 2020, SBAS InSAR technology was used to obtain surface deformation information in order to reveal the spatial correlation between gradient expansion and land subsidence in new areas. The results showed that, from 2017 to 2022, the gradient expansion phenomenon in Yan'an New Area, Liangjiang New Area, and Lanzhou New Area was significant, with gradient expansion areas accounting for 53.5%, 51.0%, and 45.2%, respectively. Yan'an New Area, which was most severely affected by terrain, had the highest proportion of gradient expansion areas, and the gradient expansion speed was consistent with the urban expansion speed trend. The maximum settlement velocities in Yan'an New Area, Liangjiang New Area, and Lanzhou New Area were 28, 30, and 29 mm/a, respectively. Settlement mostly occurred at the beginning of the expansion of the new area, and there were different scale-gradient expansion areas around the settlement area. The intensity of gradient expansion was positively correlated with the rate of land subsidence, and the clustering distribution of areas with high gradient expansion intensity and high ground subsidence rate indicated that urban gradient expansion accelerated the occurrence of land subsidence in the expansion area. This study had positive significance in exploring the correlation between urban gradient expansion and land subsidence, and in promoting the sustainable development of mountainous cities.

中图分类号: 

图1 我国第一台阶和第二台阶中3座典型的山地城市新区的高程影像
Fig. 1 Elevation images of three typical mountainous urban new areas in the first and second steps of China
表1 梯度扩张区域提取以及地面沉降监测使用数据
Table 1 Extraction of gradient expansion areas and use of data for ground subsidence monitoring
图2 20172022年兰州新区、延安新区和两江新区建设用地扩张特征
(a)~(c)建设用地扩张区域;(d)建设用地扩张与梯度扩张速度;(e)梯度扩张区域在扩张区域中占比;(f)不同梯度下梯度扩张区域占比
Fig. 2 Expansion characteristics of construction land in Lanzhou New AreaYan’an New Districtand Liangjiang New Area from 2017 to 2022
(a)~(c) Expansion area of construction land; (d) Construction land expansion and gradient expansion speed; (e) Proportion of gradient expansion region in the expansion region; (f) The proportion of gradient expansion regions under different gradients
表2 20172022年兰州新区、延安新区和两江新区梯度扩张区域面积及其在扩张区域的占比
Table 2 The area and proportion of gradient expansion zones in Lanzhou New AreaYan’an New Districtand Liangjiang New Area from 2017 to 2022
表3 兰州新区、延安新区和两江新区梯度扩张区域在不同梯度上的占比 (%)
Table 3 The proportion of gradient expansion areas in Lanzhou New AreaYan’an New Districtand Liangjiang New Area on different gradients
图3 两江新区(a)、延安新区(b)和兰州新区(cSBAS-InSAR形变速率结果
Fig. 3 SBAS-InSAR-based subsidence rates results in Liangjiang New Areaa), Yan’an New Districtb), and Lanzhou New Areac
图4 两江新区(a)、延安新区(b)和兰州新区(cPS-InSAR形变速率结果
Fig. 4 PS-InSAR-based subsidence rates results in Liangjiang New Areaa), Yan’an New Districtb), and Lanzhou New Areac
图5 两江新区(a)、延安新区(b)和兰州新区(cSBASPS形变速率验证图
Fig. 5 SBAS and PS subsidence rate verification char Liangjiang New Areaa),Yan’an New Districtb), and Lanzhou New Areac
图6 20172022年兰州新区、两江新区和延安新区梯度扩张区域
(a1)~(a6)兰州新区;(b1)~(b6)两江新区;(c1)~(c6)延安新区
Fig. 6 Gradual expansion areas of Lanzhou New AreaLiangjiang New Areaand Yan’an New District from 2017 to 2022
(a1)~(a6) Lanzhou New Area; (b1)~(b6) Liangjiang New Area; (c1)~(c6) Yan’an New District
图7 兰州新区、两江新区和延安新区不同窗口下的相关性系数
Fig. 7 Correlation coefficients under different windows in Lanzhou New AreaLiangjiang New Areaand Yan’an New District
图8 两江新区(a)、延安新区(b)和兰州新区(c)空间自相关集聚分区结果
Fig. 8 Results of spatial autocorrelation clustering zoning in Liangjiang New Areaa), Yan’an New Districtb), and Lanzhou New Areac
表4 延安新区、两江新区和兰州新区空间自相关分析结果
Table 4 Spatial autocorrelation analysis results of Yan’an New DistrictLiangjiang New Areaand Lanzhou New Area
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