Research on a Watermarking Algorithm for Remote Sensing Images Resist Screen Capture Attacks in Urban Planning Information Management

Remote Sensing data, as an essential urban basic information in urban planning, has the characteristics of large information capacity, real time, high update speed and accuracy. Because of urban spatial information involving multi-faceted public and public interests, its data security is very important. The use of digital watermarking technology can effectively protect the secu-rity of urban planning basic data. In practical applications, the “screen capture” poses a great threat to the security of remote sensing image. In order to resist the screen capture attacks, the QR code watermark information is encoded and converted, and combined with a circular angle template watermark, a digital watermarking algorithm for remote sensing images in urban planning information management is proposed. And the proposed algorithm is experimentally verified. Experiments show that the algorithm is robust against screen capture attacks, and provide security guarantee for urban construction and management.

Photogrammetry - Remote Sensing on the Study of Monuments and Historical Centers： The Effect of Hazards -The Case of Delphi Historical Center

Monuments and historical centers, because of their particular importance, are studied in multiple ways. The study concerns different scientific disciplines and technology. Photogrammetry and remote sensing contribute essentially to this study, because of the valuable qualitative and quantitative information they offer. In this paper we search through the possibilities of very high resolution satellite imagery on historical centers study, referring to Delphi historical center. The study concerns image enhancement techniques and visual interpretation of Ikonos satellite imagery. Image enhancement techniques facilitate visual interpretation, detection and recognition, of the physiognomy and spatial arrangement of Delphi historical center and offer information about physical and architectural features in the wide area of the historical center.

MAPPING OF OPHIOLITES IN THE INDUS-SUTURE ZONE OF NORTHWESTERN HIMALAYA, USING SATELLITE REMOTE SENSING DATA

Ophiolites, which have been tectonically emplaced along continental margins and island arcs, are significant to the understanding of mountain belt evolution. In the Himalayas, the ophiolitic suite of rocks occur along the Indussuture zone from Hanle in the southeast to Dras\|Kargil sector in the northwest and it represents the remnant of the compressed uplifted wedge of the oceanic crust between the two colliding continental masses, the Indian and the Asian plates.. These ophiolites are temporally and spatially correlated with the culminating phase of the Himalayan orogeny. The Indus River flows to its north separating the ophiolite from the Trans Himalayan litho\|units. Geological mapping in the hostile and inaccessible mountainous terrains of the Himalaya has always posed a great challenge to geologists. Nevertheless, a number of geologists have undertaken such arduous mapping expeditions in the past and prepared fairly good geological maps of these terrains .However there always existed disputes on the accuracy of lithological boundaries and structural details in these maps because many of these boundaries and structural features were completed through extrapolations and/or interpolations as the ruggedness and inaccessibility of a large part of the terrain forbid physical examination of every outcrop. It is in this context the potential of remote sensing, especially of satellite images, is to be appreciated.

Bayesian and Geostatistical Approaches to Combining Categorical Data Derived from Visual and Digital Processing of Remotely Sensed Images

This paper seeks a synthesis of Bayesian and geostatistical approaches to combining categorical data in the context of remote sensing classification. By experiment with aerial photographs and Landsat TM data, accuracy of spectral, spatial, and combined classification results was evaluated. It was confirmed that the incorporation of spatial information in spectral classification increases accuracy significantly. Secondly, through test with a 5-class and a 3-class classification schemes, it was revealed that setting a proper semantic framework for classification is fundamental to any endeavors of categorical mapping and the most important factor affecting accuracy. Lastly, this paper promotes non-parametric methods for both definition of class membership profiling based on band-specific histograms of image intensities and derivation of spatial probability via indicator kriging, a non-parametric geostatistical technique.

A Remote Sensing Model to Estimate Sunshine Duration in the Ningxia Hui Autonomous Region,China

Sunshine duration（SD） is strongly correlated with solar radiation, and is most widely used to estimate the latter. This study builds a remote sensing model on a 100 m × 100 m spatial resolution to estimate SD for the Ningxia Hui Autonomous Region, China. Digital elevation model（DEM） data are employed to reflect topography, and moderate-resolution imaging spectroradiometer（MODIS） cloud products（Aqua MYD06-L2 and Terra MOD06-L2） are used to estimate sunshine percentage. Based on the terrain（e.g.,slope, aspect, and terrain shadowing degree） and the atmospheric conditions（e.g., air molecules, aerosols,moisture, cloud cover, and cloud types）, observation data from weather stations are also incorporated into the model. Verification results indicate that the model simulations match reasonably with the observations,with the average relative error of the total daily SD being 2.21%. Further data analysis reveals that the variation of the estimated SD is consistent with that of the maximum possible SD; its spatial variation is so substantial that the estimated SD differs significantly between the south-facing and north-facing slopes,and its seasonal variation is also large throughout the year.

Bitumen Removal Determination on Asphalt Pavement Using Digital Imaging Processing and Spectral Analysis

This research aims to define an efficient and fast quantification of bitumen removal on the road surface by Digital Imaging Processing (DIP) and spectral analysis. The retrieval of bitumen removal is an important issue for road management and environmental studies related to asphalt wear and environmental pollution. The calculation of the Exposed Aggregate Index (EAI), based on DIP, allows to quantify in each frame the superficial removal of bitumen and the exposure of aggregates. A procedure, based on non-parametric classification process of digital images, gives a fast response of EAI. A correlation among EAI and spectral data, between 390 nm and 900 nm range, is evaluated. Results show a good correlation between spectral data at different wavelength and EAI. Finally, this work evaluates the possibility to retrieve asphalt bitumen removal through remote sensed imagery.

Applying Digital Image Processing to Evaluate a Extraction Method of Cartographic Features in Digital Images

A topic studied in cartography is to make the extraction of cartographic features that provide the update of cartographic maps more easily. For this reason many automatic routines were created with the intent to perform the features extraction. Despite of all studies about this, some features cannot be found by the algorithm or it can extract some pixels unduly. So the current article aims to show the results with the software development that uses the original and reference image to calculate some statistics about the extraction process. Furthermore, the calculated statistics can be used to evaluate the extraction process.

The Digital Mapping of Ukrainian Soils on the Base of High Resolution Space Images

The first Ukrainian using experience of multispectral space scanning for digital soil mapping is described in this paper. Methodical approaches for detailed soil observation of Ukrainian forest regions are elaborated based on modem mapping principles. For the first time in Ukraine, digital soil maps based on GIS （geographic information system） were obtained for individual farms. In GIS based on space images and digital relief models, the medium-scale and large-scale soil maps were created by geo-statistical methods. According to elaborated methods, modem digital soil mapping should provide all combined works： remote sensing and traditional soil observations. The modem digital soil mapping should be based just on quantitative principles： on remote sensing data, geomorphologic field parameters, and chemical analyses. The methodological approaches, which were used for the first time in Ukraine during digital soil mapping by remote sensing methods, are described in this paper.

基于ERDAS IMAGINE的三维地形可视化

三维可视化可以用来描述复杂的地形情况,实现对某种地学机理的深入认识,发现常规方法所不能揭示的地形规律和特征。本文在阐述三维可视化优越性的基础上,利用ERDAS IMAGINE软件对南京地区进行三维模拟和分析,为今后从整体上研究该区域提供依据。

Comparison of DEM accuracies generated from different stereo pairs over a plateau mountainous area

Digital elevation models(DEMs) can be quickly and conveniently generated using very high resolution(VHR) satellite stereo images. Previous studies have evaluated and compared DEM accuracy based on VHR satellite stereo pairs collected by different satellite sensors. However, few studies analyzed the accuracy of a DEM based on stereo image pairs from a satellite with the same orbit and different orbits for a region with significant topographic fluctuations in the plateau area. Referring to former studies, this paper had two objectives: to generate a digital elevation model(DEM) and evaluate its horizontal and vertical accuracy over a plateau area with high relief;and to study the mapping capability of multiorbit and multitemporal stereo pair images in the plateau mountainous region. To achieve these objectives, we collected the 2015 Worldview-2 stereo image pair and another three World View-2 images acquired in 2013, 2014, and 2015. First, the 2015 DEM was obtained using a strict physical model based on along-track stereo image pairs, and the reliability of the DEM was verified with field data. Then, the images obtained in 2013, 2014, and 2015 were combined into different-orbit stereo image pairs, DEMs were produced using rational function models, and the DEMs were verified using field data and the 2015 DEM as standards. The results showed that the relief degree has a particular influence on the DEM, and the precision of the DEM decreases as the topographic relief increases. Off-nadir angles can also influence DEM accuracy, with a larger angle corresponding to a lower DEM accuracy. The research also shows that the DEM obtained from four sets of experiments meets the accuracy requirement of a 1:5,000 digital elevation map, digital line graphic(DLG), and digital orthophoto map(DOM). Among these four groups of DEMs, the one based on the 2015 stereo pairs with the same satellite achieved the highest precision.

Fracture network characterisation of the Balmuccia peridotite using drone-based photogrammetry,implications for active-seismic site survey for scientific drilling

The presence of discontinuities(e.g.faults,fractures,veins,layering)in crystalline rocks can be challenging for seismic interpretations because the wide range of their size,orientation,and intensity,which controls the mechanical properties of the rock and elastic wave propagation,resulting in equally varying seismic responses at different scales.The geometrical characterisation of adjacent outcrop discontinuity networks allows a better understanding of the nature of the subsurface rocks and aids seismic interpretation.In this study,we characterise the discontinuity network of the Balmuccia peridotite(BP)in the IvreaeVerbano Zone(IVZ),northwestern Italy.This geological body is the focus of the Drilling the Ivrea eVerbano zonE(DIVE),an international continental scientific drilling project,and two active seismic surveys,SEismic imaging of the Ivrea ZonE(SEIZE)and high-resolution SEIZE(Hi-SEIZE),which aim to resolve the subsurface structure of the DIVE drilling target through high-resolution seismic imaging.For fracture characterisation,we developed two drone-based digital outcrop models(DOMs)at two different resolutions(10^(-3)-10 m and 10^(-1)-10^(3)m),which allowed us to quantitatively characterise the orientation,size,and intensity of the main rock discontinuities.These properties affect the seismic velocity and consequently the interpretation of the seismic data.We found that(i)the outcropping BP discontinuity network is represented by three more sets of fractures with respect to those reported in the literature;(ii)the discontinuity sizes follow a power-law distribution,indicating similarity across scales,and(iii)discontinuity intensity is not uniformly distributed along the outcrop.Our results help to explain the seismic behaviour of the BP detected by the SEIZE survey,suggesting that the low P-wave velocities observed can be related to the discontinuity network,and provide the basic topological parameters(orientation,density,distribution,and aperture)of the fracture network unique to the BP.These,in turn,can be used for interpretation of the Hi-SEIZE seismic survey and forward modelling of the seismic response.

“任务链+研学支架”教学模式的建构——新工科视角下“遥感数字图像处理”课教学改革

目前,传统教学在内容的系统性、认知活动高阶性、价值引领实效性、促学效果等方面存在着较严重的问题,为此,“遥感数字图像处理”课程基于新工科教学理念,以遥感技术的综合应用情境重构课程体系,开启“任务链+研学支架”教学模式,加强培养学生遥感应用能力和创新能力,以遥感技术服务社会需求为育人路径。新模式的构建,实现了应用与研学互动、研学与研教并举、育人与育才同构的效果,对同类型新工科课程具有借鉴意义。

遥感专业《数字图像处理》教材建设有效途径分析

数字图像处理教材存在理多实少、难点解析不足等种种问题。针对这些问题,提出一种混合式立体改进方法,从内容、形式和实践方面提出了多项举措,以实现够用学会、讲练透彻的学习目标。通过分析遥感专业课程内容,提炼出相关知识点进行教材编写,得到理实一体的简明化教材。教学实践证明,这种教材建设方法丰富了教学资源,有利于学生对重难点知识理解,大幅提高学习效率和质量,不失为一种有效的逆向教材建设创新方法。

无序无人机影像的并行化SfM三维重建方法

增量式运动恢复结构(ISfM)已成为无人机影像三维重建的关键技术。然而,大数据量、大重叠度和高分辨率的无序无人机影像导致的匹配对检索代价大、迭代优化误差累积和效率低的问题,使其难以满足大场景ISfM处理需求。本文提出联合全局描述子和图索引的无人机影像并行化SfM方法。针对影像特征数量大、影像检索编码本尺寸增加导致的匹配对检索效率低的问题,设计了联合全局描述子和图索引的高效影像检索方法,从而加速影像匹配。针对分块并行化SfM子场景合并存在同名点搜索效率低、内存消耗大、合并解算精度低的问题,设计了基于按需匹配图和双向重投影误差的子场景合并方法,实现无人机影像的并行化SfM重建。利用不同场景、不同采集方式获取的真实无人机影像进行试验,结果表明本文方法能够实现36~108倍加速比的匹配对检索,ISfM重建效率达到30倍加速,且相对定向和绝对定向精度与传统方法相当。

结合注意力机制的卫星遥感影像立体匹配

采用立体匹配技术对多视卫星遥感影像进行三维场景重建一直是摄影测量与遥感领域的核心问题。基于卷积神经网络的深度学习方法极大地促进了立体匹配技术的发展,然而其中涉及匹配困难和误匹配问题的相关研究仍然不足。为了提升卫星遥感影像不适定区域中视差估计的精度,本研究提出了一种结合注意力机制的立体匹配深度学习网络,在特征提取模块中加入注意力机制,分别从通道和空间两个维度捕获全局信息,对特征进行优化;在代价体的构建模块中构建新的代价体积,并重新设置视差的回归范围。为了验证本文方法的有效性,在US3D、WHU-Stereo两个数据集上分别与已有方法Stereo-Net、PSM-Net进行了比较分析。结果表明,本文方法在EPE(endpointerror)和D_1两个指标上均能达到最优,取得了较好的性能,提高了立体匹配的精度,尤其在无纹理、重复纹理、遮挡及视差不连续区域表现出良好的鲁棒性。

利用光学影像的滑坡位移监测

为充分挖掘光学遥感图像在滑坡监测中的应用潜力,本文基于数字图像相关法推导了适应滑坡非均匀形变和自然光照影响的滑坡位移光学影像计算公式,形成了基于光学影像的滑坡位移监测方法。试验分析了地表形变方式和形变量对滑坡位移光学影像计算公式的影响,给出了地表平移、旋转、扭曲3种不同形变方式下,计算误差的概率累计值变化曲线,证明了该公式95%计算结果的相对误差在0.04以内;利用两期SkySat卫星光学影像计算了某滑坡的平面位移场,分析了该滑坡的表面形变特征。本文研究为滑坡灾害监测预警提供了新的技术参考。

基于Landsat 8 OLI和资源3号立体像对数据的桉树森林蓄积量估测

【目的】探索Landsat8 OLI数据和立体数据在估算桉树森林蓄积量(forest stock volume,FSV)中的潜力,并且准确地估计桉树的FSV。【方法】以3幅Landsat8 OLI图像和资源3号立体数据为遥感数据源,并且结合少量地面调查数据实现了桉树FSV的遥感估计。研究中提取了三类遥感特征用于估计桉树FSV:第一类是包括植被指数和单波段反射率在内的光谱特征;第二类是基于Landsat 8 OLI图像的单波段提取的8种纹理特征;第三类是基于资源3号立体像对数据和开源的数字高程模型(digital elevation model,DEM)提取的冠层高度模型(canopy height model,CHM)。利用Boruta算法对三类遥感特征进行提取,之后建立了随机森林(random forest,RF)、K-最近邻(K-nearest neighbor,KNN)和支持向量机(support vector machine,SVM)3种机器学习模型以及传统的多源线性回归模型(multiple linear regression,MLR),并以决定系数(R2)、均方根误差(root mean square error,RMSE)和相对均方根误差(relative root mean square error,rRMSE)作为评价指标对模型结果进行评估。【结果】基于ZY-3立体像对数据和开源的DEM数据提取的CHM与桉树的FSV具有很强的相关性,Pearson相关系数达到了0.71。仅仅利用基于Landsat 8 OLI图像提取的光谱和纹理特征难以准确2地估计桉树的FSV,估测模型的R为0.29~0.38,rRMSE为35.65%~43.30%,存在严重的数据饱和问题。2当变量集中加入CHM后,模型的估测精度明显提高,R达到了0.64~0.66,rRMSE为25.74%~26.41%。【结论】使用Landsat 8 OLI数据估算桉树FSV时存在严重的数据饱和问题,并且使用空间分辨率为30 m的纹理特征难以有效地改善森林蓄积量的估计精度。利用资源3号立体像对数据和开源的DEM数据可以提取较为准确的CHM,并且所提取的CHM可以解决改善光学数据的饱和问题,从而提高桉树FSV的估计精度。

基于改进YOLOv4的遥感目标检测算法

针对遥感目标的多尺度、多样性、背景复杂等特点,为提升YOLOv4算法的检测速度和平均精度,提出了一种基于YOLOv4模型改进的遥感目标检测算法,首先,用Mobilenetv2替换YOLOv4的主干特征提取网络,减少参数数量,提升检测速度;其次,在Mobilenetv2的残差网络中嵌入新型注意力机制CoordAttention模块,捕获方向感和位置感知的信息,精准定位和识别感兴趣的目标;最后,借鉴Inception的思想在颈部特征增强网络处添加改进过的RFB模块,增强感受野并且提升网络的特征融合能力。研究表明,论文提出的MCR-YOLOv4(Mobilenetv2-CoordAttention-RFB-You Only Look Once)算法相比于原YOLOv4算法,模型大小减少了45.27 M,平均精度提高了1.03%,检测速度提高了56帧/s,更适用于对复杂遥感目标的检测。

PBL教学在遥感数字图像处理课程双语课程建设中的探索与实践

双语教学是我国高等教育适应经济全球化的必然选择,也是高等院校教育教学改革的重点内容之一。该文首先从教学资源、语言角色、教学实践等角度分析当前双语教学中存在的问题。其次,探讨了基于PBL(Problem-Based Learning)的双语教学模式在本科生遥感数字图像处理课程教学上的应用,从课前预习、课内深化、课后巩固三个维度阐述双语课程构建方式,并深入分析这种新型教学模式对学生的促进作用。实践结果表明,基于PBL的双语教学能够有效地提升学生在不同语言环境下的思维和表达能力,拓宽学生的国际视野,达到利用英文的思维逻辑体系看待问题、解决问题的目的,为课程今后实现全英文授课提供有力支撑,并使教师可以在实践中逐步发现问题和解决问题,不断深入指导其他课程的双语教学改革。