内点最大化与冗余点控制的无人机遥感图像配准     

余蕊  陈玮扬  杨扬  杨昆  罗毅 《遥感学报》2020,24(11):1325-1341

利用小型无人机进行遥感图像配准在自然灾害损害评估、环境监测和目标检测与追踪等领域发挥着至关重要的作用，但小型无人机的图像采集过程容易受风速/风向、复杂地形、电池容量、飞行姿态、飞行高度等自然或人为因素的影响。这些问题通常会导致捕捉到的场景重叠率低与图像非刚性畸变，在特征点提取过程中产生大量冗余点，增加了图像配准的难度。本文提出一种基于特征点的小型无人机图像配准方法，该方法的核心思想是在配准过程中识别冗余点，同时最大化可用内点数量。所识别的冗余点当作控制点，用于控制网格代图像的运动。最后通过最大化内点和合理移动控制点来恢复图像变换。本文使用50对小型无人机图像进行特征匹配和图像配准的实验，其中平均配准精度可达80.38%，并且本文方法在所有的情况下都优于5种当前流行算法。  相似文献   

2011年日本东北大地震（M_W=9.0）震间与震前变形场特征及其对强震预测的启示          下载免费PDF全文

朱守彪 《地球物理学报》2020,63(2):427-439

强震震前(preseismic)动力学过程的研究对于地震预测具有十分重要的意义,但由于观测资料的限制,目前对强震前孕震区力学状态及其演化过程的认识还非常有限.2011年日本东北9.0特大地震(Tohoku-Oki)发生在GPS观测台站最为密集的地区,为研究特大地震震间(interseismic)与震前的变形状态提供了难得的机会.文中将利用日本东北大地震之前连续的GPS观测资料,分别计算震间与震前的速度场与变形场.通过对比分析发现,日本东北地区(Tohoku)震前的应变状态与震间的有很大的不同,震间的变形主要受到太平洋板块向日本海沟北西西向的俯冲挤压作用所控制,其主压应变以近东西向压缩为主,日本东北地区的运动方向与太平洋板块的运动方向大体一致.但是,临近地震前(震前)日本东北地区的运动方向发生了很大变化,震前30天的连续GPS观测结果显示,速度场的优势方向经常变换,间歇性地出现与太平洋板块运动方向相反的情况.这意味着震前孕震区的力学状态发生了很大的改变.这种变化可能与震前破裂成核或慢滑移及慢地震等过程有关,这些过程将加速或促进大地震的发生,从而为大地震的发生准备了力学条件.值得特别强调的是,这些现象都是可以通过直接观测能够发现的大地震之前的异常现象.由此可见,加密GPS站点进行连续观测,寻找震前变形异常区以及探索异常的物理机制对于地震预测预报有重要的科学意义.  相似文献   

2013年南斯科舍海岭M_W7.8地震的多点震源机制反演          下载免费PDF全文

张喆  许力生 《地球物理学报》2020,63(8):2978-2998

2013年11月17日，在南极南奥克尼群岛北、南极板块与斯科舍板块之间发生了一次M_W7.8级地震（2013年南斯科舍海岭M_W7.8地震），我们利用全球分布的长周期和宽频带地震记录反演确定了这次地震随时间和空间变化的震源机制，验证了提出的一种多点震源机制反演的新方法.首先利用长周期记录的W震相反演了这次地震的矩心矩张量解并利用体波提取了视震源时间函数，同时利用台阵反投影技术从宽频带记录中获得了这次地震的高频源的时空分布，然后基于矩心矩张量解、视震源时间函数以及高频源的时空分布，实现了采用新方法对2013年南斯科舍海岭M_W7.8地震的多点震源机制反演.矩心矩张量解表明，地震矩心在44.50°W/60.18°S，矩心深度19 km，半持续时间49 s，释放标量地震矩4.71×10²⁰ N·m，发震断层走向104°，倾角54°，滑动角8°.视震源时间函数清楚地揭示了地震矩随时间变化的方位依赖性，总体上可以将时间过程分为前60 s和后50 s两个阶段，但前60 s可细分为两次子事件.根据台阵反投影结果，这次地震为沿海沟从西到东的单侧破裂，破裂长度达311 km，可以分为5次子事件，能量释放的峰值点依次为13 s、30 s、51 s、64 s和84 s，平均破裂速度分别为0.6 km·s^-1、2.6 km·s^-1、2.3 km·s^-1、2.8 km·s^-1和3 km·s^-1.多点震源机制反演显示，5次子事件的矩震级分别为M_W7.57，M_W7.48，M_W6.80，M_W7.53和M_W7.08，半持续时间依次为21 s，17 s，6 s，16 s和8 s，走向分别为95°，105°，81°，98°和98°，倾角依次为57°，49°，86°，46°和64°，滑动角-9°，1°，-17°，13°和-4°.这些在震源机制、能量释放以及持续时间方面的变化都是当地构造和应力环境复杂性的反映.  相似文献   

A new concept for estimating the influence of vegetation on throughfall kinetic energy using aerial laser scanning     

Johannes Antenor Senn  Fabian Ewald Fassnacht  Jana Eichel  Steffen Seitz  Sebastian Schmidtlein 《地球表面变化过程与地形》2020,45(7):1487-1498

Soil loss caused by erosion has enormous economic and social impacts. Splash effects of rainfall are an important driver of erosion processes; however, effects of vegetation on splash erosion are still not fully understood. Splash erosion processes under vegetation are investigated by means of throughfall kinetic energy (TKE). Previous studies on TKE utilized a heterogeneous set of plant and canopy parameters to assess vegetation's influence on erosion by rain splash but remained on individual plant- or plot-levels. In the present study we developed a method for the area-wide estimation of the influence of vegetation on TKE using remote sensing methods. In a literature review we identified key vegetation variables influencing splash erosion and developed a conceptual model to describe the interaction of vegetation and raindrops. Our model considers both amplifying and protecting effect of vegetation layers according to their height above the ground and aggregates them into a new indicator: the Vegetation Splash Factor (VSF). It is based on the proportional contribution of drips per layer, which can be calculated via the vegetation cover profile from airborne LiDAR datasets. In a case study, we calculated the VSF using a LiDAR dataset for La Campana National Park in central Chile. The studied catchment comprises a heterogeneous mosaic of vegetation layer combinations and types and is hence well suited to test the approach. We calculated a VSF map showing the relation between vegetation structure and its expected influence on TKE. Mean VSF was 1.42, indicating amplifying overall effect of vegetation on TKE that was present in 81% of the area. Values below 1 indicating a protective effect were calculated for 19% of the area. For future work, we recommend refining the weighting factor by calibration to local conditions using field-reference data and comparing the VSF with TKE field measurements. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd  相似文献   

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

Nils Onnen  Anette Eltner  Goswin Heckrath  Kristof Van Oost 《地球表面变化过程与地形》2020,45(14):3747-3759

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   

2017年西藏米林6.9级地震前的热红外异常分析          下载免费PDF全文

张丽峰  王培玲  张朋涛  孙玺皓 《地震工程学报》2020,42(2):360-367

以小波变换和功率谱估计为研究方法,使用中国静止气象卫星热红外亮温数据,研究了2017年11月18日西藏米林MS6.9地震前的热辐射情况。结果发现震前4个月出现热红外异常,其后续演化方向与相关区域的断裂走向非常一致。在8月10日左右异常面积达最大,相对功率谱大于6倍的面积约为20万km^2,9月20日左右消失。分析相同频率2016年同期数据,结果显示在震中周围并未出现显著异常。时序曲线分析表明在8月12日相对功率谱达到峰值,为平均值的20倍,98天后米林地震发生;从7月4日到9月7日,地震当年相对功率谱偏离背景值和标准差,持续时间为65天。西藏地区的强震热红外异常表现出与地热资源分布较为一致的特征及特征周期相对较长的特点,为判定西藏地区的震情积累了一些经验。  相似文献   

2019年四川长宁6.0级地震序列时空演化特征及其地震构造环境研究     

宫悦  王宇玺  梁明剑  龙锋  赵敏 《地震》2020,40(4):90-102

地震序列类型能够直观地反映构造应力场环境、 地震构造及孕震环境介质的差异性。 主—余型地震多发生在相对均匀的介质环境, 而前—主—余型地震及震群型地震往往发生在复杂的构造环境。 2019年6月17日四川省宜宾市长宁县发生的6.0级地震余震活动总体呈NW向分布, 其南东段的余震呈相对单一的NW向条带状, 而北西段的余震活动呈现丛集的特征。 两段的地震序列类型也表现出明显的差异性, 南东段地震序列为主—余型, 序列衰减速度较快; 北西段地震序列为震群型, 序列初期衰减非常缓慢, 余震丰富。 此次6.0级地震序列发生在长宁—双河大背斜上, 该复式背斜主要由多个次级褶皱构造和不同走向的伴生断层组成, 结构复杂。 长宁6.0级地震序列的分段性特征表明, 该地震序列不是发生在单一的断裂构造上, 为多个构造级联破裂所导致的复合型地震序列。 此外, 序列北西段余震的深度逐渐变深, 可能预示着该区域受华蓥山断裂带活动的影响, 地震序列对华蓥山断裂带未来地震活动的影响应引起关注。  相似文献   

Inter-comparison of remote sensing platforms for height estimation of mango and avocado tree crowns     

《International Journal of Applied Earth Observation and Geoinformation》2020

To support the adoption of precision agricultural practices in horticultural tree crops, prior research has investigated the relationship between crop vigour (height, canopy density, health) as measured by remote sensing technologies, to fruit quality, yield and pruning requirements. However, few studies have compared the accuracy of different remote sensing technologies for the estimation of tree height. In this study, we evaluated the accuracy, flexibility, aerial coverage and limitations of five techniques to measure the height of two types of horticultural tree crops, mango and avocado trees. Canopy height estimates from Terrestrial Laser Scanning (TLS) were used as a reference dataset against height estimates from Airborne Laser Scanning (ALS) data, WorldView-3 (WV-3) stereo imagery, Unmanned Aerial Vehicle (UAV) based RGB and multi-spectral imagery, and field measurements. Overall, imagery obtained from the UAV platform were found to provide tree height measurement comparable to that from the TLS (R² = 0.89, RMSE = 0.19 m and rRMSE = 5.37 % for mango trees; R² = 0.81, RMSE = 0.42 m and rRMSE = 4.75 % for avocado trees), although coverage area is limited to 1–10 km² due to battery life and line-of-sight flight regulations. The ALS data also achieved reasonable accuracy for both mango and avocado trees (R² = 0.67, RMSE = 0.24 m and rRMSE = 7.39 % for mango trees; R² = 0.63, RMSE = 0.43 m and rRMSE = 5.04 % for avocado trees), providing both optimal point density and flight altitude, and therefore offers an effective platform for large areas (10 km²–100 km²). However, cost and availability of ALS data is a consideration. WV-3 stereo imagery produced the lowest accuracies for both tree crops (R² = 0.50, RMSE = 0.84 m and rRMSE = 32.64 % for mango trees; R² = 0.45, RMSE = 0.74 m and rRMSE = 8.51 % for avocado trees) when compared to other remote sensing platforms, but may still present a viable option due to cost and commercial availability when large area coverage is required. This research provides industries and growers with valuable information on how to select the most appropriate approach and the optimal parameters for each remote sensing platform to assess canopy height for mango and avocado trees.  相似文献   

Estimating fractional cover of crop,crop residue,and soil in cropland using broadband remote sensing data and machine learning     

《International Journal of Applied Earth Observation and Geoinformation》2020

The fractional vegetation cover (FVC), crop residue cover (CRC), and bare soil (BS) are three important parameters in vegetation–soil ecosystems, and their correct and timely estimation can improve crop monitoring and environmental monitoring. The triangular space method uses one CRC index and one vegetation index to create a triangular space in which the three vertices represent pure vegetation, crop residue, and bare soil. Subsequently, the CRC, FVC, and BS of mixed remote sensing pixels can be distinguished by their spatial locations in the triangular space. However, soil moisture and crop-residue moisture (SM-CRM) significantly reduce the performance of broadband remote sensing CRC indices and can thus decrease the accuracy of the remote estimation and mapping of CRC, FVC, and BS. This study evaluated the use of broadband remote sensing, the triangular space method, and the random forest (RF) technique to estimate and map the FVC, CRC, and BS of cropland in which SM-CRM changes dramatically. A spectral dataset was obtained using: (1) from a field-based experiment with a field spectrometer; and (2) from a laboratory-based simulation that included four distinct soil types, three types of crop residue (winter-wheat, maize, and rice), one crop (winter wheat), and varying SM-CRM. We trained an RF model [designated the broadband crop-residue index from random forest (CRRF)] that can magnify spectral features of crop residue and soil by using the broadband remote sensing angle indices as input, and uses a moisture-resistant hyperspectral index as the target. The effects of moisture on crop residue and soil were minimized by using the broadband CRRF. Then, the CRRF-NDVI triangular space method was used to estimate and map CRC, FVC, and BS. Our method was validated by using both laboratory- and field-based experiments and Sentinel-2 broadband remote-sensing images. Our results indicate that the CRRF-NDVI triangular space method can reduce the effect of moisture on the broadband remote-sensing of CRC, and may also help to obtain laboratory and field CRC, FVC, and BS. Thus, the proposed method has great potential for application to croplands in which the SM-CRM content changes dramatically.  相似文献   

一种云端一体化的土地督察遥感监测方法     

孙久虎 《测绘通报》2020,(3):129-133

针对目前土地遥感监测工作中存在的监测频次低和数据现势性差等问题，通过统筹获取国产卫星影像数据提升监测频次，设计了多源遥感影像的空间网格组织和调度方法，改变传统的影像切片发布模式，建立实时影像服务方法，大幅提升了土地督察遥感监测时效。通过在国家土地督察济南局试点应用，研发了云端一体化的土地督察遥感监测服务平台，实践证明基于空间网格的影像组织管理效率优于传统金字塔切片管理模式，有效支撑了违法用地、永久基本农田保护和城市开发边界突破等监测预警，应用成效显著。  相似文献