A Method for Automatically Selecting Aids to Navigation Based on their Spatial Influence Domains

To address the limitations of manually selecting aids to navigation (AtNs) on charts, a method for automatically selecting AtNs based on their spatial influence domains (SIDs) is proposed. First, the associations between the spatial attributes of an AtN are analyzed. Second, an SID of the AtN is defined, and a model of the SID is constructed based on the associations between the spatial attributes. Third, the importance of the location of the AtN is weighted based on the SID model. Fourth, an algorithm to automatically select AtNs based on the maximum coverage of the SIDS of preselected AtNs is developed. Finally, several AtNs are selected automatically using the algorithm. The experimental results demonstrate that (1) the proposed method can automatically select AtNs and the results comply with the requirements; (2) the automatic selection can eliminate the human-induced errors or the inconsistent results of manual selections from different operators; and (3) the efficiency of the proposed method is higher than that of current manual methods.     

基于无人船的大洋中尺度涡观测系统展望

中尺度涡在大洋中普遍存在,研究发现其能量比大尺度海洋环流的能量大一个量级,在海洋物质能量输运和全球气候变化中起着重要的作用。受观测条件限制,目前对中尺度涡的观测主要通过卫星高度计实现,只能从海面高度来推算中尺度涡大小、分布、强度及其伴随的水体和能量输送,而卫星高度计对中尺度涡垂直结构特征认识不足,也导致了对中尺度涡所引起的上层海洋能量、热量输送估计误差偏大。目前对中尺度涡三维结构观测认识不足,展望未来将会出现基于无人船平台的大洋中尺度涡三维结构自动观测系统,该平台将集成自动水下剖面观测功能等先进技术,以便观测中尺度涡的垂直结构特征及其时空变化特征,进而可对中尺度涡带来的物质和能量输送进行系统认识。     

基于弱光栅技术的地面沉降自动化监测系统

光纤监测技术具有分布式、精度高等特点,在地面沉降监测中具有独特优势。但受限于监测成本较高与监测环境复杂,目前地面沉降光纤监测多通过人工采集数据,限制了在特殊环境变化情况下地面沉降的实时信息获取。文章在地面沉降钻孔全断面光纤监测技术的基础上,设计并建立了基于弱光栅技术的地面沉降自动化监测系统。该监测系统利用弱反射光栅、时分复用、物联网和数据库等技术,通过4G无线通信手段实现了地面沉降在线自动化监测和远程数据实时采集,并通过客户端系统软件实现数据的存储、查询和分析。将其应用到衡水地区地面沉降监测中,结果表明:钻孔内土层压缩变形主要发生在以黏性土为主的隔水层（Ad2、Ad3、Ad4）;受季节性地下水开采的影响,钻孔100～400 m深度范围内砂土含水层存在波动变化,在监测期内,冬季略回弹,随后春季地下水开采量增大,地下水位下降,土层呈现压缩趋势。监测结果验证了该系统的可行性与准确性,使得整个地面沉降监测流程趋于自动化、规范化和低成本化,具有广泛的应用前景。     

区域自动气象站蓄电池异常状态判别方法

针对天津市一种常见的CAWS600型区域自动气象站对其供电及功耗进行了详细分析,利用对电池放电特性曲线的归一化处理,得到了针对12V38AH铅酸蓄电池的剩余容量估算方法,同时利用该站蓄电池工作电压的统计规律,提出了针对蓄电池工作电压的极值判定、时间/空间一致性质量控制方法,并对2017年逐10min观测数据进行检验。检验结果显示,文章提出的质量控制方法可以有效识别出蓄电池异常站点,针对2017年个站蓄电池持续放电情况可提前10d定位。     

基于北斗的自动气象站报文传输方案设计

针对北斗卫星下行通信受4G和WIFI信号带内干扰导致传输成功率低的情况,设计了基于增加传输次数来降低误码率的自动气象站报文北斗传输方案。首次提出并建成用于传输自动气象站报文的双北斗指挥机用户群,根据北斗用户机的传输能力设计专用的气象报文编码格式,利用冗余频度开展报文重发,实现单个时次报文的4次重复接收,稳定地保证了较高的传输成功率。方案同时实现了观测报文1min内到达预报员桌面,在稳定性和时效性上均取得了突破。     

2016—2017年贵州大雾时空分布及气象要素演变分析

利用2016—2017年自动站逐小时观测资料,统计分析了贵州大雾天气的时空分布特征;同时,结合天气图资料分析筛选了锋面大雾个例31 d和辐射大雾个例17 d,对比分析大雾生消过程中风、温、湿等气象要素演变特点。结果表明：(1)贵州大雾在秋末到初春较为频发;一天中夜间02—09时是大雾频发时段,07时达到峰值。(2)贵州自西向东有4个多雾区,分别为西南部区域、中部区域、东部边缘区域和北部局部区域。(3)锋面大雾主要出现在贵州中西部,范围最广时可达20个县站左右,持续时长可达10~13 h,单站可持续60 h以上。辐射大雾以贵州中东部地区出现较多,范围最广时可接近40个县站,远比锋面大雾范围广,持续时间相对较短。(4)大雾期间,10 min平均风速为0~3 m?s-1,相对湿度为97%~100%,温度露点差为0~0.5℃;辐射大雾初期或形成前气温呈下降状态,消散期升温较明显,地气温差呈现由负到正或由低到高的变化趋势,反映出近地层大气由较为稳定的逆温环境向不稳定环境变化的过程;锋面大雾初期的降温和后期的升温现象并不突出,地气温差也没有特定的变化规律,仅有部分个例与锋面大雾情况一致。     

图像灰度匹配算法研究

图像配准是图像处理的基本任务之一,其效果将直接影响到其后续图像处理工作的效果。介绍了一种借助转动惯量计算惯量椭圆以进行遥感灰度图像配准的方法。     

传统村落景观基因信息链与自动识别模型构建——以陕西省为例

传统村落作为活的文化遗产,承载了大量历史记忆,是地域文化景观基因识别与模型构建研究的重要切入点。以陕西省71个国家级传统村落为例,基于景观基因理论建立陕西省传统村落景观基因识别体系,识别出陕西省传统村落景观基因特征;运用类型学原理和N级编码理论对景观基因进行编码,构建陕西省传统村落景观基因信息链并生成基因谱系;借鉴生物学中“胞-链-形”DNA碱基序列模型,提取出环境基因、建筑基因、农耕文化基因和宗族文化基因四个公共基因作为景观基因元（胞）,以村内道路系统作为基因链,构建传统村落景观基因DNA模型与自动识别模型,以此对传统村落的区位、类型、特征和文化基因进行自动识别。为传统村落景观基因信息有效传承与存储,以及乡村建设动态发展提供理论借鉴。     

基于2D地图的城市户外ARGIS视觉辅助地理配准技术

针对当前便携式位姿传感器获取的户外6DOF绝对位姿精度通常不足,致使基于位姿传感器的户外AR地理配准精度不高,提出了一种以2D地图作为参考数据进行户外视觉辅助定位进而提高ARGIS系统地理配准精度的方法和技术框架。在位姿传感器获取初始位姿的基础上,详细阐述了基于2D地图进行图像位姿优化和辅助校正的基本原理;并通过试验验证了该方法可以对位姿传感器获取的初始位姿进行优化,进而提高户外AR地理配准精度的有效性。     

River centerline extraction using the multiple direction integration algorithm for mixed and pure water pixels

The river centerline is a basic hydrological characteristic. Most prior studies have used remote sensing data to extract the river centerline from the open water region in a pure water pixel region. Extracting this type of river is relatively easy. However, extracting the centerline of a micro-river, which is mainly composed of mixed water pixels, is challenging. This paper presents a novel method, called the Multiple Direction Integration Algorithm (MDIA), to extract the river centerline using an image-enhancing method combined with river morphology. MDIA can be applied to regions mainly composed of pure water pixels, as well as to regions consisting of mixed water pixels in the index image. The method first calculates the normalized difference vegetation index (NDVI) and enhances the river linear structure using a Hessian matrix. Second, a small window is constructed as a circular structural element. In the window region, the local threshold is automatically obtained using water-oriented clustering segmentation and prior river knowledge to judge the pixel type. After completing the river centerline extraction in the current window, the next detecting window is generated to continue judgment. The structural element automatically executes river centerline judgment until the entire river centerline is extracted. The Landsat 8 images of six regions with different geomorphologies were chosen to analyze the method’s performance. The test sites include high mountain region, low mountain region, plains region with farmland and a residential region. The experimental results show that the optimal threshold of the processing results ranged from 0.2 to 0.3. In this range, the user’s accuracy is 0.813 to 0.997, and the producer’s accuracy is 0.981 to 1. The MDIA effectively and correctly extracts the river network in mixed-pixel regions. The presented method provides an effective algorithm for river centerline extraction that can be used to expand and update river datasets and provide reliable river centerline data for relevant hydrology studies.