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利用卫星测高技术确定海洋重力场,垂线偏差数据作为导出观测量在实际工作中被普遍采用。利用物理大地测量边值问题的定义以及扰动位在球面边界条件下的解,给出了由垂线偏差计算大地水准面高、重力异常和扰动重力的公式。分析了不同积分计算公式在重力场阶谱表达形式下对垂线偏差误差的抑制作用,也分析了不同积分核函数的变化特性,得出基本结论:在利用卫星测高数据求解海洋重力场时,当以格网化海面垂线偏差数据计算重力场参数时,求解的大地水准面高的有效性和稳定性优于重力异常和扰动重力。 相似文献
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高程异常和垂线偏差是大地测量及空间技术中常用到的一组大地参数.精确计算大洋区这些参数的工作是十分困难的.本文以我国在中太平洋调查的一个海区为例,介绍了用重力法计算洋区高程异常及垂线偏差的基本公式、分区原则、资料来源、数据处理及程序设计等主要内容.讨论了计算误差的主要来源及提高计算精度的基本途径,分析了试算区大地水准面参数的展布特征. 相似文献
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研究了基于EGM2008大地水准面模型的高程传递原理,通过青岛地区已知控制点数据计算得到EGM2008大地水准面模型与我国大地水准面差距,利用EGM2008模型计算高程异常的方法,结合GNSS技术实现高程传递。利用青岛市C级GNSS控制网数据,基于EGM2008模型,采用3种不同的拟合方法,建立了区域高程异常残差场,反演高程异常值与已知控制点高程异常值进行比对。利用青岛市D级GNSS点的数据对构建的格网模型的精度进行检核。结果表明:EGM2008大地水准面模型与我国的大地水准面存在22 cm左右的偏差;基于EGM2008模型的高程传递精度可达厘米级,可用于近海高程传递,几种拟合方法精度相当。 相似文献
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用Geosat高度计数据提取东海大地水准面 总被引：4，自引：1，他引：4
大地水准面是地球重力势等势面,它反映了地球形状及海面重力场异常特征,对大地测量学及海底探矿意义重大.本文利用Geosat高度计50个ERM周期共2.3a的数据,对包括东海区域的20°～40°N,120°～140°E海域进行了大地水准面反演计算.本文采用时间平均处理法有效地抑制了高度计数据中含有的由海洋时变因素引起的高度偏差,并用两种计算模型得到了东海大地水准面.计算出的大地水准面可反映出某些小区域海底特征,但与大尺度海底地形相关较差,这主要是由地壳均衡补偿作用引起的.对计算误差分析得出,采用模型-1和模型-2得出的大地水准面中残留的轨道误差分别为10.8和5.6cm,与OSU91A大地水准面模型偏差分别为37.6和42.2cm,时间平均处理使海洋时变因素引起的海面高度偏差降低了7倍. 相似文献
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联合T/P数据、T/P新轨道数据、Jason-1数据、Jason-1新轨道数据、Jason-2数据、Geosat/GM数据、Geosat/ERM数据、Envisat RA-2数据、ERS-1/ERM和ERS-2/ERM数据,基于EGM2008重力场模型,用相邻测高点大地水准面高度的一次差分求沿轨垂线偏差,然后基于最小二乘原理,采用求最小范数逆的方法,直接解算中国近海及其邻域(0°～42°N,102°～138°E)2′×2′分辨率网格点垂线偏差子午分量和卯酉分量。计算结果与EGM2008模型垂线偏差相比,子午分量的RMS为0.91″,卯酉分量的RMS为0.27″。 相似文献
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星载测高仪可以实时测量从卫星到瞬时海面的距离,对这一距离进行各种误差改正后,就可以用于多种不同的目的。 大地测量学家和海洋学家共同关心的问题是:如何从这一距离信息中提取大地水准面和海面地形。鉴于这两种信息在一定波长上是相互迭加的,因而分离海面地形和大地水准面就变得非常艰巨了。过去人们都是采用从平均海面中减去大地水准面的直接方法来分离的,后来人们又采用整体求解法(即同时确定海面地形,改善重力位模型及减小轨道误差)来分离。但这一问题至今并没有得到完美的解决。本文首先介绍了卫星测高技术的一些发展背景,继而对人们惯用的分离海面地形与大地水准面的方法进行了分析讨论,同时提出了改进海面地形与大地水准面可分性的一些方法。 相似文献
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水深是反映海底地形地貌的最基础要素,对缺失的水深点进行准确的插值能帮助有效地表达海底地形地貌起伏形态。针对海底地形变化复杂的区域,传统的反距离加权插值法存在只考虑样本水深点与待插值水深点之间的距离,而忽略了样本水深点之间的空间相关性的问题。本文提出了一种顾及特征水深点距离重分配的反距离加权插值算法。该算法首先对离散的水深点构建特征水深线,在特征水深线的基础上,提取特征水深线上的特征点作为特征水深点;然后在所有样本水深点到待插值水深点距离之和不变的约束下,提出距离重分配的量化指标;最后构造出一个顾及特征水深点距离重分配的IDW插值算法模型。实验结果表明,在海底地形变化复杂的区域,顾及特征水深点距离重分配的反距离加权插值算法与传统的IDW、自然邻域插值、样条函数插值算法等相比,能有效提高水深点的插值精准度。 相似文献
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Optimizing interpolation of shoot density data from a Posidonia oceanica seagrass bed 总被引：1，自引：0，他引：1
Michele Scardi Lorenzo A. Chessa Eugenio Fresi Antonio Pais & Simone Serra 《Marine Ecology》2006,27(4):339-349
A case study on the optimization of Posidonia oceanica density interpolation, using a data set from a large meadow at Porto Conte Bay (NW Sardinia, Italy), is presented. Ordinary point kriging, cokriging and a weighted average based on inverse square distance were used to interpolate density data measured in 36 sampling stations. The results obtained from different methods were then compared by means of a leave‐one‐out cross‐validation procedure. The scale at which interpolation was carried out was defined on the basis of the Hausdorff dimension of the variogram. Optimizing spatial scale and data points search strategy allowed obtaining more accurate density estimates independently of the interpolation method. 相似文献
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高频地波雷达是海洋环境监测的重要手段，当前已经实现对海流的业务化观测，但是外部因素常引起海流空间探测的不连续性。为解决此问题，尽量保障区域数据的完整性和准确性，本文将BP神经网络技术与空间插值相结合，建立了海流的BP神经网络插值模型，并进行了针对实测数据的缺失插值仿真，通过与反距离权重法和线性插值法插值结果的对比，分析该模型在区域海流大面积缺失、流速整体较大和流速整体较小3个方面的性能。结果表明，BP神经网络插值模型的海流预测效果明显优于其他两种方法，且在流场数据大范围缺失下也取得了良好的效果。 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
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Employing the properties of the affine mappings, a very novel fractal model scheme based on the iterative function system is proposed. We obtain the vertical scaling factors by a set of the middle points in each affine transform, solving the difficulty in determining the vertical scaling factors, one of the most difficult challenges faced by the fractal interpolation. The proposed method is carried out by interpolating the known attractor and the real discrete sequences from seismic data. The results show that a great accuracy in reconstruction of the known attractor and seismic profile is found, leading to a significant improvement over other fractal interpolation schemes. 相似文献