首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到19条相似文献,搜索用时 294 毫秒
1.
应用永久散射体雷达干涉(PSI)技术进行地表沉降监测研究,对PSI建模时采用的各相位分量的空间相关特性和沉降结果精度进行详细分析。试验选取覆盖上海地区的16幅高分辨率TerraSAR-X(TSX)SAR影像为数据源,进行PSI建模、形变提取和精度分析,并使用地面水准数据进行对比验证。结果表明,根据PS各相位分量的空间相关特性进行PS点的识别是合理的。与水准数据对比,两类年沉降速率结果具有很好的一致性,差异均值和标准偏差分别为1.6 mm/a和±4.6 mm/a,最小和最大差异量分别为0.198 7 mm/a和10.132 mm/a,证实了PSI技术在上海地区地表沉降监测的应用是有效和可靠的。  相似文献   

2.
本文在改进的永久散射体(PS)探测方法基础上,应用高分辨率永久散射体雷达干涉(PSI)探测上海市地表沉降,并对沉降原因进行了详细分析。实验选取2008年4月至2010年1月间,由德国卫星TerraSAR-X(TSX)所获取的18幅X波段(波长为3.1 cm)高分辨率SAR影像为数据源,进行PS探测、PSI建模、形变提取和分析。实验结果表明,改进的PS探测方法探测出的PS点是合理和可靠的,且高分辨率SAR影像对地面硬目标识别能力较强,显著提高了PS点的密度和覆盖范围。沉降探测结果显示,最大相对沉降速率达30 mm/yr,平均沉降速率为11.5 mm/yr。  相似文献   

3.
InSAR(Interferometric Synthetic Aperture Radar,InSAR)技术是随着合成孔径雷达发展起来的一种雷达干涉测量新技术,它可获得地表目标点的精确三维空间位置以及细微形变信息。基于雷达干涉测量发展的短基线(Small BAseline Subset,SBAS)干涉测量,可对缓慢地表形变进行高精度的监测。本文以广东省普宁市为实验区,选用2007~2010年间共10景ALOS/PALSAR数据,采用SBAS技术获取了该地区的形变时间序列和平均沉降速率,结果表明普宁市区存在多个严重的沉降漏斗,年最大沉降速率达15cm/a。利用观测时段内两期的水准点观测资料对SBAS时序结果进行验证,对比结果发现两者较差最大为46mm,最小为21mm,表明SBAS技术进行地面沉降监测的可靠性和有效性。  相似文献   

4.
随着城市的扩张,大型城市的郊区逐步成为新的工业生产及居民中心,为满足生产及生活用水需求,地下水被大量开采,进而导致地表沉降。目前对地表沉降的监测多集中在城市区域,城郊的地表沉降较少受到关注。本文提出使用高分辨率永久散射体(PS)雷达盖分干涉(PS-DInSAR)技术对大型城市郊区的沉降进行监测。选取某市城郊为实验区,使用覆盖该区的16幅高分辨率TerraSAR影像为数据进行PS-DIn-SAR沉降建模和解算,获取了谈区大范围的高分辨率沉降信息。谈市效区最大年沉降速度达到62mm/a(即年沉降量),平均沉降速度为24mm/a。分析表明,该区域的不均匀沉降与地下水的开采密切相关。  相似文献   

5.
短基线集差分干涉测量(SBAS-InSAR)技术是在传统DInSAR技术基础上发展起来的一种更高精度的长时序变形监测方法,可有效地克服传统DInSAR在微小形变监测中受时空去相干以及大气效应等因素的影响,已成为当前InSAR技术的研究热点.本文利用ENVISAT ASAR传感器获取的22幅C波段影像数据,基于短基线集差分干涉测量技术对北京地区地表沉降进行监测,获取每个观测时刻的形变累积量,得到研究区的形变序列图,进而分析了该区域地表沉降特征,结合地质环境监测成果,初步讨论了2003至2010年间北京地区区域地表沉降成因.  相似文献   

6.
利用时序InSAR反演常州市地表沉降速率   总被引:2,自引:1,他引:1  
利用25景Envisat ASAR数据和29景高分辨率(3 m分辨率)TerraSAR-X数据,采用永久散射体干涉测量技术(PSInSAR)研究了常州市2004-2014年的地表沉降速率。结果显示,常州市的主要沉降区域发生在武进区,存在2个主要的沉降中心和1个大范围的沉降条带,2004-2010年间的地表沉降速率达到26 mm/a,2010-2014年间沉降速率变缓,最大为24 mm/a。两组数据同时段的沉降量相关性达到0.78,并利用研究区域同期水准数据检验了本文的研究结果,两者的平均速率差值均在5 mm/a以内,表明时序InSAR技术反演结果的可靠性和精度。X波段高分数据监测到C波段无法监测的高速路段存在5.3 mm/a的沉降速率,与水准结果的RMS分别为2.5、4.2 mm/a,表明TerraSAR-X比Envisat ASAR不仅具有更高密度的PS点,并且探测目标的位移具有更高的灵敏度和更高的精度。  相似文献   

7.
地面沉降已成为我国主要地质灾害之一,本文利用27景Envisat ASAR数据,采用点目标干涉测量(IPTA)技术,以常州市为实验地区,得到常州地区2007 ~ 2011年间地表形变沉降速率图,结果表明,常州市区存在多处严重沉降,最大沉降速率达-31 mm/a,表明IPTA技术在城市地面沉降监测中有广泛的应用前景.  相似文献   

8.
地面沉降具有时间持续性与空间扩张性的特点,获取长时间序列、覆盖范围广及精度较高的地面沉降时空演化特征可以预防地面沉降造成的潜在危害。本文采用SBAS-InSAR技术,结合2017年4月—2021年2月的Sentinel-1A影像对西宁市城市地面进行沉降监测。研究结果表明,监测期间西宁市地表形变具有城区形变稳定、局部区域沉降明显及存在缓慢隆升区域的趋势;3处明显快速沉降区域(城西区的沉降区Ⅰ、城东区的沉降区Ⅱ和城北区的沉降区Ⅲ)的沉降速率约为20~35 mm/a;沉降的驱动因素为沉降区域的湿陷性黄土地层,其具有土层结构性脆弱承重特点,在覆盖土层的自重应力及建筑物附加应力的综合作用下,土质受水浸湿后,土壤的结构性能被迅速破坏,土层会发生显著的附加下沉,其强度也迅速降低,从而引起建筑物的不均匀沉降。  相似文献   

9.
地面沉降具有时间持续性与空间扩张性的特点,获取长时间序列、覆盖范围广及精度较高的地面沉降时空演化特征可以预防地面沉降造成的潜在危害。本文采用SBAS-InSAR技术,结合2017年4月—2021年2月的Sentinel-1A影像对西宁市城市地面进行沉降监测。研究结果表明,监测期间西宁市地表形变具有城区形变稳定、局部区域沉降明显及存在缓慢隆升区域的趋势;3处明显快速沉降区域(城西区的沉降区Ⅰ、城东区的沉降区Ⅱ和城北区的沉降区Ⅲ)的沉降速率约为20~35 mm/a;沉降的驱动因素为沉降区域的湿陷性黄土地层,其具有土层结构性脆弱承重特点,在覆盖土层的自重应力及建筑物附加应力的综合作用下,土质受水浸湿后,土壤的结构性能被迅速破坏,土层会发生显著的附加下沉,其强度也迅速降低,从而引起建筑物的不均匀沉降。  相似文献   

10.
探讨了多主影像相干目标InSAR(MCTSB-InSAR)技术在大区域地表沉降监测的应用。在基于特征区域相干性组合干涉像对基础上,利用三级阈值法实现稳定目标点的大密度、高精度提取,以此构建区域Delaunay三角网,创建差分相位函数模型,从而获取地表沉降速率和累积沉降量。以无锡市为例,对两幅各25期Radarsat-2影像进行分析,获取全市2012年2月-2016年1月约489 781个点目标的地表沉降时空分布信息。利用相近时段的水准测量数据进行精度评定,结果表明,二者具有较高一致性,验证了MCTSB-InSAR方法在大区域地表沉降监测中的有效性和可靠性。  相似文献   

11.
ALOS PALSAR双极化数据水稻制图   总被引:1,自引:0,他引:1  
以江苏省海安县为研究区,使用2008年获取的日本ALOS卫星PALSAR双极化模式数据,分析水稻在L波段SAR图像上的后向散射特征,并提出相应的水稻制图方法。水稻在L波段上表现出了和C波段相同的时相变化特征。HH极化后向散射依赖于水稻植株的空间分布结构,某些机械插秧区域的布拉格共振现象引起水稻后向散射严重增强,给利用PALSAR数据水稻制图带来了困难。而HV极化不存在布拉格共振现象。在考虑布拉格共振影响的条件下,提出了联合PALSAR双极化模式HH和HV极化数据、基于时相变化特征进行水稻制图的方法,获得了88.4%的制图精度。  相似文献   

12.
The study examined the capability of dual-polarization SAR data for forest cover mapping and change assessment in the Brazilian Amazon Forest regions. Shuttle Imaging Radar (SIR)-C and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data were analysed to map and quantify deforestation. The images were classified using hybrid classifier, where each land cover was grouped in various spectral sub-classes interpreted on the imagery and later merged together to generate the desired land cover classes. The classification accuracy for forest was reasonably high (>90%). The technique applied in this study can be extended for operational mapping and monitoring of deforestation in the tropics, particularly for those regions which are often covered by cloud.  相似文献   

13.
Land subsidence in densely urbanized areas is a global problem that is primarily caused by excessive groundwater withdrawal. The Kathmandu Basin is one such area where subsidence due to groundwater depletion has been a major problem in recent years. Moreover, on 25 April 2015, this basin experienced large crustal movements caused by the Gorkha earthquake (Mw 7.8). Consequently, the effects of earthquake-induced deformation could affect the temporal and spatial nature of anthropogenic subsidence in the basin. However, this effect has not yet been fully studied. In this paper, we applied the SBAS-DInSAR technique to estimate the spatiotemporal displacement of land subsidence in the Kathmandu Basin before and after the Gorkha earthquake, using 16 ALOS-1 Phased Array L-band Synthetic Aperture Radar (PALSAR) images during the pre-seismic period and 26 Sentinel-1 A/B SAR images during the pre- and post-seismic periods. The results showed that the mean subsidence rate in the central part of the basin was about ?8.2 cm/year before the earthquake. The spatial extents of the subsiding areas were well-correlated with the spatial distributions of the compressible clay layers in the basin. We infer from time-series InSAR analysis that subsidence in the Kathmandu basin could be associated with fluvio-lacustrine (clay) deposits and local hydrogeological conditions. However, after the mainshock, the subsidence rate significantly increased to ?15 and ?12 cm/year during early post-seismic (108 days) and post-seismic (2015–2016) period, respectively. Based on a spatial analysis of the subsidence rate map, the entire basin uplifted during the co-seismic period has started to subside and become stable during the early-post-seismic period. This is because of the elastic rebound of co-seismic deformation. However, interestingly, the localized areas show increased subsidence rates during both the early-post- and post-seismic periods. Therefore, we believe that the large co-seismic deformation experienced in this basin might induce the local subsidence to increase in rate, caused by oscillations of the water table level in the clay layer.  相似文献   

14.
针对PALSAR Level 1.1数据,研究使用NASA/JPL提供的开源干涉软件包ROI_PAC Version 3.0提取DEM.ROI_PAC的目前版本只能处理Level 1.0数据,因此,文章在分析了ROI_PAC软件包处理流程的基础上,提出处理Level 1.1数据的方法,并用PALSAR Level 1.1数据对该方法做了验证.干涉重建DEM与参考DEM的对比结果表明,二者的差异均值为0.27 m,标准差为±9.24 m,80%像元点的高程误差在±10 m以内.  相似文献   

15.
The current study has used Synthetic Aperture Radar (SAR) satellite data to estimate the Snow Cover Area (SCA) in Manali watershed of Beas River in Northwest Himalayas of Himachal Pradesh, India. SAR data used in this study is of Radarsat-2 (RS2) and Environmental Satellite (ENVISAT), Advanced Synthetic Aperture Radar (ASAR). The SAR preprocessing was done with SAR image processing tools for converting raw SAR images into calibrated geo-coded backscatter images. Maps for forest, built area, layover and shadow were created and used for masking snow cover in these areas. The backscattering ratio of wet snow to reference image threshold method with value range from ?2 to ?3 db was used to estimate wet SCA for study area. In this technique, if the threshold is too high (≥-2 db) wet SCA is overestimated and if it is too low (≤-3db), this method underestimates the SCA. The wet SCA is under/over estimated (+6 % to?8 % on average) in late spring season due to the inherent terrain and SAR imaging effects of layover/foreshortening and shadow and also due to the masking of forest areas. Overall, the SCA derived from SAR data matches well when compared with total SCA derived from cloud free optical remote sensing data products, especially during wet season.  相似文献   

16.
Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data from different observation modes were analysed to determine (1) which observation mode most accurately retrieves tropical forest biomass information and (2) whether different modes, when considered together, yield improved results in comparison to identical data-sets analysed independently. We performed regression analysis to estimate above-ground forest biomass using PALSAR backscatter data for natural and planted forests in south-eastern Bangladesh. The coefficient of determination (r 2) was lower or equal to 0.499 (n = 70) when PALSAR data from different observation modes were separately considered, but increased sharply when one class (rubber) is dropped and average backscatter of fine beam single (FBS) and polrimetric (PLR) modes are used in the analysis. The results presented in this article are useful for both regional and global forest biomass inventories and fixing acquisition modes for planned L-band SAR missions.  相似文献   

17.
Surface deformations in L’Aquila (centre of Italy) caused by the April 6th, 2009 earthquake were studied from space geodesy and remote sensing points of view using Synthetic Aperture Radar Interferometry (InSAR) and Sub-pixel Correlation Technique (SCT). InSAR was used to measure ground surface deformation in the satellite line of sight (LOS) direction and the deformation was determined using two separate interferometric pairs of ENVISAT ASAR and ALOS PALSAR data sets. Furthermore, SCT was employed to investigate the horizontal displacements in the area. Two separate pairs of ENVISAT ASAR and ASTER optical image data sets were employed, and horizontal displacements in Range/Azimuth and in west–east/south–north directions were investigated, respectively.  相似文献   

18.
SIR-B Synthetic Aperture Radar System operating at L-band (HH) acquired images over parts of the Assam plains at 25.6° and 45.2°incidence angle during October 1984. The capabilities of L-band SAR for delineating various land covers using multiple incidence angle imageries have been assessed. It was observed that colour composite image generated from multiple incidence angle imagery was useful in delineating various land cover units.  相似文献   

19.
Hot spot detection with satellite images, especially with synthetic aperture radar (SAR) images is still a challenging task. Several researchers have used TM/optical data for identification of hot spot but the use of SAR data is very limited for this type of application. The fusion of SAR data with TM/optical data may add additional information which in turn will lead for enhancement of detection capability of the hot spot. Therefore, this study explores the possibility of fusion of Moderate Resolution Imaging Spectroradiometer (MODIS) and Phased Array L-band Synthetic Aperture Radar (PALSAR) satellite images for the hot spot detection. Image fusion is emerging as a powerful tool where information of various sensors can be used for obtaining better results. For this purpose, vegetation greenness and roughness information which is obtained from MODIS and PALSAR satellite images, respectively, are used for fusion, and then, a contextual-based thresholding algorithm is applied to the fused image for hot spot detection. The proposed approach comprises of two steps: (1) application of genetic algorithm-based scheme for image fusion of MODIS and PALSAR satellite images, and (2) classification of the fused image as either hot spot or non-hot spot pixels by employing a contextual thresholding technique. The algorithm is tested over the Jharia Coal Field region of India, where hot spot is one of the major problems and it is observed that the proposed thresholding technique classifies the each pixel of the fused image into two categories: hot spot and non-hot spot and the proposed approach detects the hot spot with better accuracy and less false alarm.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号