Teledyne Benthos TTV-301声学深拖系统在海底微地形地貌调查中的应用

介绍Teledyne Benthos TTV-301声学深拖系统的构成、海上作业模式以及声学数据获取方式,以南海某海域实测声学数据为例,对获取的多波束水深数据、侧扫声呐数据、浅地层剖面数据进行精细处理,获取高质量的水深图像、高分辨率的侧扫声呐图像和高精度的浅地层剖面图像。对同一海底微地形微地貌在不同声学影像上的反射标识进行对比分析,建立声学3D模型,形成海底浅表层的立体探测。实验结果验证了声学深拖系统在海底微地形地貌调查中的有效性与可行性,并可取得理想的效果。     

探测海底内部地质构造的浅地层剖面系统

海底表层探测可以使用诸如水下摄像、侧扫声呐等水下特种设备实现,但海底内部形态和构造就无法直接获取,这可怎么办呢?为了解决这一难题,一种名为浅地层剖面系统的设备应运而生,就像医学中的光学影像可以探测身体内部秘密一样,该设备可以探测海底内部秘密.     

多波束与侧扫声呐高质量测量信息获取与叠加

正多波束声呐和侧扫声呐分别是目前获取海底地形与地貌图像最为有效的设备。多波束声呐可以同时获得海底测深地形与分辨率较低的海底图像,侧扫声呐可以获取高分辨率但位置精度较低的海底图像。为了准确获取海底精细的地形地貌信息,本文分别从多波束测深数据处理、多波束声呐图像处理、侧扫声呐图像处理、测深地形与侧扫声呐图像的叠加4个方面开展研究,最终得到     

侧扫声呐图像精处理及目标识别方法研究

侧扫声呐(side scan sonar ,SSS)系统,作为水下地貌图像的获取设备,因价格低廉、分辨率高等优点在海洋工程、水下目标探测和识别等领域得到了广泛的应用.而目前SSS水下目标探测和识别均依靠人工判读,效率低下且精度难以保证.据此,论文开展了侧扫声呐数据精处理及目标识别方法研究.     

声学深拖系统在海底冷泉调查中的应用

结合冷泉区天然气羽状流气柱的特征和已有的探测成果,文中使用新型的声学深拖在疑似冷泉点附近开展试验性调查。利用搭载在深拖上的高分辨率侧扫声呐和Chirp型浅地层剖面仪及多波束系统获取冷泉点附近的侧扫声呐数据、海底浅部地层剖面数据及多波束水体数据。3个疑似冷泉在侧扫声呐图像上呈现明显的亮斑,多波束水体数据可探测冷泉并确定冷泉位置,在浅地层剖面数据上可见清晰的声学反射空白带,指示天然气水合物的运移通道,同时在冷泉点3附近还发现一个新的冷泉异常点。研究结果表明,采用深拖作业,结合多种声学技术手段,可对冷泉目标物进行立体声学探测,为冷泉的快速勘查与识别定位提供科学可靠的技术依据,验证先前调查手段和分析方法的正确性。     

侧扫声呐识别沉船影像的迁移学习卷积神经网络法

侧扫声呐海底沉船图像识别是水下障碍物核查和失事船只搜救中的一项重要工作.针对传统侧扫声呐图像人工判读存在效率低、耗时长、资源消耗大及主观不确定性强和过分依赖经验等问题,本文尝试引入卷积神经网络的方法,同时考虑到侧扫声呐沉船图像属于小样本数据集,提出一种基于迁移学习的卷积神经网络侧扫声呐沉船图像自动识别方法.通过归一化处...     

侧扫声呐数据采集与地貌图像构建

针对水下航行器基于地形匹配实现自主导航时需要在线提取环境地形特征的需求,本文重点研究侧扫声呐实时数据采集与地貌图像构建方法。根据侧扫声呐的工作原理及其JSF文件格式,提取侧扫声呐扫描波束所对应的80数据帧,并完成数据解析;建立声呐扫描声强与灰度级转化模型,并构建环境地貌声学图像;通过海试试验结果与侧扫声呐专用软件所生成的地貌图像对比,验证本文方法的有效性和可行性。     

近海人工鱼礁水下物理状态探测与评估

掌握人工鱼礁水下物理状态是评估鱼礁效益的关键条件.传统调查方法存在效率低、信息不完整等缺陷,无法满足人工鱼礁精准监测的要求.该文利用多波束测深声纳系统获取礁区高精度数字高程模型(digital elevation model,DEM),结合地理信息系统(geographic information system,GIS...     

不同型号侧扫声呐分辨能力和扫宽能力的比较分析

侧扫声呐是海洋科学调查中常用的仪器设备,针对此类声学探测设备出台相关检测、检定等计量化的标准势在必行。本文介绍了侧扫声呐的工作原理和技术参数,针对侧扫声呐分辨能力和扫宽能力这两个性能指标,提出了一种评价方法。最后通过海上试验,对比分析了3种常用的侧扫声呐仪器的分辨能力和扫宽能力,为侧扫声呐系统的选用和引进提供参考。     

海底地形测量技术现状及发展趋势

简要回顾了海底地形测量技术的发展历史;详细介绍了船基声呐、机载激光、海岸带一体化测量海底地形技术及3种反演海底地形技术,呈现了海底地形的立体、高效、高精度、高分辨率获取现状。并展望了海底地形测量发展趋势,认为研制超宽覆盖、高精度、高分辨率、轻便型多波束测深系统和研究声速影响改正模型、测深数据滤波方法及海底地形表达是未来声呐测深领域的核心工作,无人船测量将会成为一种重要的作业模式,机载激光雷达测深、基于声呐图像的海底地形恢复及深拖测量发展潜力巨大。     

Evolution of the Earth's principal axes and moments of inertia: the canonical form of solution

 Harmonic coefficients of the 2nd degree are separated into the invariant quantitative (the 2nd-degree variance) and the qualitative (the standardized harmonic coefficients) characteristics of the behavior of the potential V ₂(t). On this basis the evolution of the Earth's dynamical figure is described as a solution of the time-dependent eigenvalues–eigenvectors problem in the canonical form. Such a canonical quadratic form is defined only by temporal variations of the harmonic coefficients and always remains finite, even within an infinite time interval. An additional condition for the correction or the determination of temporal variations of the 2nd degree is obtained. Temporal variations of the fully normalized sectorial harmonic coefficients are estimated in addition to ˙Cˉ ₂₀, ˙Cˉ ₂₁, and ˙Sˉ ₂₁ of the EGM96 gravity model. In addition, a non-linear hyperbolic model for Cˉ _2m (t), Sˉ _2m (t) is constructed. The trigonometric form of the hyperbolic model leads to the consideration of the potential V ₂(ψ) instead of V ₂(t) within the closed interval −π/2≤ψ≤+π/2. Thus, it is possible to evaluate the global trend of V ₂(t), the Earth's principal axes and the differences of the moments of inertia within the whole infinite time interval. Received: 25 September 1998 / Accepted: 28 June 2000     

Analysis of inversion errors of ionospheric radio occultation

The retrieved electron density profile of ionospheric radio occultation (RO) simulation data can be compared with the background model value during the simulation and the inversion error can be obtained exactly. This paper studies the inversion error of ionospheric RO through simulation. The sources of the inversion errors are analyzed. The impacts of measurement errors, such as the errors in phase measurements and satellite orbits, are very small and can be neglected. The approximation of straight-line propagation introduces errors at the height of the F1 layer under solar maximum condition. The spherical symmetry approximation of the electron density distribution is found to be the main source of the inversion error. The statistical results reveal some characteristics of the inversion errors. (1) The relative error increases with enhanced solar activity. (2) It is larger in winter than in equinox season, and it is smallest in summer. (3) For all seasons, it is smaller at middle latitude than at other latitudes. (4) For all seasons and geomagnetic latitudes, it is smaller at daytime than at other times. The NmF2 of the ROs from COSMIC are compared with the measurements of ionosondes, and the relative differences show the same dependencies on season, geomagnetic latitude and local time, as the relative errors of the simulated ionospheric ROs.

Prioritisation of sub-watersheds based on earth observation data of agricultural dominated northern river basin of India

The Upper Tons River Basin of North India has been selected for prioritisation of sub-watersheds (SW) based on morphometric parameters with respect to groundwater derived from topographic sheets and CARTOSAT data. There are 10 SW have been delineated in the region, high stream frequency (F_s) values of SW (1–5) and SW-9 indicated the occurrence of steep slopes, less permeable rocks, greater runoff, less infiltration possibility. Further, these regions have been predicted as poor groundwater potentialities. SW-2 has been identified as poorest groundwater potential zone, whereas SW-4 and SW (6–8) regions possess good permeable bed rocks. The Drainage density (D_d) map demonstrated that the middle south-west region possesses higher D_d whereas northeastern regions contain lower D_d. Further, the areal parameters indicate elongated shape of the basin, hilly region has moderate to steeper ground slope. The outcomes of work have potential to manage groundwater and to ameliorate the flash flood and droughts.     

接收机天线相位中心改正对IGS/IGMAS站的影响

针对天线相位中心改正影响GPS数据解算以及处理软件不能识别接收机天线类型的问题,该文提出了利用近似型号的天线进行数据处理的方法。首先利用IGS站精确确定天线相位中心改正对数据解算造成的影响,再利用IGMAS站验证方法的可靠性。该文选取部分IGS、IGMAS站的数据,利用GAMIT软件进行试验并分析。结果表明,当不使用天线相位改正模型时,增大了单天基线解的NRM_S值,并增加15.5%的基线误差,对精密定位能带来平均2cm的影响;当将处理软件不识别的天线换成近似能识别的天线时,基线解效果要比不使用天线改正效果好,水平和垂向的定位精度均在3.9mm左右,比使用原装能识别天线的定位精度稍差。该方法既保证了精度,也较为简单快捷。     

Accuracy of GPS-derived relative positions as a function of interstation distance and observing-session duration

 Ten days of GPS data from 1998 were processed to determine how the accuracy of a derived three-dimensional relative position vector between GPS antennas depends on the chord distance (denoted L) between these antennas and on the duration of the GPS observing session (denoted T). It was found that the dependence of accuracy on L is negligibly small when (a) using the `final' GPS satellite orbits disseminated by the International GPS Service, (b) fixing integer ambiguities, (c) estimating appropriate neutral-atmosphere-delay parameters, (d) 26 km ≤ L ≤ 300 km, and (e) 4 h ≤T ≤ 24 h. Under these same conditions, the standard error for the relative position in the north–south dimension (denoted S _n and expressed in mm) is adequately approximated by the equation S _n =k _n /T ^0.5 with k _n =9.5 ± 2.1 mm · h^0.5 and T expressed in hours. Similarly, the standard errors for the relative position in the east–west and in the up-down dimensions are adequately approximated by the equations S _e =k _e /T ^0.5 and S _u =k _u /T ^0.5, respectively, with k _e =9.9 ± 3.1 mm · h^0.5 and k _u =36.5 ± 9.1 mm · h^0.5. Received: 5 February 2001 / Accepted: 14 May 2001     

Fractal characterization of the spatial distribution of geological point processes

Geological point processes can be used to model point patterns occurring frequently in a wide variety of geoscience fields, including the study of mineral deposits, oil producing wells, earthquakes, and landslides. Characterization of the spatial distribution of GPP has implications for understanding the properties of the underlying geological processes and events. Three examples of GPP dealing with (1) metallic mineral deposits, (2) oil producing wells, and (3) aftershocks of the Wenchuan earthquake (on 12 May 2008, magnitude 8.0) are presented to illustrate that (1) the spatial distribution of geological point processes generally shows clustering implying rejection of the Poisson model because L(r) > L_Pois(r); (2) the clustering statistics of the underlying geological processes are fractal; and (3) the size distribution of geological point processes is scale invariant. These results indicate existence of a fundamental law concerning the fractal nature of the point distributions generated by geological point processes.     

Impact of land-cover layout on particulate matter 2.5 in urban areas of China

ABSTRACT

Urbanization in China is closely connected with ambient particulate matter 2.5 (PM_2.5). However, the potential for altering PM_2.5 through the urban landscape characteristics is uncertain. In this study, we analyzed the urban PM_2.5 pollution situation for 2014–2016 and investigated the impact of landscape factors on urban PM_2.5 in China at the city level. All the prefecture-level cities were stratified by urban population size into small (<500,000), medium (500,000–1,000,000), and large (>1,000,000), and the other second-level administrative cities were assigned as ‘other’ cities. The multivariate regression model including both urban landscape factors and social-economic variables explained 70.0%, 32.8%, 19.2%, and 12.4% of the arithmetic mean PM_2.5 concentration (AMC-PM_2.5) for the other, small, medium, and large cities, respectively. With regard to the configuration of land cover, agricultural activity is a major contributor of PM_2.5 pollution, for which the explanatory power ranged from 7.6% (for the large cities) to 64% (for the other cities). In addition, grassland aggregation also has a limited but negative effect on urban PM_2.5 pollution, despite the negligible effect on dry deposition. Overall, these findings likely reflect the interaction between urban air quality and urbanization, and will have implications for air quality control strategies.     

Simulation of peri-urban growth dynamics using weights of evidence approach

The study aims to simulate the peri-urban growth dynamics in a growing region of India using Weights of Evidence (WOE) based cellular automata model. The growth process was expressed as a function of four causative variables corresponding to which seven data layers were generated in a Geographic Information Systems environment. The model was calibrated for the period 2000–2005 using Kappa indices and fuzzy set theory based two way comparison method. The Kappa value was 0.7, while the value of K_location and K_histo were 0.81 and 0.93, respectively. The fuzzy similarity values increased for small to large neighbourhood sizes which showed that the model was able to simulate the contiguous and dense growth. However, for dispersed and isolated growth the model showed less accuracy. The model was validated for period 2005–2010 and revealed a Kappa value of 0.88, while value of K_location and K_histo were 0.91 and 0.96, respectively.     

Estimating the parameters of forest inventory using machine learning and the reduction of remote sensing features

Locally computed statistics of image texture and a case-based reasoning (CBR) system were evaluated for mapping of forest attributes. Cluster analysis was preferred to regression models, as a pre-selection method of features. The best stand-based accuracy using satellite sensor images was 74.64 m⁻³ ha⁻¹ (36%) RMSE for stand volume, 1.98 m⁻³ ha⁻¹ a⁻¹ (49%) for annual increase in stand volume, where κ = 0.23 for stand growth classes and κ = 0.41 for dominant tree species in stands. The top pixel-based accuracy using orthophotos was 76.54 m⁻³ ha⁻¹ (41%) RMSE for stand volume, 1.87 m⁻³ ha⁻¹ a⁻¹ (44%) for annual increase in stand volume, where κ = 0.24 for stand growth classes and κ = 0.38 for dominant tree species in stands. Mean saturation in 30 m radius was the most useful feature when orthophotos were used, and standard deviation of Landsat ETM 6.2 values in 80 m radius was the best when satellite sensor images were used. The most valuable feature components (radii, channels and local statistics) for orthophotos were: 30 m kernel radius, lightness and the mean of pixel values; for satellite sensor images: 80 m kernel radius, near-infrared channel (ETM 4) and the mean of pixel values. Locally computed statistics.