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1.
基于Sentinel-1 SAR升、降影像,利用D-InSAR技术获取新疆伽师M S6.4地震的同震形变场,结果表明,本次地震引起的同震形变场整体呈近椭圆状分布,形变区东西长约66 km,南北宽约40 km,整个形变场由南部隆升区和北部沉降区组成,南部最大隆升量约7 cm,北部最大沉降量约3 cm。本次地震发生在块体俯冲界面处的低倾角逆冲推覆构造带上,隆升和沉降两个中心均位于逆冲推覆体的上盘,形变主要以隆升形变为主,符合低倾角逆断层中强震的变形特征。在沉降区与隆升区之间干涉条纹连续分布,未出现表征地表破裂位置的空间失相关带,表明地震未引起明显的地表破裂。结合震源机制、余震精定位及区域构造特征,初步推断认为伽师地震的发震构造可能为柯坪塔格推覆构造前缘的N倾的柯坪断裂。  相似文献   
2.
利用历史观测得到的温度剖面数据,通过严格筛选和插值,建立了南海北部的气候态垂向温度剖面。随后,利用回归统计分析的方法构建了海面温度异常(SSTA)、海面高度异常(SSHA)联合扩展温度剖面的经验回归模型,并采用卫星遥感得到的SST和SSH数据扩展了南海北部的三维海洋温度场,其时间分辨率为天,空间分辨率为0.25°×0.25°。通过与观测数据的对比研究,扩展得到的温度场可以较为准确地反映南海北部温度剖面的结构特征,并且能有效地体现出一些中尺度变化过程。结果表明,本研究反演得到的三维温度扩展场是较为可靠的,它可以作为海洋数值模型的初始场,实现现场观测数据和卫星遥感数据的互补,有助于更好地分析南海北部温度场的三维结构及变化特征。  相似文献   
3.
Flow resistance in mountain streams is important for assessing flooding hazard and quantifying sediment transport and bedrock incision in upland landscapes. In such settings, flow resistance is sensitive to grain-scale roughness, which has traditionally been characterized by particle size distributions derived from laborious point counts of streambed sediment. Developing a general framework for rapid quantification of resistance in mountain streams is still a challenge. Here we present a semi-automated workflow that combines millimeter- to centimeter-scale structure-from-motion (SfM) photogrammetry surveys of bed topography and computational fluid dynamics (CFD) simulations to better evaluate surface roughness and rapidly quantify flow resistance in mountain streams. The workflow was applied to three field sites of gravel, cobble, and boulder-bedded channels with a wide range of grain size, sorting, and shape. Large-eddy simulations with body-fitted meshes generated from SfM photogrammetry-derived surfaces were performed to quantify flow resistance. The analysis of bed microtopography using a second-order structure function identified three scaling regimes that corresponded to important roughness length scales and surface complexity contributing to flow resistance. The standard deviation σz of detrended streambed elevation normalized by water depth, as a proxy for the vertical roughness length scale, emerges as the primary control on flow resistance and is furthermore tied to the characteristic length scale of rough surface-generated vortices. Horizontal length scales and surface complexity are secondary controls on flow resistance. A new resistance predictor linking water depth and vertical roughness scale, i.e.  H/σz, is proposed based on the comparison between σz and the characteristic length scale of vortex shedding. In addition, representing streambeds using digital elevation models (DEM) is appropriate for well-sorted streambeds, but not for poorly sorted ones under shallow and medium flow depth conditions due to the missing local overhanging features captured by fully 3D meshes which modulate local pressure gradient and thus bulk flow separation and pressure distribution. An appraisal of the mesh resolution effect on flow resistance shows that the SfM photogrammetry data resolution and the optimal CFD mesh size should be about 1/7 to 1/14 of the standard deviation of bed elevation. © 2019 John Wiley & Sons, Ltd.  相似文献   
4.
高分六号卫星具有覆盖广、多种分辨率、波段多的优势,能为遥感解译提供更丰富的信息。为探究高分六号卫星新增波段在森林树种识别上的应用,本文以覆盖根河市阿龙山林业局的一期高分六号宽幅影像为数据源,基于特征优化空间算法(Feature Space Optimization,FSO)和最大似然分类法,分别利用高分六号的前4个波段和所有波段(8波段)的光谱、纹理等特征进行了森林树种分类,并逐一添加新增波段特征确定了各波段的贡献率排名。结果表明:在加入了优选出的均匀性纹理、均值纹理和角二阶矩纹理3种纹理特征后,前4波段和8波段的分类精度比只基于光谱特征时的精度分别高出13.23%和24.63%;利用8波段信息比只利用前4波段在基于光谱特征上的精度高11.88%,在基于光谱+纹理特征上则高23.24%;基于8波段光谱+纹理特征的树种分类精度最高,达到68.74%,新增4波段的贡献率排名为B6>B5>B8>B7,说明新增红边波段对于本次树种分类试验的贡献率最高,能为北方树种识别提供有效帮助。  相似文献   
5.
李通 《北京测绘》2020,(4):543-546
目前,城市大比例尺地形图更新主要采用全野外的测量方法,不仅耗费大量的劳动力,并且效率低下。旋翼机和倾斜摄影测量技术的快速发展,为城市大比例尺地形图的测绘与更新提供了全新的技术手段。本文以滕州市城区约10 km2的1∶500地形图测绘项目为例,采用大疆精灵4 Pro旋翼机进行数据获取,Smart 3D软件进行空三加密及三维建模,最后在EPS软件中进行三维测图,并对地形图成果进行了精度检核,验证了技术方案的可行性,为同类项目提供了有益参考。  相似文献   
6.
朱德辉  杜博  张良培 《遥感学报》2020,24(4):427-438
高光谱遥感影像具有光谱分辨率极高的特点,承载了大量可区分不同类型地物的诊断性光谱信息以及区分亚类相似地物之间细微差别的光谱信息,在目标探测领域具有独特的优势。与此同时,高光谱遥感影像也带来了数据维数高、邻近波段之间存在大量冗余信息的问题,高维度的数据结构往往使得高光谱影像异常目标类和背景类之间的可分性降低。为了缓解上述问题,本文提出了一种基于波段选择的协同表达高光谱异常探测算法。首先,使用最优聚类框架对高光谱波段进行选择,获得一组波段子集来表示原有的全部波段,使得高光谱影像异常目标类与背景类之间的可分性增强。然后使用协同表达对影像上的像元进行重建,由于异常目标类和背景类之间的可分性增强,对异常目标像元进行协同表达时将会得到更大的残差,异常目标像元的输出值增大,可以更好地实现异常目标和背景类的分离。本文使用了3组高光谱影像数据进行异常目标探测实验,实验结果表明,该方法与其他现有高光谱异常目标探测算法对比,曲线下面积AUC(Area Under Curve)值更高,可以更好地实现异常目标与背景分离,能够更有效地对高光谱影像进行异常目标探测。  相似文献   
7.
针对目前有关北斗三号系统伪距单点定位研究较少,未对三号系统多个频点的定位性能进行对比分析的现状,本文利用实测数据对三号系统多个频点的定位性能进行了研究,并联合BDS-2、Galileo进行了同频伪距单点定位试验,统计分析了组合定位多个频点的同频定位结果。试验结果表明:目前三号系统单独定位能力有限,不适合单独定位;BDS-3/Galileo同频组合定位可以弥补BDS-3新频点单频定位时卫星个数不足、数据不完整导致的定位精度过差的情况,同时能够提高Galileo的定位精度;BDS-2/3的B3I频点与BDS/Galileo组合的B2b频点的定位精度均与GPS的L1频点的定位精度相当。  相似文献   
8.
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   
9.
Talus slopes are common places for debris storage in high-mountain environments and form an important step in the alpine sediment cascade. To understand slope instabilities and sediment transfers, detailed investigations of talus slope geomorphology are needed. Therefore, this study presents a detailed analysis of a talus slope on Col du Sanetsch (Swiss Alps), which is investigated at multiple time scales using high-resolution topographic (HRT) surveys and historical aerial photographs. HRT surveys were collected during three consecutive summers (2017–2019), using uncrewed aerial vehicle (UAV) and terrestrial laser scanning (TLS) measurements. To date, very few studies exist that use HRT methods on talus slopes, especially to the extent of our study area (2 km2). Data acquisition from ground control and in situ field observations is challenging on a talus slope due to the steep terrain (30–37°) and high surface roughness. This results in a poor spatial distribution of ground control points (GCPs), causing unwanted deformation of up to 2 m in the gathered UAV-derived HRT data. The co-alignment of UAV imagery from different survey dates improved this deformation significantly, as validated by the TLS data. Sediment transfer is dominated by small-scale but widespread snow push processes. Pre-existing debris flow channels are prone to erosion and redeposition of material within the channel. A debris flow event of high magnitude occurred in the summer of 2019, as a result of several convective thunderstorms. While low-magnitude (<5,000 m3) debris flow events are frequent throughout the historical record with a return period of 10–20 years, this 2019 event exceeded all historical debris flow events since 1946 in both extent and volume. Future climate predictions show an increase of such intense precipitation events in the region, potentially altering the frequency of debris flows in the study area and changing the dominant geomorphic process which are active on such talus slopes. © 2020 John Wiley & Sons, Ltd.  相似文献   
10.
Soil surface roughness (SSR) is an important factor in controlling sediment and runoff generation, influencing directly a wide spectrum of erosion parameters. SSR is highly variable in time and space under natural conditions, and characterizing SSR to improve the parameterization of hydrological and erosion models has proved challenging. Our study uses recent technological and algorithmic developments in capturing and processing close aerial sensing data to evaluate how high-resolution imagery can assist the temporally and spatially explicit monitoring of SSR. We evaluated the evolution of SSR under natural rainfall and growing vegetation conditions on two arable fields in Denmark. Unmanned aerial vehicle (UAV) photogrammetry was used to monitor small field plots over 7 months after seeding of winter wheat following conventional and reduced tillage treatments. Field campaigns were conducted at least once a month from October until April, resulting in nine time steps of data acquisition. Structure from motion photogrammetry was used to derive high-resolution point clouds with an average ground sampling distance of 2.7 mm and a mean ground control point accuracy of 1.8 mm. A comprehensive workflow was developed to process the point clouds, including the detection of vegetation and the removal of vegetation-induced point cloud noise. Rasterized and filtered point clouds were then used to determine SSR geostatistically as the standard deviation of height, applying different kernel sizes and using semivariograms. The results showed an influence of kernel size on roughness, with a value range of 0.2–1 cm of average height deviation during the monitoring period. Semivariograms showed a measurable decrease in sill variance and an increase in range over time. This research demonstrated multiple challenges to measuring SSR with UAV under natural conditions with increasing vegetation cover. The proposed workflow represents a step forward in tackling those challenges and provides a knowledge base for future research. © 2020 John Wiley & Sons, Ltd.  相似文献   
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