基于Oasis Montaj平台的航空物探数据处理软件系统

在深入研究Oasis Montaj平台特点的基础上,对已有的处理功能进行移植、优化,并开发了新的功能,集成为航空物探数据处理软件系统。这里就系统的整体架构、主要功能及其实现方法进行了详细介绍。通过大量的数据处理证明了该系统具有集成度高、实用性强、运行效率高、稳定性强、易操作、容错性强等诸多优势,能极大地提高数据处理的效率和质量。     

《气象报文自动处理分发系统》开发与应用

利用Visual Basic 6.0编程和mtimer定时进程控制技术，建立了《气象报文自动处理分发系统》。县（区）局测报员应用该系统的县局部分，能够实现报文编辑、转换、发送；市台预报员应用该系统的市局部分，可以实现报文收集、整理、打包传输。系统在一年多的实际业务应用中，简化了工作程序，实用性强，初步实现了气象信息传输的自动化。     

我国月降水和气温网格点资料的处理和分析

用逐步搜索逼近法的客观分析技术计算出１９５１－１９９２年中国月降水量和月平均气温的格点资料，并利用图象识别原理对格点值和站点观测值进行了比较。     

基于MySQL的广域电磁法数据处理与解释软件

针对目前广域电磁法数据处理软件集成度低、操作繁琐、数据无法统一管理的缺点,开发了广域电磁法数据处理与解释软件。软件采用客户机—服务器架构和模块化设计。基于MySQL数据库开发的项目管理模块,可以实现项目数据自动化的存储和管理,基于Python的科学计算库开发的广域电磁法的数据处理模块,可满足广域电磁法勘探的数据处理需求,以数据可视化和交互操作为基础,可极大简化处理人员的操作过程,提高数据处理效率。本软件已经应用到实际项目中,对大量数据进行了处理,取得了较好的效果。     

高光谱影像概率分类向量机分类方法研究

从分析基于支持向量机和相关向量机的高光谱影像分类方法的优势和不足出发,将基于概率分类向量机的方法用于高光谱影像分类试验。在贝叶斯理论框架下,概率分类向量机为基函数权值引入截断Gauss先验概率分布,使得不同类别的基函数权值具有不同符号的先验分布,并利用EM算法进行参数推断,得到足够稀疏的概率模型,弥补了相关向量机选取错误类别的样本作为相关向量的不足,从而有效地提高了模型的分类精度和稳定性。OMIS和PHI影像分类试验表明,概率分类向量机能够很好地应用在高光谱影像分类。     

Detection and mapping of bracken fern weeds using multispectral remotely sensed data: a review of progress and challenges

Bracken fern is one of the major invasive plants distributed all over the world currently threatening socio-economic and ecological systems due to its ability to swiftly colonize landscapes. The study aimed at reviewing the progress and challenges in detecting and mapping of bracken fern weeds using different remote sensing techniques. Evidence from literature have revealed that traditional methods such as field surveys and modelling have been insufficient in detecting and mapping the spatial distribution of bracken fern at a regional scale. The applications of medium spatial resolution sensors have been constrained by their limited spatial, spectral and radiometric capabilities in detecting and mapping bracken fern. On the other hand, the availability of most of these data-sets free of charge, large swath width and their high temporal resolution have significantly improved remote sensing of bracken fern. The use of commercial satellite data with high resolution have also proven useful in providing fine spectral and spatial resolution capabilities that are primarily essential to offer precise and reliable data on the spatial distribution of invasive species. However, the application of these data-sets is largely restricted to smaller areas, due to high costs and huge data volumes. Studies on bracken fern classification have extensively adopted traditional classification methods such as supervised maximum likelihood classifier. In studies where traditional methods performed poorly, the combination of soft classifiers such as super resolution analysis and traditional methods of classification have shown an improvement in bracken fern classification. Finally, since high spatial resolution sensors are expensive to acquire and have small swath width, the current study recommends that future research can also consider investigating the utility of the freely available recently launched sensors with a global footprint that has the potential to provide invaluable information for repeated measurement of invasive species over time and space.     

三参数小波及其在地震资料分析中的应用

提出了一类含有三个可调参数的分析小波（称为三参数小波）,通过选择这三个参数,可使其最适合于所给定的问题．Morlet小波及改进的Morlet小波是其特例．通过对三参数小波中的参数加以约束,可以获得一类新的近似解析小波．论证了通过恰当的选择参数,三参数小波不仅适合于分析包含慢变频率和振幅分量的信号,而且也适合于包含快变分量的信号．以三参数小波为分析小波,提出了一种用于薄互层地震资料分析的方法．该方法能够刻画薄互层的沉积旋回,也能研究薄互层内部的局部结构,并采用模型资料验证了方法的有效性．     

免像控无人机在地形图测量中的应用

通过eBeePlus免像控无人机航空摄影测量系统应用于1∶500地形图测绘工程实例,探究其在实践中的制图精度及适用性。使用emotion3、Pix4dMapper等软件进行外业航飞、内业影像处理,对比分析RTK和PPK两种解算方式下的制图精度,两者均满足规范要求,PPK解算方式更适宜在实践中使用;结合Eps软件制作数字线划地图,对于影像中无法提取的房屋边线、植被覆盖区域地物,采取全野外调绘、实测进行补充,阐述了无人机航测与传统数字化测图相结合的作业方式。     

Research on Parallel Algorithms for uv-faceting Imaging

The uv-faceting imaging is one of the widely used large field of view imaging technologies, and will be adopted for the data processing of the low-frequency array in the first stage of the Square Kilometre Array (SKA1). Due to the scale of the raw data of SKA1 is unprecedentedly large, the efficiency of data processing directly using the original uv-faceting imaging will be very low. Therefore, a uv-faceting imaging algorithm based on the MPI (Message Passing Interface)+OpenMP (Open Multi-Processing) and a uv-faceting imaging algorithm based on the MPI+CUDA (Compute Unified Device Architecture) are proposed. The most time-consuming data reading and gridding in the algorithm are optimized in parallel. The verification results show that the results of the proposed two algorithms are basically consistent with that obtained by the current mainstream data processing software CASA (Common Astronomy Software Applications), which indicates that the proposed two algorithms are basically correct. Further analysis of the accuracy and total running time shows that the MPI+CUDA method is better than the MPI+OpenMP method in both the correctness rate and running speed. The performance test results show that the proposed algorithms are effective and have certain extensibility.     

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.