地形因素对航空面阵CCD影像的影响分析与评价   总被引：1，自引：0，他引：1  

卫征  刘学  张兵 《国土资源遥感》2008,(1):27-30

地形因素,包括地面起伏和地球曲率,是造成航空数字遥感影像变形的主要原因之一.本文以中国科学院遥感所自行研发的多模态航空CCD相机系统为对象,结合其成像模式和几何形态,分析了地形因素给影像带来的变形,推导出航空面阵CCD影像变形的一般公式,并通过概算进行了定量评价,得出了对于航空面阵CCD影像,要想得到高精度的几何处理,必须改正地球曲率影响的结论.  相似文献   

风沙地区遥感图像分析及其对选线的意义   总被引：1，自引：0，他引：1  

卓宝熙 《国土资源遥感》2003,14(4):1-5

简要叙述了利用遥感图像进行沙丘研究的优越性,重点介绍了沙漠地区各种类型沙丘的影像特征,并以其形态特征分析为依据,对某些类型沙丘的成因提出了看法,同时指出遥感图像沙丘判释对线路选线的意义及风沙与铁路、公路选线的关系等。  相似文献   

时间域航空电磁法一维正演研究   总被引：15，自引：6，他引：15       下载免费PDF全文

罗延钟  张胜业  王卫平 《地球物理学报》2003,46(5):719-724

基于电磁勘探理论，导出了层状大地条件下时间域航空电磁法（偶极-偶极装置）的正演计算公式和算法，编制了相应的计算机程序，对若干典型地电断面作了正演计算. 计算结果说明时间域航空电磁法的探测能力和探测条件，进而为时间域直升机航空电磁系统的设计方案提供了依据.  相似文献   

Sequence of faulting and deformation during the 2000 eruptions of the Usu Volcano, Hokkaido, Japan—interpretation and image analyses of aerial photographs     

Hiromitsu Yamagishi  Tsukasa Watanabe  Fumiaki Yamazaki 《Geomorphology》2004,57(3-4):353-365

Significant faulting and deformation of the ground surface has been rarely known during volcanic eruptions. Usu Volcano, Hokkaido, Japan, is a unique example of deformation due to felsic magma intrusion. Usu Volcano has a history of such types of eruptions as phreatic, pumice eruption (Plinian type), pyroclastic flowing and lava doming since 1663. On March 31, 2000, phreatomagmatic to phreatic eruptions took place after 23 years of dormancy in the western piedmont, followed by explosions on the western flank of Usu Volcano. They were associated with significant deformation including faulting and uplift. The eruptions and deformation were continuing up to the end of May 2000.We identified the faulting using total nine sets of aerial photographs taken from before the eruption (March 31, 2000) to more than 1 year (April 27, 2001) after the end of the activity, and traced deformation processes through image processing using aerial photographs. We found that some of the new faults and the associated phreatic eruptions were related to old faults formed during the 1977–1981 eruptive episode.The image processing has revealed that the surface deformation is coincident with the area of faulting forming small grabens and the phreatic explosion vents. However, the faulting and main explosive eruptions did not take place in the highest uplift area, but along the margin. This suggests that the faulting and explosive activities were affected by small feeder channels diverging from the main magma body which caused the highest uplift.  相似文献   

UCD航摄像片在大比例尺地形图中的应用   总被引：2，自引：0，他引：2  

孙粉霞  邹学忠 《现代测绘》2009,32(4):41-41,48

本文阐述了UCD数码航摄相机的原理、功能及优点,结合在生产中的应用实践,分析了UCD数码航摄像片的成图精度.  相似文献   

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis     

Ali Almagbile 《地球空间信息科学学报》2019,22(1):23-34

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.  相似文献   

基于无人机摄影测量的增减挂钩耕地指标检查与评价方法     

李运健  陈玉鑫  初爱萍 《北京测绘》2020,(3):395-398

土地增减挂钩项目的质量检查的传统流程需到实地逐一核实,检查周期长。本文提出一种基于无人机航摄的检查技术流程,结合研发的野外实地调绘软件系统,提出一种新型的基于无人机航摄的增减挂钩项目质量检查流程,并基于DOM检查构建指标评价体系。流程优化了传统外业检查流程,实现地块的全覆盖内业检查和外业的实时取证,确保成果耕地质量指标的准确性,对土地增减挂钩项目给予客观评价。评价体系的应用选取广西几个县增减挂钩为研究对象,探究体系评价的合理性,初步确定该方法基本可行。  相似文献   

无人机航测技术在广东省和平县第三次全国国土调查中的应用     

张建辉 《北京测绘》2020,(4):511-513

第三次全国国土调查是查实查清我国国土资源利用现状的重要手段,对提高国土资源利用效率和建设信息化社会有着积极的推动作用。本文以广东省和平县第三次国土调查项目为基础,将无人机航测技术应用于本次三调中,快速的获取了调查区高分辨率的航拍影像数据,结合GNSS技术等进行外业核查和补绘,生产出了符合三调精度要求的DOM、DEM产品,对编制各类工作底图奠定了基础。实践证明,将无人机航测技术应用第三次全国国土调查中具有明显的优势,主要体现在精度高、效率快、成本低、利用率高等方面。  相似文献   

基于深度学习理论的无人机影像分类     

阳成 《北京测绘》2020,(4):481-484

针对无人机影像深度学习分类方法缺乏现状,本文利用深度学习理论卷积神经网络方法对无人机影像进行了分类。该法首先抽取无人机影像作为训练集和检验集,然后建立一个2个卷积层-池化层的卷积神经网络模型进行深度学习,通过设定参数并运行模型实现无人机影像分类。实验表明,本文提出的方法可完成较复杂地区无人机影像分类,其分类精度与支持向量机方法相当,为无人机遥感影像分类提供了一个崭新的技术视点。  相似文献   

无人机大比例尺测图像控点布设方案设计     

袁德宝  张新新  周振青  任兴达 《北京测绘》2020,(4):523-527

随着无人机技术的快速发展,无人机航空摄影测量的精度也大大改善,以无人机为平台低空摄影测量大比例尺地图成为可能。本文以旋翼无人机搭载非测量型相机,通过布设不同数量像控点进行分析和研究,得到无人机摄影测量在农村地区像控点布设规律。结果证明在合理像控点布设的情况下,无人机测图数字成果空中三角测量、平面和高程精度均可满足1∶500、1∶1000、1∶2000大比例尺地形测图的精度要求。  相似文献