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为研究埕岛海域水下三角洲地形演变,利用1958—2014年间埕岛海域7个不同时期水深点的数据,采用
不同插值方法开展适用性比较,确定选用反距离加权法进行数据插值,生成研究海域范围内7期水深地形图。通过栅格计算对不同时期的水深地形进行研究,分析比较了各个时期的地形特征,总结出区域内地形演变规律。研究表明,埕岛海域内整体地形呈西南高东北低走势,3~12 m 等深线间水下岸坡地带地形最为复杂且变化剧烈,走河期淤积中心不断向东北方向推进,最大淤积厚度超过12 m,废弃后侵蚀中心逐步向岸移动,且后期侵蚀速率明显降低,形成了“陡-缓-陡”的地形特征。 相似文献
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数字水深模型是对海底表面形态的数字化表达,传统的网格数字水深模型存在不能根据海区水深变化情况自动调节内插水深间隔的不足,提出了以深度极限误差作为判断标准,顾及海底地形变化的补深补浅方法,并在此基础上构建了相应的狄洛尼三角网。 实验证明:与传统的最浅点抽稀规则格网方法相比,所提方法更能合理的反映出海底地形的实际变化情况,并明显改善 DDM 精度。 相似文献
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传统潮滩地貌的研究方法难以刻画潮滩的微观地貌特征,地面激光扫描仪(TLS)的应用为潮滩地貌的研究提供了新的切入点,然而目前关于TLS在潮滩地貌研究中鲜有报道。以江苏东灶港海岸一段潮滩地貌为研究对象,基于野外扫描数据,对扫描区域的点云数据进行精度评估,并尝试利用反距离加权插值(IDW)与克里金插值(Kriging)方法构建了潮滩地貌的数字高程模型(DEM)。研究结果表明:(1)通过点云数据构建的DEM数据能够实现潮滩地貌的定量模拟;(2)利用IDW插值可以便捷高效构建潮滩海量数据点的DEM;(3)利用TLS量化短期地貌变化如潮汐沉积旋回效果并不好。本研究可为利用TLS在潮滩微观地貌中的量化研究提供参考。 相似文献
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针对海底地形复杂程度分类问题,在考虑传统水深均值的基础上引入坡度和起伏度两个地形因子作为表征海底地形复杂程度的分类指标并进行量化,对水深数据空间分辨率进行统一,建立包含18种典型海底特征的海底地形复杂度分类库,利用BP神经网络对建立的分类库进行训练学习。为验证该方法的有效性和适用性,选取地形复杂度不同的4块实验区分别采用统计学方法和BP神经网络算法进行海底地形复杂度进行分类,对比发现该方法可以实现海区海底平坦、一般、复杂三种地形的自动识别与分类,并保留实验区海底地形复杂度细节信息。 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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本文在研究多源水深数据构建技术的基础上,分析了张力样条插值算法和“移去-恢复”法的多源水深数据融合处理技术,基于该方法选取实验区,利用多波束、单波束、历史海图等多源水深数据进行高精度海底地形融合试验,并针对多源水深融合技术缺少误差评估的现状,利用split-sample方法对融合结果进行水深不确定性评估,形成融合结果的可靠性空间分布。结果表明该方法无论是在数据稀疏区还是高密度区都达到了较好的融合效果,既保留了高分辨率水深数据的细节信息,又较真实的反映了研究区海底地形特征,且构建的海底地形精度可靠,误差百分比集中在0.5%。本文整套数据融合和结果评估方法可为多源水深数据融合的海底高精度地形构建提供借鉴和参考。 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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Shaoyuan Pan Siquan Tian Xuefang Wang Libin Dai Chunxia Gao Jianfeng Tong 《海洋学报(英文版)》2021,40(8):119-132
Spatial-temporal distribution of marine fishes is strongly influenced by environmental factors. To obtain a more continuous distribution of these variables usually measured by stationary sampling designs, spatial interpolation methods(SIMs) is usually used. However, different SIMs may obtain varied estimation values with significant differences, thus affecting the prediction of fish spatial distribution. In this study, different SIMs were used to obtain continuous environmental variables(water depth, water temperature, salinity, dissolved oxygen(DO), p H,chlorophyll a and chemical oxygen demand(COD)) in the Changjiang River Estuary(CRE), including inverse distance weighted(IDW) interpolation, ordinary Kriging(OK)(semivariogram model: exponential(OKE),Gaussian(OKG) and spherical(OKS)) and radial basis function(RBF)(regularized spline function(RS) and tension spline function(TS)). The accuracy and effect of SIMs were cross-validated, and two-stage generalized additive model(GAM) was used to predict the distribution of Coilia nasus from 2012 to 2014 in CRE. DO and COD were removed before model prediction due to their autocorrelation coefficient based on variance inflation factors analysis. Results showed that the estimated values of environmental variables obtained by the different SIMs differed(i.e., mean values, range etc.). Cross-validation revealed that the most suitable SIMs of water depth and chlorophyll a was IDW, water temperature and salinity was RS, and p H was OKG. Further, different interpolation results affected the predicted spatial distribution of Coilia nasus in the CRE. The mean values of the predicted abundance were similar, but the differences between and among the maximum value were large. Studies showed that different SIMs can affect estimated values of the environmental variables in the CRE(especially salinity).These variations further suggest that the most applicable SIMs to each variable will also differ. Thus, it is necessary to take these potential impacts into consideration when studying the relationship between the spatial distribution of fishes and environmental changes in the CRE. 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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短排列多道反射地震接收缆较短,无水鸟、磁罗经、尾标等定位定深设备,给常规数据处理带来诸如观测系统定义等棘手问题;另外,无定深设备会造成接收缆不同接收段的沉放深度不同,破坏反射数据理论双曲线时距曲线关系。针对短排列多道反射地震数据,本文充分利用现场导航数据,计算实际激发点轨迹,再通过反距离比线性插值算法计算检波点的轨迹坐标,获得整个排列的实际观测系统参数。对因沉放深度不一致造成的扭曲时距曲线反射波,文中利用理论双曲线先计算共中心点道集的理论反射波位置,再推算排列中各接收道不同沉放深度处的静校正量,通过静校正拟合运算,消除接收排列非一致深度引起的反射波同相轴扭曲现象。将上述处理方法应用于南极海域短排列多道反射地震数据,最终获得了高分辨率叠加剖面,为后续地质解释提供了保障。 相似文献