In order to reduce the impact of subsidence disaster and provide early warning for the subsidence disaster in Beijing plain area, based on the PS-InSAR time series monitoring results (2003—2009) of Beijing plain area, spatial interpolation analysis was made by using ArcGIS to construct the settlement data of Beijing plain area. The main roads in Beijing were selected for spatial buffer analysis to generate the subsidence area; the typical periods before and after the 2008 Olympic Games were selected to quantitatively analyze the impact of road traffic on the subsidence of Beijing plain area. The results show that the road traffic influence area accounts for more than 50% of the total subsidence area, and after the 2008 Olympic Games, the maximum proportion is 87.81%; with the increase of the distance from the road, the subsidence decreases; in the southwest area of Beijing plain, the subsidence of the middle and top of the Yongding River alluvial fan is far less than that of the fan edge area in the road traffic impact area. Road traffic is the main influencing factor and the external cause of the subsidence of Beijing plain area.
Zheng Jia-bing， Zheng Jia-rong， Zhang Li-li， Si Dian-hao， Zhang Chao， Chen Bei-bei
. Influence of Road Traffic on Subsidence of Beijing Plain Area[J]. Transport Research, 2020
, 6(6)
: 62
-72
.
DOI: 10.16503/j.cnki.2095-9931.2020.06.008
[1] Ferretti A, Prati C, Rocca F. Permanent scatterers in SAR interferometry[J]. IEEE Transactions on Geoscience & Remote Sensing, 2001, 39(1): 8-20.
[2] 陈强. 基于永久散射体雷达差分干涉探测区域地表形变的研究[D]. 成都：西南交通大学，2006.
[3] Liu G X, Luo X J, Chen Q, et al. Detecting land subsidence in shanghai by PS-Networking SAR interferometry[J]. Sensors, 2008, 8(8): 4725-4741.
[4] 宫辉力，张有全，李小娟，等. 基于永久散射体雷达干涉测量技术的北京市地面沉降研究[J]. 自然科学进展，2009，19（11）：1261-1266.
[5] 陈蓓蓓，宫辉力，李小娟，等. 北京地下水系统演化与地面沉降过程[J]. 吉林大学学报（地球科学版），2012，42（S1）：373-379.
[6] 宫辉力，李小娟，潘云，等. 京津冀地下水消耗与区域地面沉降演化规律[J]. 中国科学基金，2017，31（1）：72-77.
[7] Yan Y J, Doin M P, Lopez-Quiroz P, et al. Mexico city subsidence measured by InSAR time series: joint analysis using PS and SBAS approaches[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012, 5(4): 1312-1326.
[8] 贾洪果，刘国祥，于冰. 基于超短基线PSInSAR 的道路网沉降监测[J]. 测绘通报，2012（5）：24-28.
[9] Chen M, Strobl J. Multispectral textured image segmentation using a multi-resolution fuzzy Markov random field model on variable scales in the wavelet domain[J]. International Journal of Remote Sensing, 2013, 34(13): 4550-4569.
[10] 郑佳荣，宫辉力，李青元，等. 基于PS－InSAR的2003—2009年北京平原区沉降控制因素分析[J]. 测绘通报，2014（12）：40-43.
[11] 郑佳荣，桂维振，陈蓓蓓，等. 基于三维地质建模的北京市平原区沉降分析[J]. 北京工业职业技术学院学报，2018，17（4）：6-12.
[12] 郑佳荣，宫辉力，李青元，等. 北京平原区不均匀沉降控制因素研究[J]. 测绘通报，2018（9）：108-111.
[13] 周玉营，陈蜜，宫辉力，等. 基于时序InSAR的京津高铁北京段地面沉降监测[J]. 地球信息科学学报，2017，19（10）：1393-1403.
[14] 周超凡，宫辉力，陈蓓蓓，等. 利用数据场模型评价北京地面沉降交通载荷程度[J]. 吉林大学学报（地球科学版），2017，47（5）：1511-1520.
[15] 刘凯斯，宫辉力，陈蓓蓓. 基于InSAR 数据的北京地铁6号线地面沉降监测分析[J]. 地球信息科学学报，2018，20（1）：128-137.
[16] 邱亚辉，别伟平，薄志毅，等. 基于InSAR的城市地下轨道交通沉降与灾害监测[J]. 测绘通报，2020（2）：107-112.
