利用PS-InSAR技术进行城市地铁沿线形变监测与机理分析

本文利用PS-InSAR技术获取了上海地区沉降速率场及累计沉降量等信息,并分析了该地区的沉降时空分布特征,以及该地区沉降与降水量、地铁施工运营等因素之间的关系。研究表明:①上海市沉降呈不均匀分布,北部沉降较稳定,而中部的虹口区、南部的闵行区、东部的浦东新区均发生了不同程度的沉降。其中,闵行区沉降最为严重,其最大累计沉降量达-43 mm,呈大范围、大沉降现象。②研究区域内沉降量呈非线性沉降现象及明显的季节性变化,且与地区降水量有关,降雨量对地下水的及时补充可以有效缓解地面过度沉降的发生。③上海地铁3、15、16号线部分路段均出现明显沉降现象,且处于在建阶段的15号线沉降最为明显,部分路段最大累计沉降量达-34 mm。     

Evaluation of polarimetric capabilities of dual polarized Sentinel-1 and TerraSAR-X data to improve the PSInSAR algorithm using amplitude dispersion index optimization

Polarimetric data is an additional source of information in PSI technique to improve its performance in land subsidence estimation. The combination of polarimetric data and radar interferometry can lead to an increase in coherence and the number of PS pixels. In this paper, we evaluated and compared the dual polarized Sentinel-1A (S1A) and TerraSAR-X (TSX) data to improve the PSInSAR algorithm. The improvement of this research is based on minimizing Amplitude Dispersion Index (ADI) by finding the optimum scattering mechanism to increase the number of PSC and PS pixels. The proposed method was tested using a dataset of 40 dual-pol SAR data (VV/VH) acquired by S1A and 20 dual-pol SAR data (HH/VV) acquired by TSX. The results revealed that using the TSX data, the number of PS pixels increased about 3 times in ESPO method than using the conventional channels, e.g., HH, and VV. This increase in S1A data was about 1.7 times in ESPO method. In addition, we investigated the efficiency of the three polarimetric optimization methods i.e. ESPO, BGSM, and Best for the dual polarized S1A and TSX data. Results showed that the PS density increased about 1.9 times in BGSM and about 1.5 times in Best method in TSX data. However, in S1A data, PS density increased about 1.1 times in BGSM. The Best method was not successful in increasing the PS density using the S1A data. Also, the effectiveness of the method was evaluated in urban and non-urban regions. The experimental results showed that the method was successful in significantly increasing the number of final PS pixels in both regions.     

The worsening impacts of land reclamation assessed with Sentinel-1: The Rize (Turkey) test case

Massive amounts of land are being reclaimed to build airports, new cities, ports, and highways. Hundreds of kilometers are added each year, as coastlines are extended further out to the sea. In this paper, this urbanization approach is monitored by Persistent Scatterer Interferometry (PSI) technique with Sentinel-1 SAR data. The study aims to explore this technology in order to support local authorities to detect and evaluate subtle terrain displacements. For this purpose, a large 3-years Sentinel-1 stack composed by 92 images acquired between 07/01/2015 to 27/01/2018 is employed and stacking techniques are chosen to assess ground motion. The test site of this study, Rize, Turkey, has been declared at high risk of collapse and radical solutions such as the relocation of the entire city in another area are been taken into consideration. A media fact-checking approach, i.e. evaluating national and international press releases on the test site, is considered for the paper and this work presents many findings in different areas of the city. For instance, alerts are confirmed by inspecting several buildings reported by the press. Critical infrastructures are monitored as well. Portions of the harbor show high displacement rates, up to 1 cm/year, proving reported warnings. Rural villages belonging to the same municipality are also investigated and a mountainous village affected by landslide is considered in the study. Sentinel-1 is demonstrated to be a suitable system to detect and monitor small changes or buildings and infrastructures for these scenarios. These changes may be highly indicative of imminent damage which can lead to the loss of the structural integrity and subsequent failure of the structure in the long-term. In Rize, only a few known motion-critical structures are monitored daily with in-situ technologies. SAR interferometry can assist to save expensive inspection and monitoring services, especially in highly critical cases such as the one studied in this paper.     

Assessing the suitability of data from Sentinel-1A and 2A for crop classification

Sentinel-1A C-SAR and Sentinel-2A MultiSpectral Instrument (MSI) provide data applicable to the remote identification of crop type. In this study, six crop types (beans, beetroot, grass, maize, potato, and winter wheat) were identified using five C-SAR images and one MSI image acquired during the 2016 growing season. To assess the potential for accurate crop classification with existing supervised learning models, the four different approaches namely kernel-based extreme learning machine (KELM), multilayer feedforward neural networks, random forests, and support vector machine were compared. Algorithm hyperparameters were tuned using Bayesian optimization. Overall, KELM yielded the highest performance, achieving an overall classification accuracy of 96.8%. Evaluation of the sensitivity of classification models and relative importance of data types using data-based sensitivity analysis showed that the set of VV polarization data acquired on 24 July (Sentinel-1A) and band 4 data (Sentinel-2A) had the greatest potential for use in crop classification.     

InSAR填海区地铁沿线地表沉降反演分析

为了更好地监测和掌握深圳填海区地铁工程结束后地铁沿线的地面沉降情况,该文利用TS-InSAR技术和20景2017年8月15日—2019年3月14日的Sentinel-1A SAR数据,借助POD精密定轨星历和ASTER GDEM V2分别去除轨道误差和地形相位,反演了深圳填海区2017—2019年地表沉降时间序列,并在此基础上重点分析了填海区地铁沿线地面沉降的时空演变规律以及地面沉降成因。结果显示,填海区各地铁沿线的地面沉降特征较为明显,最大沉降速率为-17.52 mm/a。其中,宝安中心、前海湾、深圳湾区段地铁沿线的地面沉降趋势较为严重,其地面沉降呈现逐渐增强和扩散趋势。     

利用Sentinel-1A数据监测南京河西地区地面沉降

南京河西地区是受长江和秦淮河淤积演化而成的漫滩地,由于河西新城大规模开发建设和地质条件的影响,地面沉降已成为该区域城市发展中不容忽视的问题。Sentinel-1数据是目前在轨运行的免费SAR数据,其具有较短的重访周期和较大的幅宽,为实现大范围长时序的地表形变监测提供了重要的数据源。利用短基线集干涉（SBAS-InSAR）技术对2015年4月至2018年4月覆盖南京河西地区的19景Sentinel-1A数据进行处理,获取了研究区2015—2018年间的地面沉降结果,并结合城市开发、人口分布等信息深入分析了地面沉降分布特征和成因。     

Assessment of Sentinel-1A data for rice crop classification using random forests and support vector machines

This study developed an approach to map rice-cropping systems in An Giang and Dong Thap provinces, South Vietnam using multi-temporal Sentinel-1A (S1A) data. The data were processed through four steps: (1) data pre-processing, (2) constructing smooth time series VH backscatter data, (3) rice crop classification using random forests (RF) and support vector machines (SVM) and (4) accuracy assessment. The results indicated that the smooth VH backscatter profiles reflected the temporal characteristics of rice-cropping patterns in the study region. The comparisons between the classification results and the ground reference data indicated that the overall accuracy and Kappa coefficient achieved from RF were 86.1% and 0.72, respectively, which were slightly more accurate than SVM (overall accuracy of 83.4% and Kappa coefficient of 0.67). These results were reaffirmed by the government’s rice area statistics with the relative error in area (REA) values of 0.2 and 2.2% for RF and SVM, respectively.     

多视角InSAR数据解算2017两伊地震三维同震形变场

2017两伊地震是自1900年以来发生在扎格罗斯山脉的最大地震,为了研究此次地震引起的同震形变场,利用覆盖同一地区的3对Sentinel-1A升降轨数据分别进行两通差分DInSAR处理,得到了研究区3个视线向的地表同震形变场,通过直接解算法重建了研究区的三维同震形变场。试验表明：3种视角的升降轨视线向上升与沉降总体趋势基本一致;联合多个视角的观测结果可以实现三维形变场的重建;根据地表视线向和三维同震形变的特征以及地质构造背景推测了发震断层很有可能为扎格罗斯山前断层。     

Coseismic surface deformation of the 2014 Napa earthquake mapped by Sentinel-1A SAR and accuracy assessment with COSMO-SkyMed and GPS data as cross validation

ABSTRACT

The new land observation satellite Sentinel-1A was launched on 25 April 2014 with a C-band synthetic aperture radar (SAR) sensor, which has the significant enhancements in terms of revisit period and high resolution. The Mw 6.1 Napa, California earthquake occurring on 24 August 2014, almost 4 months after the launch, is the first moderate earthquake imaged by the Sentinel-1A. This provides an opportunity to map the coseismic deformation of the event and evaluate the potential of Sentinel-1A SAR for earthquake study. Two techniques including the interferometric SAR (InSAR) and pixel offset-tracking (PO) are, respectively, employed to map the surface deformation along the radar line of sight (LOS), azimuth and slant-range directions. The cross comparison between Sentinel-1A InSAR LOS deformation and GPS observations indicates good agreement with an accuracy of ～2.6?mm. We further estimate the earthquake source model with the external COSMO-SkyMed InSAR and GPS data as constraints, and forward calculate the surface deformation as cross validation with the Sentinel-1A observations. The comparison between the observed and modeled deformation shows that the Sentinel-1A measurement accuracy can achieve 1.6?cm for InSAR technique along LOS direction, and 6.3 and 6.7?cm for PO along azimuth and range directions, respectively.     

Assessment of Nigeriasat-1 satellite data for urban land use/land cover analysis using object-based image analysis in Abuja,Nigeria

This study assesses the usefulness of Nigeriasat-1 satellite data for urban land cover analysis by comparing it with Landsat and SPOT data. The data-sets for Abuja were classified with pixel- and object-based methods. While the pixel-based method was classified with the spectral properties of the images, the object-based approach included an extra layer of land use cadastre data. The classification accuracy results for OBIA show that Landsat 7 ETM, Nigeriasat-1 SLIM and SPOT 5 HRG had overall accuracies of 92, 89 and 96%, respectively, while the classification accuracy for pixel-based classification were 88% for Landsat 7 ETM, 63% for Nigeriasat-1 SLIM and 89% for SPOT 5 HRG. The results indicate that given the right classification tools, the analysis of Nigeriasat-1 data can be compared with Landsat and SPOT data which are widely used for urban land use and land cover analysis.     

一种利用哨兵1号数据提取南极接地线方法

针对因IW工作模式数据在南极地区覆盖不全面导致对南极接地线的全面提取造成影响的问题,提出利用双差干涉测量提取接地线的基本原理,分别利用工作模式为IW和EW的Sentinel-1雷达卫星数据,对东南极毛德皇后地沿岸冰川接地线进行提取,将提取结果分别与MEa-SUREs接地线产品进行对比,同时再将这两种模式下的提取结果进行对比分析。结果表明,双差干涉测量可以去除冰流相位的影响,使用EW工作模式的Sentinel-1数据进行南极接地线提取可以忽略其地面分辨率较低这一缺陷,同时,这一模式的Sentinel-1数据在幅宽、南极覆盖范围等方面更具优势。因此,综合利用IW和EW工作模式的Sentinel-1数据,对南极接地线的全面、高效、长期动态监测具有重要意义。     

Contribution of Landsat 8 data for the estimation of land surface temperature in Batna city,Eastern Algeria

In this study, we presented a mono-window (MW) algorithm for land surface temperature retrieval from Landsat 8 TIRS. MW needs spectral radiance and emissivity of thermal infrared bands as input for deriving LST. The spectral radiance was estimated using band 10, and the surface emissivity value was derived with the help of NDVI and vegetation proportion parameters for which OLI bands 5 and 4 were used. The results in comparison with MODIS (MOD11A1) products indicated that the proposed algorithm is capable of retrieving accurate LST values, with a correlation coefficient of 0.850. The industrial area, public facilities and military area show higher surface temperature (more than 37 °C) in comparison with adjoining areas, while the green spaces in urban areas (34 °C) and forests (29 °C) were the cooler part of the city. These successful results obtained in the study could be used as an efficient method for the environmental impact assessment.     

A new geospatial overlay method for the analysis and visualization of spatial change patterns using object-oriented data modeling concepts

Traditional geographic information system (GIS)-overlay routines usually build on relatively simple data models. Topology is – if at all – calculated on the fly for very specific tasks only. If, for example, a change comparison is conducted between two or more polygon layers, the result leads mostly to a complete and also very complex from–to class intersection. A lot of additional processing steps need to be performed to arrive at aggregated and meaningful results. To overcome this problem a new, automated geospatial overlay method in a topologically enabled (multi-scale) framework is presented. The implementation works with polygon and raster layers and uses a multi-scale vector/raster data model developed in the object-based image analysis software eCognition (Trimble Geospatial Imaging, Munich, Germany). Advantages are the use of the software inherent topological relationships in an object-by-object comparison, addressing some of the basic concepts of object-oriented data modeling such as classification, generalization, and aggregation. Results can easily be aggregated to a change-detection layer; change dependencies and the definition of different change classes are interactively possible through the use of a class hierarchy and its inheritance (parent–child class relationships). Implementation is exemplarily shown for a change comparison of CORINE Land Cover data sets. The result is a flexible and transferable solution which is – if parameterized once – fully automated.