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1.
遥感图像中地表水体同山体、建筑物等地物产生的阴影在光谱特征上存在较高的类间相似性,导致提取过程中容易出现混淆和错分的情况。针对此问题,提出一种基于面向对象和人工蜂群的地表水体提取方法。该方法首先对遥感图像进行分割以获取分割对象的光谱、比率、几何形状等统计特征,以弥补高分遥感图像波段数目少,信息量不足的缺陷;并借助人工蜂群算法在解决复杂问题最优化方面的优势,选取水体同阴影二值分类的几何平均正确率作为算法的适应度函数,最终获取地表水体的最优化提取规则。选取厦门市大嶝岛和湖南省资兴市部分区域,基于国产高分一号、二号遥感数据进行水体提取,并与传统SVM分类结果进行比较。实验结果表明本算法提取水体的总体精度和Kappa系数均优于传统SVM分类器,表明该方法可应用于高分遥感图像的地表水体提取。 相似文献
2.
为实现对海岸线的动态监管和监测,提出了一种自动阈值与区域增长相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)影像海岸线自动提取方法。首先结合Canny边缘检测和最大类间方差法(OTSU方法)实现自动阈值分割提取水陆分界线; 在自动阈值提取的基础上,对水域进行开运算和图像分割,将占有较大比例的海上水体作为种子点进行区域增长,获取海上水体,从而去除陆地水体、阴影等误分为海域的部分; 之后对区域增长法获取的海陆分割结果进行去噪、填充等形态学优化处理,填补海上船体、风车、岛礁等造成的空洞影像,形成最终的海陆分割结果; 最后,使用Canny边缘检测算子获取海岸线。基于江苏海岸带的实验结果表明该方法可以高精度地提取出光滑、连续的海岸线,在SAR影像海岸线提取中具有较强的实用性。 相似文献
3.
《地壳构造与地壳应力文集》2017,(0)
地震是破坏性最强的自然灾害之一。在震后快速获取震区建筑物损毁的第一手图像资料,标定轻重灾区,对于抗震救灾并尽可能减少人民群众的生命财产损失有非常重要的意义。合成孔径雷达(SAR)具有全天时、全天候的工作特点,基于SAR图像丰富的强度、相位、纹理和极化等信息,进行震前震后变化检测能很好地解决这个问题。本文基于前人研究,总结了SAR图像变化检测的各种方法,系统阐述了国内外学者基于SAR图像强度、相位及多信息融合变化检测提取建筑物震害信息的研究,同时着重就极化信息变化检测及其在震害信息提取的研究进行了总结。 相似文献
4.
以皖南山区秋浦河流域为研究对象,综合利用OLI影像和DEM数据,针对山区水体提取中出现的阴影问题和河流断线问题提出一种新的解决思路。首先通过比较单波段阈值法、NDWI水体指数法、谱间关系法以及SWI阴影水体指数几种水体提取方法,显示SWI能够剔除大部分山体阴影;其次使用基于数学形态的膨胀滤波和Pavlidis图像细化算法对SWI提取结果进行处理,较短水体的断线得到连接;最后对于水体断线严重的上游河流,利用DEM进行河网的提取,并以提取的河网代替水体指数的提取结果。结果表明,基于OLI和DEM数据进行山区水体的提取,方法简单,提取的面状水体齐全,线状水体连续,精度达到83.2%,该方法可为其他山区地形水体提取提供一定的借鉴。 相似文献
5.
《地壳构造与地壳应力文集》2018,(0)
地震是对人类生命和财产威胁最大的自然灾害之一,大地震往往引起大量建筑物倒塌,从而造成大量人员伤亡和财产损失。震后快速准确地评估建筑物损毁情况,有利于合理安排资源进行救援和灾后重建。合成孔径雷达(SAR)遥感凭借其全天时、全天候工作能力,在评估建筑物震害信息中发挥了重要作用。本文将从SAR传感器的发展历程入手,介绍SAR提取建筑物震害信息的方法,并针对各个方法的优缺点和存在的问题,指出可行的解决方案,这有利于根据实际情况选择合理的方法,从而快速准确地获取震害信息。最后展望了SAR图像提取震害建筑物信息的发展趋势。 相似文献
6.
西昆仑山崇测冰川区多源遥感影像的冰川信息提取方法研究 总被引：2，自引：2，他引：0
冰雪独有的性质与特性使得基于遥感影像对其进行信息提取成为可能,如何进行精准的冰雪信息提取是冰雪时空变化研究的关键和基本要求。利用多源遥感影像（TM、IRS-P5和SAR）对西昆仑山崇测冰川区的冰川进行信息提取,采用不同分类方法和数据融合方法,分别针对光学影像和微波影像进行处理,提取冰川信息并进行比较分析。结果表明：面向对象分类方法是最优的冰川信息提取方法;图像融合处理有助于提高冰川信息的提取精度,特别是多光谱和高分辨率图像融合后再分类,提取效果更为理想。 相似文献
7.
《地壳构造与地壳应力文集》2016,(1)
合成孔径雷达(SAR)卫星具有全天候、全天时的特点,为地球空间信息的获取提供了一个有效途径。变化检测技术(change detection)近几年作为极为重要的遥感应用研究手段获得了长足的发展。本文在介绍SAR卫星数据发展现状的基础上,重点介绍了基于SAR图像的变化检测方法及技术流程,并以汶川地震都江堰地区ALOS数据为例,采用差值法和比值法进行震害建筑物分布信息提取,并结合光学影像进行评定。结果证明,传统的变化检测方法对SAR图像的震害信息提取具有较好的效果,能够有效地应用于震害信息的提取与评估中。 相似文献
8.
《地壳构造与地壳应力文集》2016,(0)
合成孔径雷达(SAR)卫星具有全天候、全天时的特点,为地球空间信息的获取提供了一个有效途径。变化检测技术(change detection)近几年作为极为重要的遥感应用研究手段获得了长足的发展。本文在介绍SAR卫星数据发展现状的基础上,重点介绍了基于SAR图像的变化检测方法及技术流程,并以汶川地震都江堰地区ALOS数据为例,采用差值法和比值法进行震害建筑物分布信息提取,并结合光学影像进行评定。结果证明,传统的变化检测方法对SAR图像的震害信息提取具有较好的效果,能够有效地应用于震害信息的提取与评估中。 相似文献
9.
快速全面的获取地震灾情信息对于减少灾害损失、预防次生灾害发生具有重要的意义。遥感技术凭借其快速、大范围、高精度地获取地面信息的特点在震后信息提取中发挥了重要作用。传统光学遥感数据由于受到震后多云雨天气的影响,往往难以获取有效数据。合成孔径雷达(SAR)能够全天候获取数据,已成为震害评估的重要数据源。随着遥感图像向着高分辨率方向发展,数据所包含的信息也越来越丰富,更有利于地震地质灾害调查。本文以2017年九寨沟地震为例,采用高分辨率光学和SAR遥感图像为数据源,从道路震害分析、滑坡次生灾害提取、同震形变场计算等多个角度开展应用研究,对此次地震地质灾害进行调查。结果表明,结合高分辨率光学和SAR遥感影像各自的特点和优势,能够在地震地质灾害信息全面调查中发挥重要作用。 相似文献
10.
机载高分辨率In SAR技术作为一种新的技术手段,被广泛应用于地形测绘、资源调查及灾害监测等方面。机载In SAR影像不同于光学航空摄影,原有的像片调绘方法已不适用于地物的定性和定位。依据机载SAR成像机理,探讨了形状、色调、阴影等SAR影像直观特征对地物空间的对应关系及判读方法,并对地形起伏、地物高度、叠掩、阴影等引起的定位误差进行分析,提出了提高准确定位的措施。在某40km2的外业调绘项目中,其调绘成果经后期实测数据的精度验证,调绘成果定位中误差为0.87m,满足国家规范要求。 相似文献
11.
Bad weather conditions usually limit the acquisition of optical remote sensing images, while all day and all weather synthetic aperture radar (SAR) shows the ability of providing timely remote sensing data for emergency response and rescue works after earthquake. Because SAR is sensitive to the surface changes caused by earthquake, the modified electromagnetic behaviour by geological disasters and the collapse of buildings can be recorded in SAR images as backscattering intensity changes. Absolute radiometric calibration was performed to SAR products to derive backscattering coefficient sigma nought from image digital number (DN). Based on change detection methods, Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data and TerraSAR-X data acquired for the Ms 8.0 Wenchuan earthquake were used to extract earthquake damage information. This study revealed that landslides showed stronger backscattering and barrier lakes showed lower backscattering in post-earthquake 10 m ALOS PALSAR images comparing to pre-earthquake, and collapsed buildings showed lower backscattering compared to un-collapsed buildings in 1 m TerraSAR-X image. Results showed that SAR data with different spatial resolutions are useful for different earthquake damage information extraction: medium spatial resolution SAR data, e.g. 10 m ALOS PALSAR data, were efficient for secondary geological disaster extraction; high-resolution SAR data, e.g. 1 m TerraSAR-X data, with the help of ancillary GIS data or high-resolution optical data, could be used to extract building collapse information in urban areas. This study indicates that SAR remote sensing data can provide earthquake damage information at early emergency stage and assist the field surveying, further damage assessment and post-earthquake reconstruction. 相似文献
12.
Building seismic vulnerability assessment plays an important role in formulating pre-disaster mitigation strategies for developing countries. The occurrence of high-resolution satellite sensors has greatly motivated it by providing a promising approach to obtain building information. However, this also brings a big challenge to the accurate building extraction and its coherent integration with the assessment model. The main objective of this paper is to investigate how to extract building attributes from high-resolution remote sensing imagery using the object-based image analysis (OBIA) method, so as to accurately and conveniently assess building seismic vulnerability by the combination of in situ field data. A general framework for the assessment of building seismic vulnerability is presented, including (1) the extraction of building information using OBIA, (2) building height estimation, and (3) the support vector machine (SVM)-based building seismic vulnerability assessment. Particularly, an integrated solution is proposed that merges the strengths of multiple spatial contextual relationships and some typical image object measures, under the unified framework to improve building information extraction at different scale levels as well as for different interest objects. With the aid of 35 building samples from two powerful earthquakes in China, the cloud-free WorldView-2 images and some building structure parameters from field survey were used to quantity the grades of building seismic vulnerability in Wuhan Optics Valley, China. The results show that all 48 buildings among the study area have been well detected with an overall accuracy of 80.67 % and the mean error of heights estimated from building shadow is less than 2 m. This indicates that the integrated analysis strategy based on OBIA is suitable for extracting the building information from high-resolution remote sensing imagery. Additionally, the assessment results using SVM show that the building seismic vulnerability is statistically significantly related to structure types and building heights. Both the proposed OBIA method and its integration strategy with SVM are easily implemented and provide readily interpretable assessment results for building seismic vulnerability. This reveals that the proposed method has a great potential to assist urban planners for making local disaster mitigation planning through the prioritization of intervention measures, such as the reinforcement of walls and the dismantlement of endangered houses. 相似文献
13.
Fevzi Karsli Mustafa Dihkan Hayrettin Acar Ali Ozturk 《Arabian Journal of Geosciences》2016,9(14):635
Recent developments in the field of remote sensing have introduced new sensor technologies in usage of LiDAR, SAR, and high-resolution optical data. Classification performance is expected to increase through combining these various data sources. The purpose of this study is to develop a new approach for automatic extraction of buildings in urbanized and suburbanized areas. For this purpose, multi-feature extraction process including the spatial, spectral, and textural features were conducted on the very high spatial resolution multispectral aerial images and the LiDAR data set. SVM algorithm was trained by using this multi-feature data, and the classification was performed. After the classification of building and non-building, objects were extracted with high accuracy for the test areas. As a result, it has been proven that multi-features derived from combination of optical and LiDAR data can be successfully applied to solve the problem of automatic detection of buildings by using the proposed approach. 相似文献
14.
Wenzao Shi 《Earth Science Informatics》2016,9(4):497-509
In order to extract buildings using only gray information, this article proposed an approach for recognizing and extracting buildings from panchromatic high-resolution remotely sensed imagery based on shadows and segmentation. First, shadows were detected by potential histogram function. Second, the value of neighborhood total variation for each pixel was calculated, and then binarization and annotation were implemented to generate lable regions whose centroids were used as the seeds of the region growing segmentation, candidate buildings were selected from the segmentation result with the constraint of aspect ratio and rectangularity. At last, shadows were processed with open, dilate and corrode operations respectively, buildings were extracted by computing the adjacency relationship of the processed shadows and candidate buildings, and the building boundaries were fitted with the minimum enclosing rectangle. For verifying the validity of the proposed method, eighteen representative sub-images were chosen from PLEIADES images covering Shenzhen, China. Experimental results show that the average precision and recall of the proposed method are 97.95 % and 79.40 % for the object-based evaluation, and are 98.75 % and 83.16 % for the area-based evaluation respectively, and it has more 10 % and 6 % increase in the overall performance for above two evaluation criterion comparing with two other similar methods. 相似文献
15.
Potential of High-Resolution Satellite Data in the Context of Vulnerability of Buildings 总被引：1，自引：2，他引：1
High-resolution space-borne remote sensing data are investigated for their potential to extract relevant parameters for a
vulnerability analysis of buildings in European countries. For an evaluation of large earthquake scenarios, the number of
parameters in models for vulnerability is reduced to a minimum of relevant information such as the type of building (age,
material, number of storeys) and the geological and spatial context. Building-related parameters can be derived from remote
sensing data either directly (e.g. height) or indirectly based on the recognition of the urban structure type in which the
buildings are located. With the potential of a fully- or semi-automatic inventory of the buildings and their parameters, high-resolution
satellite data and techniques for their processing are a useful supporting tool for the assessment of vulnerability. 相似文献
16.
Extracting building stock information from optical satellite imagery for mapping earthquake exposure and its vulnerability 总被引：2，自引：1，他引：1
The paper focuses on automatic extraction of building stock information for quantifying physical exposure and its vulnerability from High and Very High Resolution (VHR) optical satellite imagery. We use two case studies. In Sana’a (Yemen), we use automatic techniques to extract the building stock as well as building height that is used to characterize its vulnerability. In Port-au-Prince (Haiti)—the area affected by the 2010 earthquake—we map the building stock based on a pre-disaster imagery, and we show the added value of area-based information when added to point-based damage assessment from visual change interpretation of post-disaster aerial images. This paper shows that VHR imagery can be used to locate and quantify the building stock and its height. This paper also shows that damages measured from changes detected from pre- and post-disaster imagery can in principle map and provide vulnerability information related to the structural fragility of the building stock. 相似文献
17.
The continuous improvement of the launched satellites’ spatial and spectral resolutions has brought new challenges for remote sensing image segmentation technology. The traditional supervised methods greatly depend on artificial interpretation and reduce the degree of automation and robustness of image segmentation. Therefore, the article proposes a novel unsupervised multi-scale segmentation method for high-resolution remote sensing images based on automated parameterization and it mainly includes three steps, adaptive selection of scale parameter (SP) based on local area homogeneity index J-value, multi-scale segmentation based on the inter-scales boundaries constraint strategy, and region merging based on multi-features. The article makes experiments by multi-group high-resolution remote sensing images of different launched satellites and compares the proposed method with the well-known commercial software eCognition and a traditional supervised method. The results show that the proposed method can locate the object edges more accurately and extract the object outlines more completely, and needs no human intervention in segmentation process, so it can provide a generic and effective unsupervised solution for high-resolution remote sensing image segmentation. 相似文献
18.
青海湖作为高海拔的内陆湖泊,其表面水体面积多年变化对寒旱区的气候变化和水循环至关重要。为了研究30年来青海湖湖泊面积变化规律,提取了1986—2017年(除去2012年)覆盖青海湖的459景Landsat5/8影像,采用6种常用的水体提取方法分别提取了青海湖表面水体面积,并分析了不同方法的差异,最终分别对Landsat 5 TM和Landsat 8 OLI遥感影像采用改进的归一化差异水体指数(MNDWI)和水体指数2015(WI2015)方法获得1986—2017年青海湖表面水体面积的年变化,并分析其变化趋势。结果表明:1989—2003年青海湖面积减小了175.34km^2,年平均减小率为12.52km^2/a,2003—2017年青海湖面积增加了183.43km^2,年平均增加率为13.10km^2/a,整体上,1986—2017年青海湖面积增加了104.46km^2,年平均增加率为3.37km^2/a。 相似文献
19.
Building collapse is a significant cause of earthquake-related casualties; therefore, the rapid assessment of buildings damage is important for emergency management and rescue. Airborne light detection and ranging(Li DAR) can acquire point cloud data in combination with height values, which in turn provides detailed information on building damage. However, the most previous approaches have used optical images and LiDAR data, or pre- and post-earthquake LiDAR data, to derive building damage information. This study applied surface normal algorithms to extract the degree of building damage. In this method, the angle between the surface normal and zenith(θ) is used to identify damaged parts of a building, while the ratio of the standard deviation to the mean absolute deviation(σ/δ) of θ is used to obtain the degree of building damage. Quantitative analysis of 85 individual buildings with different roof types(i.e., flat top or pitched roofs) was conducted, and the results confirm that post-earthquake single LiDAR data are not affected by roof shape. Furthermore, the results confirm that θ is correlated to building damage, and that σ/δ represents an effective index to identify the degree of building damage. 相似文献
20.
The situation after earthquake disasters is for a large part of the deployed field units very exceptional. Expert and information systems offer the possibility to support the decisions of the field personnel in such complex and unfamiliar situations. They can be used for training purposes and to support the operations in real cases. Two different expert and information systems were created. The first system supports the onsite search and rescue (SAR) personnel at building collapses and the second supports inspectors evaluating the buildings' states after earthquakes. In both cases, after the input of information related to a certain situation, the expert system poses context-sensitive subsequent questions and gives assistance for the site inspection. The expert and information system for rescue operations then generates advice concerning suitable SAR procedures and equipment for the given situation. Additionally, basic information, checklists and calculation components are offered as support. The expert and information system for the buildings’ state evaluation will assist the inspectors to decide reliably and in short time whether the buildings are safe to be further used or not after an earthquake. Interactive checklists depending on the building type as well as further auxiliary material will support the inspectors in classifying the buildings. Both systems are part of the also developed Disaster Management Tool (DMT). The presentation will include an overview of the knowledge collection and evaluation process, the development stage of both expert and information systems, their integration into the DMT and their use when coping with an earthquake disaster. 相似文献