基于噪声随机模型的加权观测融合方法

信息融合技术中,在各局部传感器的有色观测噪声为一阶AR模型的情况下,可以利用观测扩增方法消除有色噪声的影响,得到最优加权观测融合方程,从而实现状态的最优滤波解。对于有色观测噪声为MA或ARMA模型的情况,观测扩增方法不再适用。提出了基于有色观测噪声随机模型级数展开的方法,求解出各局部传感器有色观测噪声的方差,并利用该方差对加权观测融合滤波器进行了构造。通过计算实例证明,该方法不仅适用于观测噪声为AR模型,同时适用于噪声MA或ARMA模型。     

卫星测高问题的球谐级数解法

研究了球界面下卫星测高问题的解法，利用有限逼近方法得到了下列结论：若陆地部分是球冠，则卫星测高问题的解可以转换成关于球谐级数位系统的线性方程组。同时证明了常用的Stokes问题、Dirichlet问题、Neumann问题可以看成卫星测高问题的特殊情况。     

Assessment of the abnormal growth of floating macrophytes in Winam Gulf (Kenya) by using MODIS imagery time series

The objective of this research study is to assess the capability of time-series of MODIS imagery to provide information suitable for enhancing the understanding of the temporal cycles shown by the abnormal growth of the floating macrophytes in order to support monitoring and management action of Lake Victoria water resources.The proliferation of invasive plants and aquatic weeds is of growing concern. Starting from 1989, Lake Victoria has been interested by the high infestation of water hyacinth with significant socio-economic impact on riparian populations.In this paper, we describe an approach based on the time-series of MODIS to derive the temporal behaviour, the abundance and distribution of the floating macrophytes in the Winam Gulf (Kenyan portion of the Lake Victoria) and its possible links to the concentrations of the main water constituencies.To this end, we consider the NDVI values computed from the MODIS imagery time-series from 2000 to 2009 to identify the floating macrophytes cover and an appropriate bio-optical model to retrieve, by means of an inverse procedure, the concentrations of chlorophyll a, coloured dissolved organic matter and total suspended solid.The maps of the floating vegetation based on the NDVI values allow us to assess the spatial and temporal dynamics of the weeds with high time resolution.A floating vegetation index (FVI) has been introduced for describing the weeds pollution level.The results of the analysis show a consistent temporal relation between the water constituent concentrations within the Winam Gulf and the FVI, especially in the proximity of the greatest proliferation of floating vegetation in the last 10 years that occurred between the second half of 2006 and the first half of 2007.The adopted approach will be useful to implement an automatic system for monitoring and predicting the floating macrophytes proliferation in Lake Victoria.     

Development of time series stacks of Landsat images for reconstructing forest disturbance history

Abstract

Forest dynamics is highly relevant to a broad range of earth science studies, many of which have geographic coverage ranging from regional to global scales. While the temporally dense Landsat acquisitions available in many regions provide a unique opportunity for understanding forest disturbance history dating back to 1972, large quantities of Landsat images will need to be analysed for studies at regional to global scales. This will not only require effective change detection algorithms, but also highly automated, high level preprocessing capabilities to produce images with subpixel geolocation accuracies and best achievable radiometric consistency, a status called imagery-ready-to-use (IRU). This paper describes a streamlined approach for producing IRU quality Landsat time series stacks (LTSS). This approach consists of an image selection protocol, high level preprocessing algorithms and IRU quality verification procedures. The high level preprocessing algorithms include updated radiometric calibration and atmospheric correction for calculating surface reflectance and precision registration and orthorectification routines for improving geolocation accuracy. These automated routines have been implemented in the Landsat Ecosystem Disturbance Adaptive System (LEDAPS) designed for processing large quantities of Landsat images. Some characteristics of the LTSS developed using this approach are discussed.     

天津地区Sentinel-1A雷达影像PSInSAR地面沉降监测

利用2015-05—2016-02获取的天津地区23景哨兵-1A(Sentinel-1A)卫星IW模式影像,进行基于地面散射特性保持稳定的高相干点永久散射体干涉测量处理(PSIn SAR),获取了地面沉降速率,分析了重点沉降区域时序形变特征和成因。实验结果表明,天津地区沉降严重区域主要集中在北辰区和大寺镇,结合北辰区沉降速率图和第2、3承压含水组水位降落漏斗等值线图,分析发现地面沉降中心和地下水位漏斗大致吻合,呈现整体向东北方向偏移的趋势,得出造成地面沉降的主导因素可能为超量开采地下水的结论。     

基于时间序列模型的沉降监测预报分析

时间序列模型预测具有可靠性与高效性的特点。本文结合沉降监测工程,采用Matlab进行建模预报分析,分别基于预测模型(AR、MA、ARMA)进行应用。对比自回归模型、滑动平均模型及自回归滑动平均模型预测结果的精度,表明3种模型可预测期连续分布,模型组合可提高预测精度。     

平顶山城区碳环境演变时间序列分析

大气中日益上升的温室气体浓度,已导致温室效应日益增强,从而引发一系列不利的环境与生态后果,并会对世界粮食生产、水资源利用等关系人类生存发展的方面产生重要影响。1994~2014年是平顶山城市化进程不断加快和经济社会高速发展的时期,土地利用、人口、能源消耗和城市植被等影响碳源、碳汇的主要方面也都发生了重大的变化。将1994~2014年河南省平顶山市城区的碳平衡变化情况作为研究对象,计算出碳平衡主要影响因素各自的变化情况并加以分析,得出有关平顶山城区碳环境演变的结论。最后,为促进平顶山城区的碳源碳汇平衡,提出实现城市快速发展过程中低碳效应策略。     

联合区域叠加滤波法与小波变换去除GPS站坐标时间序列噪声

GPS站坐标时间序列中存在的周期性与非周期性误差严重影响了对测站运动特征的分析及其非线性变化的物理机制解释。因此,为削弱噪声的影响,本文首先利用区域叠加滤波法去除了南加利福尼亚地区16个测站时间序列的共模误差,以此削弱时间序列中存在的包括周年和半周年误差在内的周期性误差。为去除滤波后残留的噪声,对滤波后的信号进行静态离散小波变换,提取了周期为半周年以上的信号。结果表明,联合区域叠加滤波法与小波变换对GPS站坐标时间序列进行处理,既能够削弱周期性误差对信号的影响,又能较好地提取测站的非线性运动信号。     

空基下视时序影像瞬时成像模型研究

物方空间的物体随着时间的推移进行着绝对运动,运动导致了相对位置的变化,时间序列影像记录了物方三维空间的动态变化。本文基于下视时间序列影像的动态特性,在共线方程中引入时间元素,提出了空基下视时间序列影像瞬时成像模型,描述了动态“物像”间的瞬时投影关系;针对地表不同类型动态物体,构建了“由像到物”的应用模型,实现了从像方动态特征计算地表物体特征的目的。通过仿真和真实航空下视序列影像的试验与分析,验证了序列影像瞬时成像模型能够定量计算像地动态特征。     

动态最小二乘支持向量机学习算法

针对大样本集的训练问题和动态训练样本的模型更新问题,提出了动态最小二乘支持向量机学习算法。该算法充分利用已建好的模型,逐渐加入新样本,并可删除位于任何位置的非支持向量,避免了矩阵求逆运算,保证了算法的高效率。大坝变形及电离层延迟两个时间序列的预报实例表明,该算法具有计算时间短、预报精度高的特点。