Remote estimation of surficial seafloor properties through the application Angular Range Analysis to multibeam sonar data

The variation of the backscatter strength with the angle of incidence is an intrinsic property of the seafloor, which can be used in methods for acoustic seafloor characterization. Although multibeam sonars acquire backscatter over a wide range of incidence angles, the angular information is normally neglected during standard backscatter processing and mosaicking. An approach called Angular Range Analysis has been developed to preserve the backscatter angular information, and use it for remote estimation of seafloor properties. Angular Range Analysis starts with the beam-by-beam time-series of acoustic backscatter provided by the multibeam sonar and then corrects the backscatter for seafloor slope, beam pattern, time varying and angle varying gains, and area of insonification. Subsequently a series of parameters are calculated from the stacking of consecutive time series over a spatial scale that approximates half of the swath width. Based on these calculated parameters and the inversion of an acoustic backscatter model, we estimate the acoustic impedance and the roughness of the insonified area on the seafloor. In the process of this inversion, the behavior of the model parameters is constrained by established inter-property relationships. The approach has been tested using a 300 kHz Simrad EM3000 multibeam sonar in Little Bay, NH. Impedance estimates are compared to in situ measurements of sound speed. The comparison shows a very good correlation, indicating the potential of this approach for robust seafloor characterization.     

数字地球中影像数据的Zipf-like访问分布及应用分析

在数字地球GlobeSIGht系统中,统计分析不同采集时间尺度的4个系统日志,得出了影像数据瓦片请求均符合幂律分布中的Zipf-like分布的结论。该结论有助于数字地球系统在诸如影像数据存储分布和缓存等方面的性能优化设计和分析。     

中国太阳能热发电站选址模型研究

太阳能热发电技术在我国新世纪能源战略中具有重要地位,太阳能热发电电站位置的合理选择对发电成本有直接影响,涉及到太阳能热发电技术本身、高时空分辨率的太阳能法直辐射分布、土地利用分布、水资源分布、社会经济分布,以及政策税收等众多因素。本文提出了一个太阳能热发电站选址的决策支持系统框架,就其中的太阳能直法辐射调查进行了初步试验。本文依据供需时空平衡原则进一步讨论了多种绿色能源互补的大能源系统运筹问题。     

Characteristics, Formation Periods, and Controlling Factors of Tectonic Fractures in Carbonate Geothermal Reservoirs: A Case Study of the Jixianian System in the Xiong’an New Area, China

As typical carbonate geothermal reservoirs with low porosity in northern China, the Jixianian System in the Xiong’an New Area is the main target for geothermal fluid exploration. The Jixianian System comprises the Gaoyuzhuang, Yangzhuang, Wumishan, Hongshuizhuang, and Tieling formations. The characteristics, formation periods, and controlling factors of reservoir tectonic fractures have been determined based on analyses of outcrops, cores, thin sections, and image logs. The results show that unfilled fractures account for over 87% and most tectonic fractures are high-angle shear fractures with angles concentrated at 40° to 70° and the fracture porosity increases linearly with an increased fracture aperture. Within the same tectonic setting and stress field, the lithology and layer thickness are the dominant factors governing the development of tectonic fractures, which are the most developed in dolomites and thin layers. Tectonic fractures were most likely formed in regions near faults or areas with larger stress gradients. The tectonic fractures in the carbonate geothermal reservoirs are roughly divided into four sets: NNW–SSE and NNE–SSW oriented ‘X’-conjugated shear fractures formed from the Paleozoic to the pre-Yanshanian Movement; NE–SW-oriented shear fractures, formed in episode B of the Yanshanian Movement, occurred at the Early Cretaceous; nearly E–W-oriented tensional fractures formed in the late Yanshanian Movement at the Late Cretaceous to Paleogene, and NEE–SW-oriented shear fractures formed during the Himalayan movement.     

Thematic mapping from remotely sensed data with neural networks: MLP, RBF and PNN based approaches

 Neural networks are attractive tools for the derivation of thematic maps from remotely sensed data. Most attention has focused on the multilayer perceptron (MLP) network but other network types are available and have different properties that may sometimes be more appropriate for some applications. Here a MLP, radial basis function (RBF) and probabilistic neural network (PNN) were used to classify remotely sensed data of an agricultural site. The accuracy of these classifications ranged from 86.25–91.25%. The accuracy of the PNN classification could be increased through the incorporation of prior probabilities of class membership but the accuracy of each classification could also be degraded by the presence of an untrained class. Post-classification analyses, however, could be used to identify potentially misclassified cases, including those belonging to an untrained class, to increase accuracy. The effect of the post-classification analysis on the accuracy of the classification derived from each of the three network types investigated differed and it is suggested that network type be selected carefully to meet the requirements of the application in-hand. Received: 23 March 2000 / Accepted: 9 July 2000     

Petrology and structure of the Palaeoproterozoic (1.9 Ga) Rytky nickel sulphide deposit,Central Finland: a comparison with the Kotalahti nickel deposit

The Palaeoproterozoic (1.9 Ga) Rytky and Kotalahti mafic-ultramafic intrusions are located in the contact zone between the Archaean craton and Proterozoic supracrustal rocks. During the second deformation event (D₂) the surrounding country rocks were subjected to intensive metamorphism and deformation associated with the Svecofennian orogeny; the Archaean/Proterozoic boundary controlled both D₂ thrusting and magma ascent. Emplacement of the Rytky and Kotalahti intrusions took place at the culmination of D₂, as shown by the gneiss inclusions with S₂ schistosity within the intrusions. Overthrusting continued after emplacement, with detached fragments of the bodies incorporated into the Archaean gneisses. During the third deformation event (D₃) the originally subhorizontal intrusions were rotated into a subvertical position, so that they now have their stratigraphic top towards the west. The Rytky intrusion is composed mainly of medium- and coarse-grained lherzolite, websterite and gabbronorite. The nickel deposit with pentlandite as the main nickel mineral is associated with the lherzolite and websterite. The coarse-grained lherzolite, websterite and melagabbro represent the first rocks to form, and they contain the nickel sulphide mineralisation. Country rock contamination, as indicated by high TiO₂, P₂O₅, Rb, Zr and light rare earth element contents (LREE), is most pronounced in the marginal part of the intrusion, which was the first to form. The variation in olivine composition (Fo 78.6-84.77 mole %; Ni 630–2386 ppm) and the metal ratio of the sulphide (Ni/Co 19.3 – 50.3) along with the internal stratigraphy of the intrusion indicate an in-situ process of sulphide ore formation.Editorial handling: P. LightfootAn erratum to this article can be found at     

旅游地学对旅游业可持续发展之积极作用

旅游地学对旅游业可持续发展之积极作用至少可在不断发现更新旅游资源和对旅游资源及其生态环境的监测和保护诸方面，有所作为。     

基于核空间的多光谱遥感图像分类方法

提出了多光谱遥感图像分类方法中解决非线性问题的一种思路。通过引入核空间理论,将在输入空间中不能线性分类的问题映射到一个可以进行线性分类的高维空间,并利用核函数避免了在高维空间中运算的复杂度,较好地解决了非线性分类问题。利用这种思路,本文对一种比较简单的分类算法———自适应最小距离分类方法加以改进,并将其应用于多光谱遥感图像的分类中,提出了一种核函数的选择策略。     

基于无人机光学图像的海流观测方法研究

海流信息在海上航行、海洋资源勘探等方面有着重要的应用,传统的现场和遥感观测方式不能满足大面积、实时观测海流的要求。基于无人机平台的光学海洋遥感技术具有机动灵活、成本低、分辨率高的特点,近年来在海洋环境监测中得到应用。然而,由于小型无人机容易受飞行姿态、太阳耀斑等因素的影响,目前在海流观测方面还不成熟。本文提出了利用小型无人机获取高分辨率海面流场的方法,并分析不同因素对观测结果的影响。首先,对无人机获取的光学海面图像做预处理,消除几何成像和图像噪声等因素的影响,并通过分析图像灰度值均值的变化,减小太阳耀斑对图像的影响;然后,基于三维傅里叶变换和海浪的频散关系反演海流,并将反演结果与浮标实测的海流数据进行对比,验证了该方法的可靠性。其次,结合实验数据详细分析了不同因素对海流反演的影响:在本文的实验条件下(有效波高0.2～1.5m,波浪主波周期3.8～5.7s),当图像空间分辨率为0.15m、反演子图尺寸在波浪主波波长的2～3倍时,海流的反演误差较小;增加图像幅数和提高时间分辨率也有利于提高海流的反演精度。现场观测实验的结果表明,本文提出的无人机观测海流技术可以有效获取海流信息。     

广西近海灾害地质因素及声学反射特征

利用高分辨率地球物理资料及相关历史资料,对北部湾北部的广西近海灾害地质因素进行了地质地球物理解译,识别出海底沙波、海底沙脊、塌陷洼地、冲刷沟槽、浅层气、残积砂体、地层间断、埋藏丘、埋藏古河道等多种灾害地质因素.根据它们出现的频率、规模及声学特征可知:浅层气和埋藏古河道是广西近海最为发育的灾害地质因素,其对海洋工程的施工与建设有较大的危害性.