基于EEMD和ARIMA的海温预测模型研究

类型丰富、时空分辨率高的海洋探测数据,为信号分解和机器学习算法的应用提供了可能。本文针对如何建立有效的海温预测模型这一问题,使用高时空分辨率的海表温度(SST)融合产品,引入信号处理领域的集合经验模态分解(EEMD)和机器学习领域的自回归积分滑动平均模型(ARIMA)。首先利用最适于分解自然信号的EEMD方法,将海温数据分解成多个确定频率的序列;再利用ARIMA分别对各个频率的序列进行预测,最后将各个序列的预测结果进行组合。该方法在丰富数据的支撑下,比以往直接使用海温数据所建立的预测模型精度更高,为更好地进行海温预测提供了新方法。     

基于无人机多源遥感数据海岛植被叶面积指数协同反演研究

无人机多源遥感数据的获取、融合以及应用是当今研究的热点和难点。文中以城洲岛为例,针对海岛特殊的地理生态环境,获取无人机多源遥感数据。结合无人机多光谱遥感数据定量分析各遥感植被指数与植被叶面积指数(Leaf Area Index, LAI)的响应关系,构建单因子遥感反演模型;基于无人机激光LiDAR点云提取海岛植被冠层高度模型(Canopy Height Model,CHM),并将其作为自变量引入到多源统计回归分析中,从而构建多源遥感数据协同反演模型,对区域尺度下海岛叶面积指数(LAI)进行估算,开展验证和精度评价。结果显示,加入植被冠层高度因子的协同反演模型的判定系数R2为0.92,绝对平均误差系数为12.29%,预测精度要优于单因子反演模型(判定次数R2为0.86,绝对平均误差系数19.95%)。研究表明,加入了植被冠层高度因子的协同反演模型能在一定程度上提高乔木植被LAI的预测精度。实践证明,无人机多源遥感技术在生态学定量研究中具有巨大的潜力和广阔的应用前景。     

长江口外潮汐精细化模型研究与精度分析

长江口外海上测量除受风浪影响较大外,最重要的问题是潮位控制非常困难。文中简要阐述了开展长江口外潮汐精细化模型研究的方法,介绍了利用潮汐精细化模型对长江口外航路任意点进行潮汐预报的方法,并通过实测数据进行了精度分析,提出了建议。     

一种基于点云提取微地形对象的方法

在分析微地形特点以及现有网格DEM在表述微地形中存在的不足的基础上,提出了面向对象的数字高程模型,给出了该模型的形式化描述和以点云为数据源构建面向对象数字高程模型过程中采用的对象边界的识别、特征保持的点云疏化、基于属性近似的网格约化及对象识别等关键步骤的方法。并以实例证明了此过程的可行性。     

测绘职业教育培养模式的探索与实践

从测绘科学的发展、社会需求和职业教育的特点等方面,介绍了现代测绘背景下测绘人才培养所出现的问题,分析了测绘职业教育的结构,提出了测绘职业教育人才的培养模式。     

Static performance of power-augmented ram vehicle model on water

An experimental parametric study of a novel air-assisted platform-type model called power-augmented ram vehicle is described. The zero-speed regimes of the model over the water are investigated. The recovered thrust, pressure underneath the platform, and the model attitude are recorded for variable system geometry, loading conditions, and propulsor thrust. The stern flap under the model platform provides an effective mechanism for controlling the thrust recovery and the air-jet-induced lift. Unstable behavior of the model is found at sufficiently high levels of the propulsor thrust.     

Characteristics of developing waves as a function of atmospheric conditions,water properties,fetch and duration

For any specific wind speed, waves grow in period, height and length as a function of the wind duration and fetch until maximum values are reached, at which point the waves are considered to be fully developed. Although equations and nomograms exist to predict the parameters of developing waves for shorter fetch or duration conditions at different wind speeds, these either do not incorporate important variables such as the air and water temperature, or do not consider the combined effect of fetch and duration. Here, the wind conditions required for a fully developed sea are calculated from maximum wave heights as determined from the wind speed, together with a published growth law based on the friction velocity. This allows the parameters of developing waves to be estimated for any combination of wind velocity, fetch and duration, while also taking account of atmospheric conditions and water properties.     

The new wave overtopping database for coastal structures

Significant effort has been made to generate a homogeneous database on wave overtopping consisting of more than 10,000 irregular wave overtopping tests from more than 160 independent projects or test series, each described by means of 31 parameters. Many coastal structures, including dikes, rubble mound breakwaters, berm breakwaters, caisson structures and combinations have been considered and have been schematised for inclusion in the database. All these overtopping tests are represented by over 300,000 numbers in the database.     

珠江口二类水体水色三要素的优化反演

根据2003年1月份珠江口实测资料获得了适合该海域的相关参数,建立了适用于该海域的二类水体水色三要素优化反演模型,同步优化反演得到了与2003年1月25～26日实测站点相对应的2003年1月29日的SeaWiFs图像像元点的水色三要素,反演与实测水色三要素的平均相对误差分别为：叶绿素14．9％,悬浮泥沙12．1％,黄色物质13．6％。研究结果说明本研究建立的优化反演模型比较适用于珠江口二类水体水色三要素的反演,且具有较高的反演精度。