四川省芦山“4·20” 7.0级地震公路灾情遥感监测评估

四川省芦山“4·20” 7.0级强烈地震发生后,次生地质灾害造成多处公路损毁,快速、准确地监测公路灾情,是应急救灾一项基础而重要的工作。遥感影像信息提取是获取公路灾情的一种有效途径。利用震后机载航空影像与国产卫星影像,结合交通运输部相关基础数据,对公路灾情开展了监测与评估。在公路周边共发现433处地质灾害点,灾害类型以崩塌为主。其中对公路已造成影响的灾害点197处,损毁公路总长度约10 km。另有潜在危险性较大的灾害点63处,对公路构成严重威胁,需注意加强防范。经实地验证,公路灾情信息提取结果真实可靠。信息提取与分析结果已分别在震后第二天和第三天上报到交通运输部,为高效地组织开展公路抢修保通提供了科学的依据。     

Object-oriented Detection of Landslides based on the Spectral，Spatial and Morphometric Properties of Landslides

Earthquakes in mountain area often induce hundreds of thousands of landslides resulting in destructive casualties and economic damage.It is urgent needed to rapidly detect the extent areas of the landslides.With the advent of very high resolution satellite remote sensing,the application of the object\|oriented classification method in this area have significant advantage comparing to those of visual interpretation and pixel\|based methods.However,the study of object\|oriented landslide detection is relatively few,and the study usually has a small study area.The method of object\|oriented rapid identification of landslides based on the spectral,spatial and morphometric properties of landslides and a 2.5m SPOT5 multi\|spectral image is proposed in this paper and is applied in a relatively large study area.The normalized difference vegetation index (NDVI) threshold was set to remove vegetation objects and obtain landslide candidates.Then,the spectral characteristics,texture,terrain features and context of the image were used to build indicators to gradually separate the landslide from false positives.The small scale chessboard segmentation was conducted to further eliminate vegetation objects and get the landslide objects.The object\|oriented detection results show that the adopted method can recognize about 95% of the landslides in the study area.When considering the landslide excessive detection and omissions,the landslide detection quality percentage of the proposed method is 74.04%.Hence,the method proposed in the article can help to rapid assess landslide disasters caused by earthquakes or heavy rainfalls,providing a reference for post\|disaster emergency relief and reconstruction work.     

基于卫星遥感及数据库同步的气象灾害监测预警系统设计

为缩小预警监测指标与测试指标之间的数值差,实现对气象灾害现象的准确监测,设计基于卫星遥感及数据库同步的气象灾害监测预警系统。在中心站体系内建立自动监测站局域网络,按照实际响应需求,连接影像显示模块与预警、响应模块,完成监测预警系统主站部分的设计。求解遥感影像数据集,根据卫星信息堆叠系数求解结果,定义核函数任务映射表达式,实现基于卫星遥感技术的气象灾害监测信息处理。建立数据库模型,通过分析中间件性能需求的方式,确定监测数据的XML同步处理结果,完成数据库同步中间件的搭建,结合相关设备元件,实现基于卫星遥感及数据库同步的气象灾害监测预警系统设计。实验结果表明,卫星遥感及数据库同步处理技术可以有效控制预警监测指标与测试指标之间的数值差,其最大取值结果不超过0.26,符合精准监测气象灾害现象的应用需求。     

A Object-oriented Landslide Extraction Method based on Morphological Opening Operation

Landslide is one of the most common geological disasters,and it is of great significance to quickly and accurately obtain the hazard degree and distribution of landslide.By introducing the morphological opening operation and the regional level set algorithm to construct the object\|oriented landslide extraction method,and using the multi\|spectral image of GF\|2 satellite as the data source,the landslide extraction experiment is carried out by using the constructed method and the landslide extraction method based on the pixel in the study area of the Bagmati area in Nepal,and the results of the landslide extraction are analyzed.The experimental results show that the object\|oriented landslide extraction method is more accurate than the extraction method based on the pixel,and the anti\|interference ability of the clouds and snows is stronger than that of the pixel\|based landslide extraction method.     

基于遥感卫星资料的台风监测技术研究进展

受到全球气候变暖的影响,台风的年暴发频率及其造成的危害都成上升趋势,中国位于西北太平洋沿岸,已成为世界上少数几个遭受台风影响最严重的国家之一。卫星遥感资料因其覆盖范围广、成像面积大、时间分辨率高,已成为台风灾害损失评估的有效资料。在综合近年来台风监测相关研究的基础上,从常规观测资料、气象卫星遥感资料、微波遥感资料等角度出发,对遥感技术在台风监测中的应用现状进行了详细的论述。同时,也对各种数据资源存在的问题以及优势进行了分析,并提出需要加强开展多源数据融合、台风监测系统建设等方面的研究。     

基于多源卫星遥感的灾害性气象观测数据监测系统设计

灾害性气象的频发不仅给人们的生活带来了极大的影响,而且还危及生态环境的稳定。为减小实测气象数据与真实数据样本之间误差,实现对灾害性气象观测数据的准确监测,设计基于多源卫星遥感的灾害性气象观测数据监测系统。设置温湿度传感器及防辐射罩,按照数据信息传输网络布局形式,将风速风向传感器、雨量传感器、太阳能控制器接入既定模块单元之中,完成监测系统的硬件设计。利用多源卫星遥感技术,定义多源影像空间,通过分解数字卫星图像的方式,确定监测极值点所处位置,并计算相似性度量指标的具体数值,完成基于多源卫星遥感的灾害性气象图像配准处理。根据上位机组网模型,完善WINSOCK控件的连接形式,实现监测系统的执行程序编制,联合相关传感器元件,完成基于多源卫星遥感的灾害性气象观测数据监测系统设计。实验结果表明,多源卫星遥感技术设计系统的湿度测量曲线、气压测量曲线、风速测量曲线与真实气象数据样本之间的误差值均未超过2%,能够准确监测灾害性气象观测数据。     

卫星遥感海冰监测技术在河北省近海海域的应用

卫星遥感技术已成为海冰监测的重要技术手段之一。介绍了应用EOS系列卫星、HY-1B卫星和HJ-1A/B卫星等遥感数据提取河北省近海海域海冰分布、海冰类型、海冰厚度等海冰信息的方法。重点研究了应用HJ-1A/B卫星遥感数据进行海冰分类,及根据海冰类型与厚度的对应关系估算海冰厚度的方法,并以2013年1月17日的卫星遥感数据为例,提取海冰信息,制作相关海冰专题产品。结果表明:利用多种卫星遥感数据进行海冰监测,既可相互补充又能提高监测效率和准确率,制作更精细化的海冰监测产品,为河北海洋管理部门制定防灾减灾措施提供重要依据。     

遥感技术在我国滑坡研究中的应用综述

中国滑坡遥感研究与应用已有30多年的发展历史,作为滑坡调查的主要手段在大型工程建设中的滑坡灾害调查及危险性评价中发挥了重要作用。从4方面阐述了遥感技术在我国滑坡研究中的应用：① 区域滑坡灾害遥感调查;② 大型单体滑坡遥感调查;③ 滑坡灾害遥感监测;④ 遥感应用于滑坡风险评估。随着遥感技术理论的逐步完善和遥感图像空间分辨率、时间分辨率与波谱分辨率的不断提高,遥感技术已成为滑坡灾害调查、动态监测与预警、灾情实时调查与损失评估等工作中不可缺少的重要手段之一。     

图层约束下的点状自然灾害风险地图综合

点状自然灾害现象如地震、滑坡等,由于其特殊性,灾害风险与其周边的地理环境有着复杂的联系和相互作用,孕灾环境对灾情具有放大或缩小的效应,在制图综合过程中,不能只考虑单个灾害点个体,而因将与之相关的各因素综合考虑,从而判定其风险范围。基于此,在地理学与地图学的基础上,从灾害系统的角度考虑,探讨基于图层约束(LC)和模糊推理系统(FIS)相结合的点状现象自动综合的适用性问题,重点阐述基于图层约束理论和FIS算法相结合的滑坡灾害自动综合技术,并以滑坡灾害为例,构建了基于滑坡灾害程度区划、地形坡度、地貌区划、地震长期烈度区划、年暴雨日数、年均降水量等为约束图层的自动综合应用;通过多尺度综合分析结果表明,中国存在三大重点滑坡区:即青藏高原东部斜坡带、黄土高原滑坡区和太行山东麓、巫山、武陵山脉一线滑坡带。本研究为多尺度、多图层约束下的自然灾害风险地图自动综合提供了一种有效途径,同时对不同区域尺度下的灾害风险管理提供了更高效、更准确的决策支持和技术支撑。     

PlantingInformation Extraction of Winter Wheatand Rape based on GF-1 Images

Successive emission of high resolution satellite has created new opportunities for the application of domestic high resolution remote sensing data.In order to explore the feasibility of GF data in the field of small and medium scale crop remote sensing monitoring and to establish a suitable technical system,with Yangzhou as an example,using decision tree model and object oriented classification method to research the feasibilityon crop planting information extraction of GF wide field viewdata.And explore the method to improve the accuracy.The results showed that,sub\|regionpretreatmentcan reduce the adverse effects of crop spatial distribution on the extraction of the planting area.The overall accuracy of winter wheat was 97%,the Kappa coefficient was 0.93;the overall accuracy of rape was 96%,the Kappa coefficient was 0.84.Research shows thatdomestic GF\|1 WFV images can be applied to the crop planting informationextraction,and toprovide an important reference and decision support for adjusting crop spatial and optimizing management of gain producing areas.     

Progress of Chinese Coastal Wetland based on Remote Sensing

Coastal wetlands as a unique ecosystems with high productivity and abundant biology diversity,has many important resource values,ecological values,economic values and scientific research values.Due to the multi\|temporal,multi\|platform,macroscopic,objective,informative,real\|time,highly effective,comparable and so on,so the remote sensing technology has been gradually approved and widely promoted in coastal wetland research in the past three decades.Current status of coastal wetland research based on remote sensing technique in China was systematically discussed from multiple aspects,including remote sensing data sources,theories and methods,and the application of remote sensing technology to Chinese coastal wetland is reviewed from the aspects of coastal wetland resource investigation and management,landscape pattern and dynamic change,ecological environment monitoring,ecosystem quality and service evaluation.This paper also points out some shortcomings existed in Chinese coastal wetland research by remote sensing technology include the spatial and temporal distributions of the study area is uneven and dominated by small and medium scale,lack of interdisciplinary comprehensive research,focus on theoretical research and ignore application intelligent application of remote sensing technology,information sharing ability is poor,the improve of interpretation accuracy is difficulties.Related research prospects should be to carry out such as monitoring and mapping on all scale,strengthen the multidisciplinary collaboration,strengthen the comprehensive and comparative study,establish a unified classification system of coastal wetland based on remote sensing and the national coastal wetland information system,emphasis on the development of new remote sensing technology and fusion of multi\|source data,emphasis on the use of new methods and new models.     

西藏墨脱县甘登乡滑坡遥感应急调查

利用4个类型11个时相的卫星数据，采用“数字滑坡”技术进行处理及解译获取灾害特征信息，基于地学原理进行的动态空间分析认为：最近发生在我国雅鲁藏布江大拐弯下游右岸，西藏甘登乡菊汤蒙的堵江性质为原已存在的一崩滑群的局部复活，为一自然重力侵蚀现象。自2008年汛期以来曾有过3次较大规模的活动堵江，崩滑活动的规模约为500×104m3 。卫星监测表明，菊汤蒙崩塌群正处于活动期，会经常发生堵江。该段河流位于高山峡谷，滑坡坝堵江后可在较短时间冲开，溃坝可能在下游造成一定的灾害，建议作为重大地质灾害卫星监测区域。     

遥感卫星灾害应急监测效能评估指标体系构建

遥感卫星广泛应用于包括防灾减灾在内的多个领域,发挥了巨大的社会效益。自然灾害应急对卫星监测的需求具有针对多时空要素的动态高效多源多维的特点,而卫星的全球化可重访、无国界观测能力与灾害的监测需求高度契合。在研究分析遥感卫星在灾害应急任务中的能力需求和应用模式的基础上,从单项性能、能力指标和应用效能三个层次展开分析,构建遥感卫星灾害应急监测效能评估指标体系,给出主要指标的评估方法,为我国卫星有效用于国内外重大灾害应急监测服务提供有效的评估手段和技术支撑。     

基于COSMOＧSkyMed和SPOTＧ５的城镇洪水淹没信息快速提取研究

洪水是我国最为频繁的自然灾害之一,如何快速准确地获取洪水淹没范围在救灾减灾工作中具有重要意义.目前,卫星遥感技术已广泛应用于洪水信息提取的研究中.不同的遥感数据源在洪水信息提取中各有利弊,综合研究雷达影像和可见光影像的优缺点,建立了基于多源遥感数据的洪水淹没信息快速提取模型.首先,利用灾中第一时间获取的COSMOＧSkyMed雷达影像,采用面向对象的方法提取出洪灾发生时的水域空间信息;其次,利用灾前SPOTＧ５高分辨率光学影像,采用多光谱影像波段运算和决策树分类的思想提取出常态下的水域空间信息;最后,对灾中雷达影像COSMOＧSkyMed提取的水体和灾前光学影像SPOTＧ５提取的水体进行空间差值运算,得到洪水淹没范围信息,并利用洪水当天拍摄的无人机遥感影像对结果进行精度评价.将该模型应用于２０１３年浙江余姚水灾,监测结果表明:在洪水发生后,能够快速获取淹没范围空间信息,并且提取精度达到９３．７％,为洪灾的防治以及抗洪抢险救灾工作提供强有力的技术支撑和基础数据信息.     

矿山环境遥感监测研究进展

矿产资源是人类赖以生存和发展的重要生产资料,开展矿山监测对于矿产资源开发利用和矿区环境保护至关重要。由于具有大范围、多时相和综合性等优势,遥感技术已成为矿山监测的主要手段。针对矿山开发利用状况、地质灾害问题以及生态环境监测与质量评价等需求,系统总结了矿山环境遥感监测所用的数据源、方法和模型。目前遥感监测数据源已趋于多样化并覆盖矿山监测各方面,得益于云计算平台及人工智能技术快速发展,大数据分析和深度学习等方法在矿山环境遥感监测中逐渐发挥重要作用,而多源数据融合、地物智能化提取、三维形变监测和定量反演等是矿山环境遥感监测存在的主要问题与挑战。     

基于高精度低空摄影测量的滑坡灾害监测与预报关键技术研究

采用传统监测与预报技术,受到滑坡区域扩大影响,导致预测精准度较低,针对该问题,提出了基于高精度低空摄影测量的滑坡灾害监测与预报关键技术研究。依据滑坡地质体环境因素,建立滑坡灾害监测与监测与预报指标,根据该指标,计算地层压力变量相关参数。以高分辨率数字遥感设备为传感器,采用高精度低空摄影测量技术来提取数据,以此分析滑坡堆积特征和密实程度。通过上述特性,建立关联函数,确定监测与预报对象以及监测与预报等级,由此完成滑坡灾害监测与预报。由实验结果可知,该技术预测精准度较高,最高可达到98.8%,为保障人们生命安全提供必要技术支持。     

Building Height Estimation from GF-2 Image based on Morphological Shadow Index

GF-2 is a high resolution earth observing satellite with sub\|meter resolution which is developed by our own technique.To estimate urban building height based on GF\|2 remote sensing image combined with the idea of mathematical morphology and object\|oriented classification.First of all,segment image based on multi\|scale segmentation.Then extract shadow and calculate its length based on object\|oriented classification combined with spectral,shape,Morphological Shadow Index (MSI) and other features.In the end,estimate building height based on the geometrical model of satellite,sun and building and then accuracy evaluation and error analysis are carried out by using the field measurement data.Experimental results showed that 90% of the buildings’ absolute error is less than 1 m.This experiment demonstrate that the method can extract the height of urban building from the GF\|2 image effectively and the immense potential of domestic high resolution remote sensing image in applications on urban building information extraction.     

HJ-1A/B星CCD多光谱遥感数据特征评价及应用研究

我国现有的风云系列卫星、资源卫星及海洋卫星都可实现多种性能的对地观测,在灾害与环境监测方面发挥了很好的作用。然而,面对复杂多样的自然灾害及环境问题,这些卫星却都难以完全满足灾害和环境监测与预报所需的空间分辨率、时间分辨率和光谱分辨率以及全天候的要求。主要对环境与灾害监测预报小卫星A、B(HJ-1A/B)星多光谱遥感数据进行了质量评价,提取数据特征,以便为该数据的推广应用提供参考。     

海洋灾害遥感元数据及数据系统设计

提出一个海洋灾害遥感元数据框架,用来对海洋灾害遥感数据进行描述、组织、存储和管理;在此基础上,建立了海洋灾害遥感数据系统,实现了卫星数据及灾害专题产品的网络发布、查询检索和数据获取,为国家灾害应急监测与灾后恢复重建等重大应急任务提供数据交换与数据共享服务。     

Disaster Monitoring of Satellite Image Processing Using Progressive Image Classification

The analysis of remote sensing image areas is needed for climate detection and management, especially for monitoring flood disasters in critical environments and applications. Satellites are mostly used to detect disasters on Earth, and they have advantages in capturing Earth images. Using the control technique, Earth images can be used to obtain detailed terrain information. Since the acquisition of satellite and aerial imagery, this system has been able to detect floods, and with increasing convenience, flood detection has become more desirable in the last few years. In this paper, a Big Data Set-based Progressive Image Classification Algorithm (PICA) system is introduced to implement an image processing technique, detect disasters, and determine results with the help of the PICA, which allows disaster analysis to be extracted more effectively. The PICA is essential to overcoming strong shadows, for proper access to disaster characteristics to false positives by operators, and to false predictions that affect the impact of the disaster. The PICA creates tailoring and adjustments obtained from satellite images before training and post-disaster aerial image data patches. Two types of proposed PICA systems detect disasters faster and more accurately (95.6%).