基于几何形态测量学的四种滨螺形态差异与系统发生关系研究   总被引：1，自引：0，他引：1  

陈楠桦  梁仁杰  白义  王海瑞 《海洋与湖沼》2018,49(6):1365-1374

运用几何形态测量学方法研究浙江省大陈岛海域常见的4种滨螺间的形态关系。对4种滨螺的壳口、螺体分别进行数字化标点,经叠印分析、主成分分析(PCA)和薄片样条法分析,获得4种滨螺在壳口和螺体上的差异,并进一步分析其形态特征与潮间带环境适应性关系。PCA结果表明四种滨螺壳口间差异在主成分轴上无法有效分开,而螺体间差异在主成分轴上能有效分开,说明壳口特征在不同滨螺间不具有规律性差异。螺体的PCA中PC1轴可以将短滨螺与其他3种滨螺区分,薄片样条法分析显示差异的部位主要在体螺层的宽度和螺体的高度间,PC2轴可以将粒结节滨螺与其他3种滨螺分开,薄片样条法分析显示差异部位主要是体螺层之上第一层以及体螺层之间。基于螺体特征的4种滨螺亲缘关系分析表明粗糙滨螺与塔结节滨螺亲缘关系最近,其次为短滨螺,粒结节滨螺最不相近。运用特征追踪法对螺层和螺肋特征追踪,结果表明螺层6层,螺肋密生是滨螺的祖先特征,后来演化出7层和8层的螺层特征以及颗粒状突起的螺肋特征。  相似文献   

基于D-InSAR技术的金沙江地区滑坡形变监测与分析     

齐麟  孔祥意  袁鑫  姜岩 《测绘与空间地理信息》2020,(2):175-177,181

滑坡是发生在我国山区的主要地质灾害类型,金沙江地区由于地势较高、地形复杂、多云多雨的特点,给传统的滑坡监测增加了难度。合成孔径雷达差分干涉测量技术(Differential interferometry synthetic aperture radar,D-InSAR)已在滑坡地面沉降监测中得到了广泛应用。本文选取金沙江上游沿岸作为研究区域,基于2018年8月11日与9月28日的Sentinel-1A影像及SRTM1数据,利用GAMMA软件及D-InSAR技术监测到金沙江地区的地表形变,成功识别出金沙江右岸的一处滑坡灾害。研究结果显示,在此滑坡的坡顶部分出现了约2.5 cm的沉降,而在坡底部分由于崩塌物的累积,地面出现了约3 cm的抬升。从实验结果可以得出,InSAR技术是一种有效的滑坡变形监测手段,利用Sentinel-1A卫星的SAR数据对滑坡区域进行形变监测,可以得到较好的干涉结果。  相似文献   

基于一维综合孔径微波辐射计的海面温度反演研究   总被引：1，自引：0，他引：1  

艾未华  冯梦延  陈冠宇  陆文 《海洋学报(英文版)》2020,42(5):115-122

Due to the low spatial resolution of sea surface temperature(T_S) retrieval by real aperture microwave radiometers,in this study, an iterative retrieval method that minimizes the differences between brightness temperature(T_B)measured and modeled was used to retrieve sea surface temperature with a one-dimensional synthetic aperture microwave radiometer, temporarily named 1 D-SAMR. Regarding the configuration of the radiometer, an angular resolution of 0.43° was reached by theoretical calculation. Experiments on sea surface temperature retrieval were carried out with ideal parameters; the results show that the main factors affecting the retrieval accuracy of sea surface temperature are the accuracy of radiometer calibration and the precision of auxiliary geophysical parameters. In the case of no auxiliary parameter errors, the greatest error in retrieved sea surface temperature is obtained at low T_S scene(i.e., 0.710 6 K for the incidence angle of 35° under the radiometer calibration accuracy of0.5 K). While errors on auxiliary parameters are assumed to follow a Gaussian distribution, the greatest error on retrieved sea surface temperature was 1.330 5 K at an incidence angle of 65° in poorly known sea surface wind speed(W)(the error on W of 1.0 m/s) over high W scene, for the radiometer calibration accuracy of 0.5 K.  相似文献   

DInSAR技术对不同方位形变的敏感性研究   总被引：3，自引：1，他引：2  

查显杰  傅容珊  戴志阳 《测绘学报》2006,35(2):133-137

以DEM数据为假想的地面目标,只考虑距离对相位的影响,模拟竖直向、距离向和方位向形变的干涉纹图,从而研究DInSAR技术对空间不同方位形变的敏感性。在所有模拟参数和形变位移大小都相同的情况下,三个不同方位形变所产生的相位从0到2π变化的完整干涉环的数目是各不相同的,揭示DInSAR技术对不同方位地表形变的敏感性存在差异,且敏感性由大到小依次为:竖直向、距离向和方位向。  相似文献   

利用Sentinel-1影像监测土地回填导致的地表形变     

杨映新  洪武胜  吴曼乔 《测绘通报》2021,(6):67-70

在机场填海区地表稳定散射的范围内,本文运用合成孔径雷达干涉测量（InSAR）技术对机场地表形变安全性进行了监测分析,反演获得了研究区域范围内的年形变速率数据结果和高分辨率形变时序结果,并以此分析了香港国际机场的地表形变区在监测周期内的形变时空分布特征。为证明监测结果的精度和可靠性,本文采用全球导航卫星系统（GNSS）观测站的垂直位移数据,对InSAR方法反演的结果进行了交叉验证,证明两者具有良好的一致性。  相似文献   

海洋涡旋遥感：进展与挑战     

陈戈  杨杰  田丰林  陈树果  赵朝方  唐军武  刘颖洁  王祎诺  苑忠浩  何遒  曹川川 《遥感学报》2021,25(1):302-322

海洋涡旋数量大、分布广、含能高、裹挟强,是研究物质循环、能量级联和圈层耦合的理想载体。对涡旋的全生命周期追踪观测成为21世纪以来海洋遥感领域最重要的进展之一,并引发了新一轮涡旋研究的热潮。本文从涡旋的温度异常、物质示踪、旋转流场和闭合拓扑等特征出发,简述了红外辐射计、可见光扫描仪、微波高度计、合成孔径雷达等遥感技术在涡旋观测中的机理和方法,重点阐述了卫星高度计涡旋识别与追踪算法及其在涡旋形态学、运动学和动力学中的应用。基于虚拟星座下的多参数遥感,介绍了涡旋在海洋、大气、生态等交叉学科领域的前沿应用和最新进展。指出当前涡旋遥感发展面临的亚中尺度、垂直结构、跨学科研究等3大挑战,展望了新一代遥感技术在未来海洋科学特别是涡旋海洋学研究中的应用前景。  相似文献   

一维综合孔径微波辐射计遥感海面温度的敏感性分析     

陈冠宇  艾未华  陆文  冯梦延 《海洋学报》2019,41(3):143-154

一维综合孔径微波辐射计能够有效提高观测的空间分辨率，其观测入射角通常在0°~55°范围内变化。为了开发适用于一维综合孔径微波辐射计的海面温度反演算法，需要评估其观测亮温对海洋大气环境要素的敏感性。利用海面发射率模型和大气辐射传输模型，构建了适用于一维综合孔径微波辐射计的微波海洋大气辐射传输模式，研究了C波段垂直和水平极化微波辐射亮温在不同入射角下对海洋大气环境要素的敏感性变化情况，并定量计算了相应的敏感系数。结果表明:垂直和水平极化亮温对海洋大气环境要素的敏感性表现出不同的特性。随着入射角的增大，垂直极化亮温对海面温度的敏感性增强，对海面风场的敏感性相对减弱；水平极化亮温则相反。由大气水汽含量和云液态水含量误差引入的垂直和水平极化亮温误差随入射角增大而增大，但是，即使在55°的大入射角下垂直和水平极化亮温误差仍小于0.12 K。对于海面温度反演精度优于1 K的要求，一维综合孔径微波辐射计的测温精度需优于0.6 K。研究结果对于一维综合孔径微波辐射计海面温度反演算法的研究和载荷设计具有一定的理论指导意义。  相似文献   

SAR image despeckling with a multilayer perceptron neural network     

Xiao Tang  Lei Zhang  Xiaoli Ding 《International Journal of Digital Earth》2019,12(3):354-374

Speckle noise in synthetic-aperture radar (SAR) images severely hinders remote sensing applications; therefore, the appropriate removal of speckle noise is crucial. This paper elaborates on the multilayer perceptron (MLP) neural-network model for SAR image despeckling by using a time series of SAR images. Unlike other filtering methods that use only a single radar intensity image to derive their parameters and filter that single image, this method can be trained using archived images over an area of interest to self-learn the intensity characteristics of image patches and then adaptively determine the weights and thresholds by using a neural network for image despeckling. Several hidden layers are designed for feedforward network training, and back-propagation stochastic gradient descent is adopted to reduce the error between the target output and neural-network output. The parameters in the network are automatically updated in the training process. The greatest advantage of MLP is that once the despeckling parameters are determined, they can be used to process not only new images in the same area but also images in completely different locations. Tests with images from TerraSAR-X in selected areas indicated that MLP shows satisfactory performance with respect to noise reduction and edge preservation. The overall image quality obtained using MLP was markedly higher than that obtained using numerous other filters. In comparison with other recently developed filters, this method yields a slightly higher image quality, and it demonstrates the powerful capabilities of computer learning using SAR images, which indicate the promising prospect of applying MLP to SAR image despeckling.  相似文献   

An improved building detection approach using L-band POLSAR two-dimensional time-frequency decomposition over oriented built-up areas     

Lei Deng  Ying He  Zhi-hui Mao  Jie Yu 《地理信息系统科学与遥感》2019,56(1):1-21

The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value.  相似文献   

Wetland hydroperiod classification in the western prairies using multitemporal synthetic aperture radar          下载免费PDF全文

Joshua S. Montgomery  Chris Hopkinson  Brian Brisco  Shane Patterson  Stewart B. Rood 《水文研究》2018,32(10):1476-1490

Wetlands represent one of the world's most biodiverse and threatened ecosystem types and were diminished globally by about two‐thirds in the 20th century. There is continuing decline in wetland quantity and function due to infilling and other human activities. In addition, with climate change, warmer temperatures and changes in precipitation and evapotranspiration are reducing wetland surface and groundwater supplies, further altering wetland hydrology and vegetation. There is a need to automate inventory and monitoring of wetlands, and as a study system, we investigated the Shepard Slough wetlands complex, which includes numerous wetlands in urban, suburban, and agricultural zones in the prairie pothole region of southern Alberta, Canada. Here, wetlands are generally confined to depressions in the undulating terrain, challenging wetlands inventory and monitoring. This study applied threshold and frequency analysis routines for high‐resolution, single‐polarization (HH) RADARSAT‐2, synthetic aperture radar mapping. This enabled a growing season surface water extent hyroperiod‐based wetland classification, which can support water and wetland resource monitoring. This 3‐year study demonstrated synthetic aperture radar‐derived multitemporal open‐water masks provided an effective index of wetland permanence class, with overall accuracies of 89% to 95% compared with optical validation data, and RMSE between 0.2 and 0.7 m between model and field validation data. This allowed for characterizing the distribution and dynamics of 4 marsh wetlands hydroperiod classes, temporary, seasonal, semipermanent, and permanent, and mapping of the sequential vegetation bands that included emergent, obligate wetland, facultative wetland, and upland plant communities. Hydroperiod variation and surface water extent were found to be influenced by short‐term rainfall events in both wet and dry years. Seasonal hydroperiods in wetlands were particularly variable if there was a decrease in the temporary or semipermanent hydroperiod classes. In years with extreme rain events, the temporary wetlands especially increased relative to longer lasting wetlands (84% in 2015 with significant rainfall events, compared with 42% otherwise).  相似文献