首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到17条相似文献,搜索用时 250 毫秒
1.
将光谱聚类方法应用于高光谱遥感数据处理,对低反射率地物信息的提取取得较好效果;同时采用决策树的多分类器组合方法提取高光谱遥感影像信息,经对比研究发现其效果明显优于单个分类器。  相似文献   

2.
李强  张景发 《地震》2017,37(4):80-92
强地震发生后, 道路是抗震救灾的生命线, 快速有效地提供灾区可通行道路的状况可为地震应急救援力量的部署提供强有力的信息支撑。 基于遥感图像的震害道路识别是遥感地震应急领域中的难点, 但对于地震应急具有无可比拟的价值。 在总结分析地震前后道路影像特征的基础上, 系统地介绍了遥感影像道路提取方法, 之后介绍了遥感震害道路评估工作流程, 重点阐述了遥感震害道路提取与评估方法, 然后综合分析了遥感道路提取在地震应急中的不足, 最后展望了未来遥感技术在震害道路提取与评估中的应用。  相似文献   

3.
高分辨率遥感影像中地物对象的最优分割是遥感图像理解、地物识别的关键问题, 也是有效利用地物空间信息的基础. 针对遥感影像中简单地物具有内部光谱均一和外界光谱差异大的特点, 提出图斑显著性的概念, 并在多尺度分析中的图像分割过程中建立图斑演变的显著性变化曲线, 应用显著性变化曲线的极大值和分割过程中图斑之间的包含关系建立尺度序, 并以此解决图像分割中的简单地物的最优分割问题, 确定可能为地物对象的图斑. 并将此原理和方法应用于高分辨率海岸带遥感影像的图像分割中, 效果明显.  相似文献   

4.
建筑物震害多源遥感特征与机理分析   总被引:2,自引:2,他引:0       下载免费PDF全文
张景发  李强  焦其松 《地震学报》2017,39(2):257-272
随着遥感信息源的不断增加,多种遥感数据被用于详细判读建筑物的震害情况.为准确判读震害等级与建立震害自动识别模式,本文收集整理了汶川地震震区的震害遥感图像,通过目视判读、图像处理、统计分析,重点分析了各类震害建筑物在光学影像中的特征表现、在合成孔径雷达图像中的成像机理特征以及在激光雷达图像中的三维特征.在此基础上构建了建筑物简化模型,并联合光学影像和雷达图像对震害建筑物的影像特征剖面予以分析.结果显示:光学遥感图像色彩信息符合人眼色觉原理,具有较好的直观判读效果;合成孔径雷达图像能够记录地物侧面、表面的粗糙程度和角反射特点,信息量丰富但不直观;激光雷达图像能获取建筑物的三维信息,因此震害评估工作中需有效地综合利用多源遥感数据,才能实现最佳的判识效果.   相似文献   

5.
一种基于综合吸收能力的高光谱遥感植被指数计算方法   总被引:2,自引:0,他引:2  
植被指数一直是遥感技术研究植被的重要方法,当前主要方法多是利用遥感数据中的典型波段进行组合计算.随着高光谱遥感的广泛应用,简单波段组合计算应用于高光谱遥感数据效果并不理想,植被指数计算方法需要在传统方法基础上,充分利用连续光谱曲线优势.文章在借鉴当前主流植被指数计算方法基础上,结合植被的光谱曲线特征,提出了一种基于综合吸收能力的植被指数计算方法(VSAI).具体方法是运用植被光谱曲线在绿、红、红外波段范围内的曲线拐点所形成曲面的形状与面积,与样本之间的相似关系,进行植被存在性与郁闭度评估.结果表明,该方法计算出来的指数能较好的反应植被信息,有较好层次.  相似文献   

6.
基于光谱角匹配预测的高光谱图像无损压缩   总被引:1,自引:0,他引:1  
在地表信息获取方面,高光谱遥感是对地观测技术的主要方法,观测同时产生了海量高光谱图像的存贮与传输问题.研究发现,高光谱图像具有独特的光谱上下文特征,可从光谱维分析高光谱图像的光谱相关性,并用光谱角来度量相邻像素间的光谱相似性的差异,探测水平或垂直光谱边界,由此提出了基于光谱角匹配预测(SAMP)的无损压缩算法.实验表明,SAMP算法的预测效果好于已有文献中提出的一些优秀算法,且具有低复杂性.  相似文献   

7.
马海建  陆楠  李晓璇 《地震》2013,33(2):71-78
重大地震灾害发生以后, 快速准确地提取灾区的道路震害信息对于应急救援工作具有重要意义。 由于地震造成的破坏非常复杂, 没有固定的光谱特征变化模式, 而且影像中存在大量同物异谱和同谱异物现象。 因此, 传统基于光谱特征的遥感影像道路震害提取方法, 不仅提取精度较低, 而且通用性不强, 需要根据不同影像调整参数。 道路边线是一种稳定的道路几何特征, 其特征变化能够准确地表现道路的状态变化。 基于此, 本文研究了一种基于道路边线的震害信息快速提取方法。 该方法利用震后遥感影像提取完好道路边线, 与震前道路线分布数据进行变化检测, 从而实现震害路段的提取。 最后, 利用汶川震区的遥感影像进行实例验证, 与人工解译的结果进行比较。 结果表明, 该方法能够快速准确地提取道路震害信息。  相似文献   

8.
巢湖浮游植物叶绿素含量与反射光谱特征的关系   总被引:79,自引:14,他引:65  
利用高光谱地物光谱仪在巢湖进行了反射光谱测量和同步水质采样分析。在分析巢湖水体反射光谱特征的基础上,通过研究水体光谱反射率与叶绿素浓度之间的关系,利用反射率比值法和一阶微分法分别建立了叶绿素a的遥感定量模型。结果表明反射率比值R705nm/R680nm和690nm反射率的一阶微分均与叶绿素a浓度有较好的相关性,且用反射率比值法估算叶绿素a效果较好。  相似文献   

9.
利用遥感技术进行震害建筑物的自动识别可为震害的快速评估与救灾决策提供科学可靠的依据.本文从震害建筑物在高分辨率遥感影像下灰度的特征入手,以5·12汶川特大地震后都江堰市区ALOS遥感影像为数据源,在MATLAB平台下对影像进行灰度增强处理、数学形态学重构以及连接、填充处理,并结合区域统计特性最后自动识别震害房屋.结果表明,利用ALOS影像丰富的纹理特征及空间结构信息与MATLAB在数学形态学处理中的优势能够准确有效地提取震害建筑物信息.  相似文献   

10.
向导式遥感震害评估系统研制   总被引:1,自引:0,他引:1  
依托国家科技支撑计划重点项目子专题,在总结、归纳已有震害评估系统处理方式、流程及优缺点的前提下,研究了符合实际工作状况的遥感震害评估系统.该系统集成了基于ENVI/IDL、ERDAS开发的影像处理模块,可辅助提取高分辨率遥感影像中房屋倒塌、道路损毁、滑坡、泥石流、堰塞湖等震害信息.尤其是面向对象分类模块,对遥感影像各种特征进行了综合处理.基于ArcEngine开发的空间数据管理与分析模块,可处理道路空间位置分布、地震烈度划分、行政区划及属性等信息.并实现了对各模块向导式的流程化调用,有效提高了震后灾害评估工作的效率.该系统已在地震应急工作中发挥了有力的作用.  相似文献   

11.
张克诚  王晓青  丁香 《中国地震》2023,39(2):367-376
2015年4月25日在尼泊尔廓尔喀县发生的8.1级地震及后续强烈余震,造成尼泊尔北部严重的人员伤亡和财产损失,灾区建筑物倒塌损失严重。本文利用现场震害调查资料和高分卫星遥感影像,开展建筑物震害遥感解译,得到各个遥感解译点的遥感震害指数,结合现场调查点评估的烈度拟合了遥感震害指数-实际震害指数转换关系,再根据遥感震害指数估计了全部解译点的震害指数及地震烈度。估计的烈度与现场调查结果对比显示出较好的一致性,研究结果为该地区今后发生地震提供了可借鉴的遥感评估震害指数转换模型。  相似文献   

12.
After destructive earthquakes, the assessment result of seismic intensity is an important decision-making basis for emergency rescue, recovery and reconstruction. This job requires higher timeliness by government and society. Because remote sensing technology is not affected by the terrible traffic conditions on the ground after the earthquake, large-scale seismic damage information in the earthquake area can be collected in a short time by the remote sensing image. The remote sensing technique plays a more and more important role in rapid acquisition of seismic damage information, emergency rescue decision-making, seismic intensity assessment and other work. On the basis of previous studies, this paper proposes a new method to assess seismic intensity by using remote sensing image, i.e. to interpret the building collapse rate of a residential quarter after an earthquake by high-resolution remote sensing images. If there already are detailed building data and building structure vulnerability matrix data of a residential area, we can calculate the building collapse rate under any intensity values in this residential area by using the theory of earthquake damage prediction. Assuming that the building collapse rate interpreted by remote sensing is equal to the building collapse rate predicted by using the existing data, it will be easy to calculate the actual seismic intensity of the residential area in this earthquake event. Based on this idea, according to the relevant standard specifications issued by China Earthquake Administration, this paper puts forward some functional models, such as the calculation model of building collapse rate based on remote sensing, the data matrix model of residential building structure, the prediction function matrix model of residential building collapse rate and the prediction model of residential building collapse rate. A formula for calculating seismic intensity by using remote sensing interpretation of collapse rate is also proposed. To test and verify the proposed method, this paper takes two neighboring blocks of Jiegu Town after the Yushu M7.1 earthquake in Qinghai Province as an example. The building structure matrix of the study block was constructed by using pre-earthquake 0.6m resolution satellite remote sensing image(QuickBird, acquired on November 6, 2004), post-earthquake 0.2m aerial remote sensing image(acquired by National Bureau of Surveying and Mapping, April 15, 2010) and some field investigation data. The building collapse rate in the two blocks was calculated by using the interpretation results of seismic damage from the Remote Sensing Technology Coordinating Group of China Seismological Bureau. The seismic damage matrix of building structures in Yushu area is constructed by using the abundant scientific data of the scientific investigation team of the project “Comprehensive Scientific Investigation of the Yushu M7.1 Earthquake in Qinghai Province” of China Seismological Bureau. On this basis, the collapse rate prediction function of different structures in Yushu area is constructed. According to the prediction function of collapse rate and the building structure matrix of the two blocks, the building collapse rate under different intensity values is predicted, and the curve of intensity-collapse rate function is drawn. By comparing the building collapse rate interpreted by remote sensing and the intensity-collapse rate function curve of this two blocks, the seismic intensity of both blocks are calculated to be the same value: Ⅸ degree, which is consistent with the results of the field scientific investigation of the earthquake. The validation shows that the method proposed in this paper can effectively avoid the influence caused by the difference of seismic performance of buildings and accurately evaluate seismic intensity when using remote sensing technique. The method has certain application value for earthquake emergency work.  相似文献   

13.
The fast developing remote sensing techniques play an increasingly important role in earthquake emergency response, disaster survey and loss estimation. As there is a lack of quantitative studies on seismic damage based on remote sensing, its practicality in seismic disaster management has usually been questioned. The paper introduces the essential quantitative study idea, the concept of the remote sensing seismic damage index (DRS_I RS) and analysis models, demonstrates the seismic damage indices (DG_IC) of buildings obtained from ground surveying and its quantitative relation to DRS_I RS in Dujiangyan city, Sichuan Province, which was destroyed by the 2008 Wenchuan earthquake with M_S8.0. The primary results show that an obvious relationship exists between the DRS_I RS of buildings obtained from the high resolution satellite or aerial remote sensing images and DG_I C or the building collapse ratio obtained through ground survey, which suggests that the quantitative study on seismic damage based on remote sensing will provide an effective method for seismic damage survey and loss estimation.  相似文献   

14.
基于无人机影像的九寨沟地震建筑物震害定量评估   总被引:1,自引:0,他引:1  
利用2017年8月8日九寨沟7.0级地震震后获取的无人机影像,结合地面震害调查资料,分析各类建筑物震害特征,建立建筑物震害无人机遥感解译标志;选取地震灾区漳扎镇(部分区域)和荷叶寨2个区域作为研究区,进行了无人机遥感建筑物震害提取,基于遥感震害指数进行了震害定量评估,并与现场建筑物震害调查统计结果进行了比较验证。结果显示,遥感解译建筑物震害与实际震害程度相吻合,表明利用震后快速获取的高分辨率无人机影像,可以较为准确地识别建筑物震害,进而为地震灾害定量评估和应急救援辅助决策提供重要参考。  相似文献   

15.
韩召华 《地震工程学报》2020,42(2):552-557,578
利用GIS技术对地震危险等级进行评定时,由于其地形控制点选取合理性较差,导致其所采集遥感图像清晰度较低,地震等级评定不够精准。针对此问题提出一种新的地震灾情遥感信息危险等级在线应急评定方法。利用图像几何校正法,对遥感图像进行分幅裁剪,基于裁剪结果选取地面控制点,提取有价值遥感数据信息,建立遥感解译评估指标。将推导出的综合震灾指数引入到指标中,将各个评价单元的信息进行等级排序和划分,完成地震灾情遥感信息危险等级在线应急评定。仿真实验中,对所提方法和GIS地震危险等级评定方法进行有效性对比测试。实验结果表明,地震灾情遥感信息危险等级在线应急评定方法提升了灾情地形控制点选取的合理性,使获取的遥感图像更清晰,灾情等级评定结果更精准。  相似文献   

16.
The fast processing, seismic damage data extraction and loss evaluation from RS imagery acquired immediately after a destructive earthquake occurs, are important means for compen-sating the insufficiency of seismic damage information from ground-based investigations and provide an important basis for emergency command and rescue. The paper introduces the method of emergency seismic damage assessment using remote sensing data and its application to the great Wenchuan earthquake of magnitude 8.0 occurring in southwest Sichuan Province on May 12, 2008. The practical effectiveness of the method is also evaluated in the paper.  相似文献   

17.
A large number of debris flow disasters (called Seismic debris flows) would occur after an earthquake, which can cause a great amount of damage. UAV low-altitude remote sensing technology has become a means of quickly obtaining disaster information as it has the advantage of convenience and timeliness, but the spectral information of the image is so scarce, making it difficult to accurately detect the information of earthquake debris flow disasters. Based on the above problems, a seismic debris flow detection method based on transfer learning (TL) mechanism is proposed. On the basis of the constructed seismic debris flow disaster database, the features acquired from the training of the convolutional neural network (CNN) are transferred to the disaster information detection of the seismic debris flow. The automatic detection of earthquake debris flow disaster information is then completed, and the results of object-oriented seismic debris flow disaster information detection are compared and analyzed with the detection results supported by transfer learning.  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