Monitoring soil surface roughness under growing winter wheat with low-altitude UAV sensing: Potential and limitations

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.     

Talus slope geomorphology investigated at multiple time scales from high-resolution topographic surveys and historical aerial photographs (Sanetsch Pass,Switzerland)

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.     

重庆地震应急资料产出系统研发与应用

地震应急资料具有较强的时效性、专业性和多学科融合的特点。中强地震发生后启动应急响应,工作人员需在短时间内产出多学科、跨领域、多手段的专业地震会商资料。以地震会商系统为平台,利用其灵活开发、自动计算和智能分析的优势,建立地震应急资料产出系统（包括会商资料处理模块、应急图件产出模块和震情报告生成模块）,通过地震触发,根据预设流程和报告模板,自动产出专业报告,为震情形势研判和震后应急救援提供专业可靠的应急资料,最大限度地发挥应急救援和灾损评估的效能。     

基于微型无人机摄影技术的微构造信息提取研究——以博-阿断裂乌苏通沟东岸为例

利用微型无人机摄影测量技术,获取了博-阿断裂在乌苏通沟东岸的高精度地形、地貌数据,解译DEM数据,并结合野外调查工作,明确了断裂在乌苏通沟东岸冲洪积扇上19.3～31.1m的水平位错。分析获取的陡坎剖面,且对比陡坎两侧地貌的剥蚀程度,认为陡坎形成后受到后期水流的侵蚀,部分陡坎的高度在一定程度上被放大,断裂的实际垂直位错在0.7m左右。通过实例展示了无人机摄影技术在活动构造研究中的巨大潜力以及在微构造信息提取中的独特优势。     

Quantifying flow resistance in mountain streams using computational fluid dynamics modeling over structure-from-motion photogrammetry-derived microtopography

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 σ_z 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/σ_z, is proposed based on the comparison between σ_z 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.     

Guidelines on the use of structure-from-motion photogrammetry in geomorphic research

As a topographic modelling technique, structure-from-motion (SfM) photogrammetry combines the utility of digital photogrammetry with a flexibility and ease of use derived from multi-view computer vision methods. In conjunction with the rapidly increasing availability of imagery, particularly from unmanned aerial vehicles, SfM photogrammetry represents a powerful tool for geomorphological research. However, to fully realize this potential, its application must be carefully underpinned by photogrammetric considerations, surveys should be reported in sufficient detail to be repeatable (if practical) and results appropriately assessed to understand fully the potential errors involved. To deliver these goals, robust survey and reporting must be supported through (i) using appropriate survey design, (ii) applying suitable statistics to identify systematic error (bias) and to estimate precision within results, and (iii) propagating uncertainty estimates into the final data products. © 2019 John Wiley & Sons, Ltd.     

基于无人机倾斜摄影的强震区公路高位危岩崩塌形成机制及稳定性评价

强震区公路高位危岩崩塌具有极高隐蔽性和危害性,传统的接触式勘察方法难以有效调查震后位于公路两侧高陡斜坡体上的危岩崩塌体。提出一种基于无人机的倾斜摄影测量技术,该技术采用无人机超低空采集高位危岩体的高清影像数据,构建三维空间模型,从而提取危岩体特征参数,为危岩体稳定性分析提供数据支撑。利用无人机对某高速公路危岩崩塌地质灾害路段进行调查,对无人机倾斜摄影测量成果进行分析,明确调查区19处危岩崩塌体特征和崩塌成因机制,在此基础上评价典型崩塌体稳定性。并且使用RocFall软件模拟分析典型危岩体崩落运动轨迹,研究高位危岩崩塌对公路的危险性。研究成果对强震区山区公路高位危岩崩塌勘察、稳定性评价工作具有重要的参考价值。     

基于HTML5+CSS3+jQuery Mobile的台站智能管理系统开发与实现

随着黑龙江省地震局省内运维任务越来越重,出现了运维管理模式无法优化资源配置,运维流程比较随意,设备缺乏数字化管理,运维人员有限等问题。为了解决实际工作问题,结合地震设备运维管理系统软件在黑龙江省区域运维中的应用,采用HTML5+CSS3+jQuery Mobile软件技术开发了一套基于移动端的设备管理系统,使用户可以同时用移动端与PC端,通过Web浏览器操作服务器,实现了区域运维中心对地震监测设备的统一数字化管理,提高了管理效率。     

倾斜摄影实景三维建模技术及其应用现状分析

倾斜摄影实景三维建模技术将传统测量从二维平面提升至三维立体层次,同时也将部分外业测绘工作转化到内业数据处理,极大程度地提高了生产效率.作为一种新兴测绘技术,倾斜摄影实景三维建模技术具有其自身的两面性,本文从倾斜摄影实景三维建模技术原理出发,结合其优点及不足之处,详细阐述分析了该技术在各个领域的应用现状及优化措施.     

DMC影像在数字摄影测量中的应用

介绍了DMC影像数据的特点,通过与传统扫描影像的比较,介绍了DMC影像在数字摄影测量中的应用。