地面建筑物破坏状态检测的多类互信息量评估—震灾前光学图像与震灾后SAR图像的融合

利用震前可具备的光学图像与震后卫星SAR图像的信息融合,可检测与评估震灾区地表面建筑物破坏状态。本文根据震前光学图像的建筑物特征参数,通过SAR成像仿真算法,模拟各建筑物SAR图像,根据震后SAR真实图像与SAR仿真图像互信息量的比较,综合利用归一化互信息量、梯度互信息量、区域互信息量及检测与评估建筑物破坏状态。采用2010年海地地震灾前的IKONOS光学图像、灾后COSMO-SkyMed与RADARSAT-2的星载SAR图像,进行震后建筑物破坏状态检测与评估。其结果与震后GeoEye光学图像进行了验证,证明了本文方法的可行性。     

加入空间-时相纹理的高分辨率图像城市建筑物物倒塌提取

将两种基于地统计学的纹理特征加入到高分辨率遥感影像的城市建筑物倒塌探测中,考察了多尺度纹理对探测结果的影响.采用基于单类支持向量机的多时相直接分类方法提取建筑物倒塌信息.以伊朗巴姆地区2003 年12 月地震前后的Quickbird 遥感影像为数据源,评价和验证了本文方法的有效性.研究表明,将多尺度的空间和时相纹理信息加入到高分辨率遥感影像的倒塌建筑物探测中,可以有效提高分类精度,该方法得到的结果可应用于灾害救援及评估.     

利用多尺度Hough变换提取高分辨率SAR图像建筑物L型结构

提出了一种利用多尺度Hough变换从高分辨率SAR图像提取建筑物L型结构的方法。针对高分辨率SAR图像建筑物L型结构的特点,建立了建筑物L型结构简化几何模型,并采用从粗到精的思路利用多尺度Hough变换提取建筑物L型结构方向线。并提出了一种L型结构组合度函数对提取直线进行编组,确定建筑物L型结构的方向和拐点。最后,采用基于扫描线的方法计算L型结构线宽,得到完整规则的建筑物L型结构。多幅真实机载高分辨率SAR图像实验结果表明,本方法可以有效地提取高分辨率SAR图像建筑物L型结构,提取结果与实际位置吻合较好。     

汶川地震粮食受损遥感快速估算与分析

综合利用灾前IRS P6 Liss-4高分辨率数据与灾后的航空影像, 估算粮食受损面积, 并利用同期农业气象数据估算了不同受灾区域粮食作物单产水平, 最终估算得出震区粮食作物受损产量。监测结果表明: 地震造成的12个重灾县市冬小麦直接损失247.1hm2, 产量约为1013778kg, 直接影响不大。但受灾地区冬小麦总产量超过22万t, 而且对秋粮作物的种植和生产造成影响, 对中国粮食生产的间接影响不容忽视。     

A New Neuro-Fuzzy Approach for Post-earthquake Road Damage Assessment Using GA and SVM Classification from QuickBird Satellite Images

Tracking damaged roads and damage level assessment after earthquake is vital in finding optimal paths and conducting rescue missions. In this study, a new approach is proposed for the semi-automatic detection and assessment of damaged roads in urban areas using pre-event vector map and both pre and post-earthquake QuickBird images. In this research, damage is defined as debris of damaged buildings, presence of parked cars and collapsed limbs of trees on the road surface. Various texture and spectral features are considered and a genetic algorithm is used to find the optimal features. Subsequently, a support vector machine classification is applied to the optimal features to detect damages. The proposed method was tested on QuickBird pan-sharpened images from the Bam earthquake and the results indicate that an overall accuracy of 93% and a kappa coefficient of 0.91 were achieved for the damage detection step. Finally, an appropriate fuzzy inference system (FIS) and also an “Adaptive Neuro-Fuzzy Inference System” are proposed for the road damage level assessment. These results show that ANFIS has achieved overall accuracy of 94% in comparison with 88% of FIS. The obtained results indicate the efficiency and accuracy of the Neuro-Fuzzy systems for road damage assessment.     

Limitations of high resolution satellite stereo imagery for estimating canopy height in Australian tropical savannas

Obtaining reliable measures of tree canopy height across large areas is a central element of forest inventory and carbon accounting. Recent years have seen an increased emphasis on the use of active sensors like Radar and airborne LiDAR (light detection and scanning) systems to estimate various 3D characteristics of canopy and crown structure that can be used as predictors of biomass. However, airborne LiDAR data are expensive to acquire, and not often readily available across large remote landscapes. In this study, we evaluated the potential of stereo imagery from commercially available Very High Resolution (VHR) satellites as an alternative for estimating canopy height variables in Australian tropical savannas, using a semi-global dense matching (SGM) image-based technique. We assessed and compared the completeness and vertical accuracy of extracted canopy height models (CHMs) from GeoEye 1 and WorldView 1 VHR satellite stereo pairs and summarised the factors influencing image matching effectiveness and quality.Our results showed that stereo dense matching using the SGM technique severely underestimates tree presence and canopy height. The highest tree detection rates were achieved by using the near-infrared (NIR) band of GE1 (8–9%). WV1-GE1 cross-satellite (mixed) models did not improve the quality of extracted canopy heights. We consider these poor detection rates and height retrievals to result from: i) the clumping crown structure of the dominant Eucalyptus spp.; ii) their vertically oriented leaves (affecting the bidirectional reflectance distribution function); iii) image band radiometry and iv) wind induced crown movement affecting stereo-pair point matching. Our detailed analyses suggest that current commercially available VHR satellite data (0.5 m resolution) are not well suited to estimating canopy height variables, and therefore above ground biomass (AGB), in Eucalyptus dominated north Australian tropical savanna woodlands.     

相干变化指数法在震害快速评估中的应用

合成孔径雷达(SAR)具有全天候全天时的特点,为快速展开地震救援,评估震害损失提供了重要的数据支持。本文基于汶川震中东南平原地区的ENVISATASAR影像,利用相位干涉方法处理得到相干变化指数图像,对6个评估区域的像元相干变化指数进行统计分析,以相干变化指数平均值作为区分建筑物基本完好与损毁的阈值,并与实地调查结果相比,精度基本达到70%。验证干涉相干变化指数法对震害快速评估有效的同时,也为震区提供震害救援的依据。     

Coseismic fault rupture detection and slip measurement by ASAR precise correlation using coherence maximization: application to a north-south blind fault in the vicinity of Bam (Iran)

Using the phase differences between satellite radar images recorded before and after an earthquake, interferometry allows mapping the projection along the line of sight (LOS) of the ground displacement. Acquisitions along multiple LOS theoretically allow deriving the complete deformation vector; however, due to the orbit inclination of current radar satellites, precision is poor in the north-south direction. Moreover, large deformation gradients (e.g., fault ruptures) prevent phase identification and unwrapping and cannot be measured directly by interferometry. Subpixel correlation techniques using the amplitude of the radar images allow measuring such gradients, both in slant-range and in azimuth. In this letter, we use a correlation technique based on the maximization of coherence for a radar pair in interferometric conditions, using the complex nature of the data. In the case of highly coherent areas, this technique allows estimating the relative distortion between images. Applied to ASAR images acquired before and after the December 26, 2003 Bam earthquake (Iran), we show that the near-field information retrieved by this technique is useful to constrain geophysical models. In particular, we confirm that the major gradients of ground displacement do not occur across the known fault scarp but approximately 3 km west of it, and we also estimate directly the amplitude of right lateral slip, while retrieving this value from interferometry requires passing through the use of a model for the earthquake fault and slip.     

利用“天地图”设计和研发建筑物震害风险信息平台

基于“天地图”API技术和地震灾害风险评估模型,以宁波市为例,建设建筑物震害风险信息发布系统平台。该平台实现了单体建筑物抗震等级和避难场所等地震信息查询、不同烈度下建筑物毁损程度预估、建筑物经济损失和人员伤亡评估及地震科普等功能,能够提供更加直观准确的辅助决策信息来帮助降低建筑物毁损和人员伤亡。     

A laser scanning-based method for fast estimation of seismic-induced building deformations

Monitoring damaged buildings in an area where an earthquake has occurred requires the use of techniques which provide rapid and safe measurements even in emergency conditions. In particular, remote sensing techniques like terrestrial laser scanning (TLS) can satisfy these requirements, since they produce very dense point clouds in little time and also allow an accurate geometric modeling of observed buildings. Nevertheless, strong constraints on TLS data acquisition geometry, such as acquisition distance and incidence angles, typically characterize an area in seismic emergency conditions. In order to correctly interpret the data, it is necessary to estimate errors affecting TLS measurements in these critical conditions. A reliable estimation can be achieved by means of experiments and numerical simulations aimed at quantifying a realistic noise level, with emphasis on reduction of artifacts due to data acquisition, registration and modeling. This paper proposes a data analysis strategy in which TLS-based morphological maps computed as point-to-primitive differences are created. The method can be easily used for accurate surveying in emergency conditions. In order to demonstrate the proposed method in very diverse situations, it was applied to rapidly detect deformation traces in the San Giacomo Roncole Campanile (Modena), the Asinelli tower (Bologna) and the Cantalovo Church (Verona), three buildings damaged by the Mw 5.9 Emilia Romagna 2012 earthquake (Italy).     

一种基于稀疏表示模型的壁画修复算法

古代壁画受保存时间、保存环境、保护技术等限制,无法避免地承受着如褪色、脱落甚至大面积起甲等损害。传统人力手工修复技术存在操作不可逆的问题,因此数字图像修复技术被广泛用于虚拟修复中。提出了一种线描图指引下基于稀疏表示模型的壁画修复算法。首先,利用人机交互的方式将破损壁画中缺失的结构信息根据对应的线描图补全;之后,通过对待修复块的分类,定义了一种先纹理后结构的全新修复策略;接着,运用结构复杂度排序和全局随机抽取策略分别提高修复的准确性和效率;最后,利用稀疏表示模型求解候选块的线性组合去填充待修复区域。实验结果表明,所提算法对敦煌壁画破损图像修复具有较好效果。     

Enhanced change detection index for disaster response,recovery assessment and monitoring of buildings and critical facilities—A case study for Muzzaffarabad,Pakistan

The availability of Very High Resolution (VHR) optical sensors and a growing image archive that is frequently updated, allows the use of change detection in post-disaster recovery and monitoring for robust and rapid results. The proposed semi-automated GIS object-based method uses readily available pre-disaster GIS data and adds existing knowledge into the processing to enhance change detection. It also allows targeting specific types of changes pertaining to similar man-made objects such as buildings and critical facilities. The change detection method is based on pre/post normalized index, gradient of intensity, texture and edge similarity filters within the object and a set of training data. More emphasis is put on the building edges to capture the structural damage in quantifying change after disaster. Once the change is quantified, based on training data, the method can be used automatically to detect change in order to observe recovery over time in potentially large areas. Analysis over time can also contribute to obtaining a full picture of the recovery and development after disaster, thereby giving managers a better understanding of productive management and recovery practices. The recovery and monitoring can be analyzed using the index in zones extending from to epicentre of disaster or administrative boundaries over time.     

地震损毁建筑物的高分辨率SAR图像模拟与分析

为了分析汶川地震震后高分辨率合成孔径(SAR)图像的城区建筑物特征,基于实际获取的机载X波段SAR图像,采用电磁模拟方法进行分析和研究.通过对城区的完整建筑和毁损建筑进行三维建模,采用射线跟踪的电磁计算方法和图像域积分的成像模拟方法得到不同受灾程度的建筑物SAR模拟图像.与真实SAR图像对比分析,提出的算法能够分析建筑物结构变化对SAR图像的影响,模拟主要的强散射点,能有效辅助SAR图像进行城区特征分析.     

Use of shadows for detection of earthquake-induced collapsed buildings in high-resolution satellite imagery

In this paper, we present a hybrid shadow-analysis approach that integrates the model- and property-based methods for detecting collapsed buildings after an earthquake using high-resolution satellite imagery. The framework of the proposed approach has four main steps. (1) The three-dimensional (3D) building model is established according to its footprint and height data stored in a geographical information system. (2) The theoretical shadow area of the building at the time that the post-seismic image was acquired is calculated. And the polygon of the ground shadow area of the building, which is called the theoretical ground shadow polygon, is extracted. (3) The theoretical ground shadow polygon is overlaid with the casting shadow area of the building, which is called the actual shadow area in the post-seismic satellite image, and the mean value of the digital number values of the post-seismic image pixels within the polygon of the theoretical shadow area is calculated. (4) The calculated mean value is compared with predefined thresholds, which are determined by the training pixels collected from the different types of shadows. On this basis, the shadows of totally collapsed, partially collapsed and uncollapsed buildings can be distinguished. A comprehensive experiment for Dujiangyan city, one of the urban areas most severely damaged in the May 2008 Wenchuan Earthquake, was conducted, and the experimental results showed the superiority of the proposed approach to the other existing ones.     

5·12地震灾区生态环境变化研究

针对5·12地震及快速灾后重建带来的生态环境变化,基于不同时相的遥感影像数据,构建研究区(北川县)生态环境综合评价体系结构,并提取相关变化信息,最终得出生态环境质量等级图。结果表明:地震及其次生灾害和灾后重建等使得北川县特别是东南部老县城附近地区、新县城重建地区生态环境受到一定程度的破坏,造成该地区环境质量的下降。     

汶川地震灾后农田和森林植被恢复遥感监测

2008年汶川8.0级特大地震对当地的生态系统造成了极大的破坏,为了评估5年来灾区农田和森林植被的恢复情况,利用逐年机载高分辨率遥感影像,结合星载遥感数据和地面调查数据,开展了灾区农林植被恢复状况监测。在农田恢复监测方面,结合2008年地震发生后以及2013年5月中旬的机载高分辨率遥感数据,采用目视解译的方式对汶川地震中受损农田的恢复状况进行监测与评估,同时利用GVG(GPS、Video和GIS)农情采样系统的作物种植成数调查结果,分析了灾后作物种植结构的变化。结果表明,灾区1592 ha受损农田,5年后仅有约17.5%得到了恢复和耕种使用。就耕地利用强度而言,重灾区耕地利用率较高,作物种植结构没有发生重大变化。在森林恢复状况监测方面,对典型区(岷江干旱河谷区和盆周山地区的3个重点区域)采用目视解译方式识别出森林变化,并结合大区域尺度规一化植被指数(NDVI)时间序列变化分析,对整个灾区的森林损毁和恢复情况做出评价。监测结果显示,汶川县、什邡市和绵竹市的森林植被恢复情况总体较好,但是一些坡度较大的损毁区、次生灾害频发区的森林尚未恢复,大区域尺度的统计结果显示,地震重灾区的46381 ha重度损毁森林植被和177025 ha中度损毁森林植被区域,完全恢复的区域占13.52%和25.84%,部分恢复的区域都占到50%。在自然恢复较为困难的区域,如汶川县中部和东北部、都江堰市北部、彭州市北部、什邡市北部、绵竹市北部、安县北部及北川县南部等,需要加强人工干预。遥感监测方法既适用于震后的农田和森林恢复状况动态监测,也适用于其他自然灾害发生时对灾区农田和森林植被破坏状况进行应急监测,具有实际应用价值和良好的发展前景。     

A Bayesian characterization of urban land use configurations from VHR remote sensing images

The composition and arrangement of spatial entities, i.e., land cover objects, play a key role in distinguishing land use types from very high resolution (VHR) remote sensing images, in particular in urban environments. This paper presents a new method to characterize the spatial arrangement for urban land use extraction using VHR images. We derive an adjacency unit matrix to represent the spatial arrangement of land cover objects obtained from a VHR image, and use a graph convolutional network to quantify the spatial arrangement by extracting hidden features from adjacency unit matrices. The distribution of the spatial arrangement variables, i.e., hidden features, and the spatial composition variables, i.e., widely used land use indicators, are then estimated. We use a Bayesian method to integrate the variables of spatial arrangement and composition for urban land use extraction. Experiments were conducted using three VHR images acquired in two urban areas: a Pleiades image in Wuhan in 2013, a Superview image in Wuhan in 2019, and a GeoEye image in Oklahoma City in 2012. Our results show that the proposed method provides an effective means to characterize the spatial arrangement of land cover objects, and produces urban land use extractions with overall accuracies (i.e., 86% and 93%) higher than existing methods (i.e., 83% and 88%) that use spatial arrangement information based on building types on the Pleiades and GeoEye datasets. Moreover, it is unnecessary to further categorize the dominant land cover type into finer types for the characterization of spatial arrangement. We conclude that the proposed method has a high potential for the characterization of urban structure using different VHR images, and for the extraction of urban land use in different urban areas.     

图割能量驱动的高分辨率遥感影像震害损毁建筑物检测

为充分利用高分辨率遥感影像提供的细节信息,提高震害损毁建筑物检测精度,提出了一种图割框架下融合形状、边缘、角点等多种类型特征的损毁建筑物检测方法。该方法首先利用震前建筑物线划图提取包含单个建筑物的局部影像,用于图割能量函数建模,并分别根据建筑物的位置、形状、边缘以及角点构造能量函数的各约束项。在此基础上,通过最大流/最小割算法求解能量函数最小值,依据最小割能量进行地震前后局部影像中建筑物的相似性度量。最后利用最大期望算法(expectation maximization,EM)求得最小割能量的分类阈值,并根据错分率估值执行后处理以获得最终变化检测结果。采用2011年3月11日东日本大地震前后石卷港的高分辨率遥感影像进行试验,结果表明本文提出的方法能有效检测出损毁建筑物。     

A comparative study of the segmentation of weighted aggregation and multiresolution segmentation

Multiresolution segmentation (MRS) algorithm has been widely used to handle very-high-resolution (VHR) remote sensing images in the past decades. Unfortunately, segmentation quality is limited by the dependency of parameter selection on users’ experience and diverse images. Contrarily, the segmentation by weighted aggregation (SWA) can partly overcome the above limitations and produce an optimal segmentation for maximizing the homogeneity within segments and the heterogeneity across segments. However, SWA is solely tested and justified with digital photos in computer vision field instead of VHR images. This study aims at evaluating SWA performance on VHR imagery. First, multiscale spectral, shape, and texture features are defined to measure homogeneity of image objects for segmentation. Second, SWA is implemented to handle QuickBird, unmanned aerial vehicle (UAV), and GF-1 VHR images and further compared with MRS in eCognition software to demonstrate the applicability of SWA to diverse images in building, vegetation and water, forest stands, farmland, and mountain areas. Third, the results are fully evaluated with quantitative measurements on segmented objects and classification-based accuracy assessment on geographic information system vector data. The results indicate that SWA can produce higher quality segmentations, need fewer parameters and manual interventions, create fewer segmentation levels, incorporate more features, and obtain larger classification accuracy than MRS.     

Satellite-based damage mapping following the 2006 Indonesia earthquake—How accurate was it?

The Yogyakarta area in Indonesia suffered a devastating earthquake on 27 May 2006. There was an immediate international response, and the International Charter “Space and Major Disasters” was activated, leading to a rapid production of image-based damage maps and other assistance. Most of the acquired images were processed by UNOSAT and DLR-ZKI, while substantial damage mapping also occurred on the ground. This paper assesses the accuracy and completeness of the damage maps produced based on Charter data, using ground damage information collected during an extensive survey by Yogyakarta's Gadjah Mada University in the weeks following the earthquake and that has recently become available. More than 54,000 buildings or their remains were surveyed, resulting in an exceptional validation database. The UNOSAT damage maps outlining clusters of severe damage are very accurate, while earlier, more detailed results underestimated damage and missed larger areas. Damage maps produced by DLR-ZKI, using a damage-grid approach, were found to underestimate the extent and severity of the devastation. Both mapping results also suffer from limited image coverage and extensive cloud contamination. The ground mapping gives a more accurate picture of the extent of the damage, but also illustrates the challenge of mapping a vast area. The paper concludes with a discussion on ways to improve Charter-based damage maps by integration of local knowledge, and to create a wider impact through generation of customised mapping products using web map services.