共查询到16条相似文献，搜索用时 171 毫秒
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多波束数据的海底数字地形模型构建 总被引：11，自引：0，他引：11
提出大批量多格式原始多波束数据的DTM构建方法，以满足大区域、大比例尺海底地形制图的需要。在多种格式原始多波束数据接口和系统内部标准数据结构的基础上，通过对数据文件、数据种类和数据运算量的有效组织管理，实施边读入、边权重配赋的网格插值，分析了高斯、指数和距离平方反比权重函数的适用性，及最小值、最大值和平均值的实用性。在权重配赋网格插值基础上，提出分形fBM和张力样条配合使用的方程式插值方法，保证DTM数据的有效外延和地形分辨。整套算法效率高，并能有效保证DTM的精度，对存储在外部介质的数据遍历一次即可完成网格插值。 相似文献
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探讨了多波束测量和三维可视化技术在海洋中的应用。多波束测量系统产生的海量探测数据，为数据可视化和数据分析技术的发展创造了机会。通过可视化技术可以在不降低原始数据质量的情况下，进行多源数据的融合显示。对DTM数据进行光照、明暗和三维处理，可以创造一种直观、易于理解的可视化效果。将反映物质属性的信息作为假彩色纹理，叠加到地形之上，在交互式分析工具的支持下，可以使三维可视化技术在海洋地质、海洋环境、海洋渔业和海洋工程中得到广泛的应用。 相似文献
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CUBE算法及其在多波束数据处理中的应用 总被引：5，自引：0，他引：5
阐述了一种基于表面生成的多波束数据处理方法——CUBE(Combined Uncertainty and Bathymetry Estimator)算法,用该方法可以对观测区域网格节点"真实"水深及相关误差进行估计。与从测量水深中选择出"最佳"数据的手工交互方式的多波束数据编辑手段不同,CUBE算法具有很强的抗差性和较高的效率,适合于实时多波束数据处理。对南海某测区多波束数据处理结果表明,在没有人工干预的情况下,利用CUBE算法去噪生成的海底DTM图与手工编辑生成的相当吻合。CUBE算法和手工编辑方法综合对比得出,CUBE算法能够很好地保留水深地形细节,在计算效率、误差评估、实时处理等方面比手工编辑方法具有较大的优势。 相似文献
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基于GIS空间分析的海底表层沉积物粒度分布特征插值研究 总被引：3，自引：0，他引：3
为了对比研究不同空间插值方法在沉积物粒度空间分布表述上的精度及适用性,在2004年11月荣成宁津小型海湾-黑泥湾综合调查的基础上,探讨了表层沉积物粒度参数的空间插值,比较了IDW(反距离加权法)、Kriging(克里金插值法)、Spline(样条插值法)与NN(自然邻域法)4种GIS空间分析方法的特征、差异及实效性,并对影响插值结果准确性的因素进行分析。结果显示,在黑泥湾表层沉积物粒度结果的空间插值计算中,从插值准确性和空间表达能力两方面考虑,IDW,Spline,Kriging和NN中以IDW法较为适宜,但要考虑到"牛眼效应"的出现会与局部实际情况存在差异;Kriging法和NN法的插值结果准确性较高,但其空间表达能力稍逊;Spline法在近岸带表层沉积物粒度特征插值中的应用性相对较差。海洋调查要素空间分布的内在规律性是控制插值结果的主要因素,表层沉积物分布以长期稳定的潮流、地形特征为主导因素,呈现由岸向海条带状分布的特征。数据均匀分布区域的插值结果要优于边界区和突变区;另外,在选取的3个观察尺度上,不同插值方法的误差均与野外取样网格间距呈显著线性正相关。 相似文献
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In this paper, the generalised two-dimensional differential transform method (DTM) of solving the time-fractional coupled KdV equations is proposed. The fractional derivative is described in the Caputo sense. The presented method is a numerical method based on the generalised Taylor series expansion which constructs an analytical solution in the form of a polynomial. An illustrative example shows that the generalised two-dimensional DTM is effective for the coupled equations. 相似文献
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黄海渔业资源密度空间插值方法的比较研究 总被引：2，自引：0，他引：2
空间插值是渔业生态学研究,特别是海洋生态系统模型构建中的常用工具。为找到适合黄海渔业资源密度的插值方法,本文对四种常用的空间插值方法进行了比较研究。四种插值方法分别为反距离加权（Inverse distance weighted,IDW）、全局多项式（global polynomial interpolation,GPI）、局部多项式（local polynomial interpolation,LPI）和普通克里格（ordinary kriging,OK）。采用交叉验证分析（cross-validation diagnostic）确定不同插值方法的准确度。同时,结合渔业资源密度空间分布的可视化表达,比较不同插值方法结果的优劣。结果表明,原始的生物学数据具有典型的非正态分布特征,对数转化方法能让其显著地接近或符合正态分布。四个调查阶段中,指数模型在2014年8月和10月为最佳半方差函数,2015年1月和5月数据具有明显的纯块金效应。配对样本T检验表明,预测数据和实测数据之间没有显著差异（P>0.05）。交叉验证结果表明,OK在2014年10月插值效果最好,IDW在剩余的三个航次表现最佳,GPI和LPI表现效果不佳。OK在空间分布的可视化表达方面效果最好,既不像IDW一样有较多的“牛眼”效应,也不像GPI和LPI一样具有过多的平滑效果。然而,纯块金效应的存在有时会影响OK的应用。综上所述,我们推荐操作简单且处理快速的IDW作为黄海渔业资源密度常规的插值方法。 相似文献
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This article evaluates different spatial interpolation methods for mapping submerged aquatic vegetation (SAV) in the Caloosahatchee Estuary, Florida. Data used for interpolation were collected by the Submersed Aquatic Vegetation Early Warning System (SAVEWS). The system consists of hydro-acoustic equipment, which operates from a slow-moving boat and records bottom depth, seagrass height, and seagrass density. This information is coupled with geographic location coordinates from a Global Positioning System (GPS) and stored together in digital files, representing SAV status at points along transect lines. Adequate spatial interpolation is needed to present the SAV information, including density, height, and water depth, as spatially continuous data for mapping and for comparison between seasons and years. Interpolation methods examined in this study include ordinary kriging with five different semivariance models combined with a variable number of neighboring points, the inverse distance weighted (IDW) method with different parameters, and the triangulated irregular network (TIN) method with linear and quintic options. Interpolation results were compared with survey data at selected calibration transects to examine the suitability of different interpolation methods. Suitability was quantified by the determination coefficient (R2) and the root-mean-square error (RMSE) between interpolated and observed values. The most suitable interpolation method was identified as the one yielding the highest R2 value and/or the lowest RMSE value. For different geographic conditions, seasons, and SAV parameters, different interpolation methods were recommended. This study identified that kriging was more suitable than the IDW or TIN method for spatial interpolation of all SAV parameters measured. It also suggested that transect data with irregular spatial distribution patterns such as SAV parameters are sensitive to interpolation methods. An inappropriate interpolation method such as TIN can lead to erroneous spatial representation of the SAV status. With a functional geographic system and adequate computing power, the evaluation and selection of interpolation methods can be automated and quantitative, leading to a more efficient and accurate decision. 相似文献
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This article evaluates different spatial interpolation methods for mapping submerged aquatic vegetation (SAV) in the Caloosahatchee Estuary, Florida. Data used for interpolation were collected by the Submersed Aquatic Vegetation Early Warning System (SAVEWS). The system consists of hydro-acoustic equipment, which operates from a slow-moving boat and records bottom depth, seagrass height, and seagrass density. This information is coupled with geographic location coordinates from a Global Positioning System (GPS) and stored together in digital files, representing SAV status at points along transect lines. Adequate spatial interpolation is needed to present the SAV information, including density, height, and water depth, as spatially continuous data for mapping and for comparison between seasons and years. Interpolation methods examined in this study include ordinary kriging with five different semivariance models combined with a variable number of neighboring points, the inverse distance weighted (IDW) method with different parameters, and the triangulated irregular network (TIN) method with linear and quintic options. Interpolation results were compared with survey data at selected calibration transects to examine the suitability of different interpolation methods. Suitability was quantified by the determination coefficient (R2) and the root-mean-square error (RMSE) between interpolated and observed values. The most suitable interpolation method was identified as the one yielding the highest R2 value and/or the lowest RMSE value. For different geographic conditions, seasons, and SAV parameters, different interpolation methods were recommended. This study identified that kriging was more suitable than the IDW or TIN method for spatial interpolation of all SAV parameters measured. It also suggested that transect data with irregular spatial distribution patterns such as SAV parameters are sensitive to interpolation methods. An inappropriate interpolation method such as TIN can lead to erroneous spatial representation of the SAV status. With a functional geographic system and adequate computing power, the evaluation and selection of interpolation methods can be automated and quantitative, leading to a more efficient and accurate decision. 相似文献