数字滤波技术在潮汐观测中的应用研究     

闫秦  成方林  郭海  叶颖  王斌 《海洋技术学报》2015,34(4):28-32

潮汐是重要的海洋物理要素。瞬时变化的海面高度信息除了包含潮汐信息外,还包括波浪等高频干扰信息,因此需要对干扰信息进行滤除。如何从获取到的海面瞬时高度变化中提取出潮汐信息就成为一个关键问题。海洋学中通常是通过低通滤波来获取低频的潮汐信息。通过分析常用的3种低通数字滤波的方法,即滑动平均法、快速傅里叶变换法和小波变换法,对3种低通滤波方法应用于潮汐数据处理的效果进行了比较分析,得出滑动平均法在潮汐信息提取中具有较高应用价值的结论。  相似文献   

视觉感受与Markov随机场相结合的高分辨率遥感影像分割法   总被引：2，自引：0，他引：2  

许妙忠  丛铭  万丽娟  解天鹏  朱晓玲 《测绘学报》2015,44(2):198-205

鉴于视觉感受对外界强大的感知与识别能力,模拟视觉神经感知的工作机制,并结合Markov随机场模型,提出一种影像分割方法。首先,分析视觉感知系统的工作机制,将其特性归纳为等级层次性、学习能力、特征检测能力和稀疏编码特性,继而利用小波变换、非监督聚类、特征分析和Laplace分布模拟视觉工作机制,然后结合Markov随机场模型实现高分辨率遥感影像的分割。通过不同卫星的真实遥感影像进行了相关试验。试验结果表明本文提出的方法在高分辨率遥感影像分割任务中有非常良好的表现。  相似文献   

基于小波特征融合的Hyperion影像降维方法     

孙小芳 《测绘工程》2015,(8):11-15

根据影像中地物光谱曲线的小波特征点确定地物识别的合适光谱分辨率,通过融合原先若干窄波段生成具有适合地物识别光谱分辨率的宽波段数据,达到降维高光谱数据的目的。文中对hyperion影像进行坏线和Smile效应去除,经过FLAASH大气校正,得到155个波段。对提取的八类地物的样本平均光谱进行DB4小波分解,计算小波细节系数方差;以小波细节系数信息熵作为特征点,得出不可渗透表面、居民地、水田、裸土4类地物识别适宜光谱分辨率为80nm,其余地物识别适宜光谱分辨率为160nm。以窄波段间的活跃度为指标进行融合,生成降维后的宽波段分别是21个波段和11个波段。8类地物在3尺度和4尺度下的分类结果说明降维影像能满足应用需求,提出的降维方法可行。  相似文献   

基于小波分析的灰色-神经网络组合模型在大坝变形预测中的应用     

沈哲辉  黄腾  葛文  孟庆年 《测绘工程》2015,(11):51-53

监测序列经小波分解后可以得到各层分量。对低频分量采用灰色GM(1,1)模型进行建模预测,对高频分量采用BP神经网络进行建模预测,最后将各分量进行小波重构,得到监测序列的预测值。将预测值分别与没有进行小波分解直接用GM(1,1)模型预测的值和经小波分解的低、高频系数都采用GM(1,1)模型预测的值进行对比,发现经小波分解的灰色-神经网络组合模型预测精度更高。  相似文献   

震前电离层TEC异常探测方法的研究进展     

黄海莎  刘庆元 《测绘与空间地理信息》2015,(1)

介绍了震前电离层TEC异常探测原理的研究进展和主要的异常探测方法,详细介绍了时间序列法、Kalman滤波和小波变换在电离层异常探测中的原理和应用,总结了传统方法和新方法在电离层异常探测的应用发展情况,并分析了每种方法的优势与不足。为未来中国采用电离层异常探测开展地震预测工作提出了建议。  相似文献   

利用小波阈值消噪改进M-W组合周跳探测性能     

戚国宾  甘雨  隋立芬  肖国锐  刘乾坤 《测绘科学技术学报》2015,(1):22-26,31

受伪距噪声的影响,Turbo Eidt法中M-W组合难以探测所有周跳。分析了M-W组合观测量的误差特性,指出伪距误差导致周跳漏检、探测延迟的原因。采用小波阈值消噪方法对M-W组合观测值进行处理,阈值估计使用Visushrink方法可削弱伪距噪声、增加周跳的辨识度。消噪后,周跳会发生扩散,除当前历元外,前后多个历元均会超出阈值,便于探测。实测数据结果表明:经小波消噪后的M-W组合观测值能够准确定位小至1周的所有周跳,避免漏检现象,增强周跳探测的可靠性。  相似文献   

气压对巴伦台钻孔倾斜的影响特征及机制研究     

许璐  邢喜民 《大地测量与地球动力学》2018,38(8):873-876

以巴伦台钻孔倾斜及分量应变辅助观测气压数据为研究对象，运用相关及小波分析研究气压对巴伦台钻孔倾斜的影响特征。结果表明，气压对巴伦台钻孔倾斜影响表现为准线性关系，对NS向的影响大于EW向。气压对NS向影响的显著频段有2 048～8 192、32 768～65 536 min，对EW向影响的显著频段为2 048～8 192 min。探讨了气压对巴伦台钻孔倾斜的影响机制。  相似文献   

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.  相似文献   

Evaluation of nonlinear models for precipitation forecasting     

Abazar Solgi  Vahid Nourani  Mohammad Bagherian Marzouni 《水文科学杂志》2017,62(16):2695-2704

Prediction of factors affecting water resources systems is important for their design and operation. In hydrology, wavelet analysis (WA) is known as a new method for time series analysis. In this study, WA was combined with an artificial neural network (ANN) for prediction of precipitation at Varayeneh station, western Iran. The results obtained were compared with the adaptive neural fuzzy inference system (ANFIS) and ANN. Moreover, data on relative humidity and temperature were employed in addition to rainfall data to examine their influence on precipitation forecasting. Overall, this study concluded that the hybrid WANN model outperformed the other models in the estimation of maxima and minima, and is the best at forecasting precipitation. Furthermore, training and transfer functions are recommended for similar studies of precipitation forecasting.  相似文献   

Likely effects of climate change on groundwater availability in a Mediterranean region of Southeastern Spain          下载免费PDF全文

Hassane Moutahir  Pau Bellot  Robert Monjo  Juan Bellot  Miguel Garcia  Issam Touhami 《水文研究》2017,31(1):161-176

Groundwater resources are typically the main fresh water source in arid and semi‐arid regions. Natural recharge of aquifers is mainly based on precipitation; however, only heavy precipitation events (HPEs) are expected to produce appreciable aquifer recharge in these environments. In this work, we used daily precipitation and monthly water level time series from different locations over a Mediterranean region of Southeastern Spain to identify the critical threshold value to define HPEs that lead to appreciable aquifer recharge in this region. Wavelet and trend analyses were used to study the changes in the temporal distribution of the chosen HPEs (≥20 mm day^?1) over the observed period 1953–2012 and its projected evolution by using 18 downscaled climate projections over the projected period 2040–2099. The used precipitation time series were grouped in 10 clusters according to similarities between them assessed by using Pearson correlations. Results showed that the critical HPE threshold for the study area is 20 mm day^?1. Wavelet analysis showed that observed significant seasonal and annual peaks in global wavelet spectrum in the first sub‐period (1953–1982) are no longer significant in the second sub‐period (1983–2012) in the major part of the ten clusters. This change is because of the reduction of the mean HPEs number, which showed a negative trend over the observed period in nine clusters and was significant in five of them. However, the mean size of HPEs showed a positive trend in six clusters. A similar tendency of change is expected over the projected period. The expected reduction of the mean HPEs number is two times higher under the high climate scenario (RCP8.5) than under the moderate scenario (RCP4.5). The mean size of these events is expected to increase under the two scenarios. The groundwater availability will be affected by the reduction of HPE number which will increase the length of no aquifer recharge periods (NARP) accentuating the groundwater drought in the region. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献