基于高分辨率格点数据的1961-2013年青藏高原雪雨比变化

基于国家气象信息中心发布的1961-2013年全国0.5° × 0.5°逐日降水量和日平均气温格点数据集以及气象站点日降水量和日平均气温实测资料,采用森斜率,M-K突变分析,IDW空间插值以及小波分析等方法,对近53年来青藏高原的降水量,降雨量,降雪量以及雪雨比的时空变化,突变和周期等特征进行了分析.结果表明:① 从时间尺度上看,青藏高原的降水量和降雨量总体呈增加趋势,增加幅度分别为0.6 mm·a^-1(p < 0.05)和1.3 mm·a^-1(p < 0.001);而降雪量和雪雨比均呈下降趋势,下降幅度分别为0.6 mm·a^-1(p < 0.01)和0.5% a^-1(p < 0.001).② 从空间分布上看,青藏高原的大部分地区降水量和降雨量呈增加趋势,而降雪量却呈现减少趋势.因此,雪雨比在青藏高原相应呈现减少趋势.③ 突变和周期分析表明,青藏高原降水量,降雨量,降雪量和雪雨比的突变时间分别出现在2005,2004,1996和1998年左右,而周期变化集中为5年,10年,16年,20年左右.④ 青藏高原降水量倾向率和降雨量倾向率均随海拔的升高呈现出先降低后升高的变化趋势,降雪量倾向率随海拔的升高而降低,雪雨比倾向率随海拔的升高呈微弱的下降趋势.     

一种动态构建Delaunay三角网的算法

Delaunay三角剖分算法是构建数字高程模（DEM）的主要算法。在分析现有的Delaunay三角剖分的3种算法之后,指出现有算法存在的不足。并提出一种TIN的动态建模方法,利用分块技术来改进搜索方法,大大提高了Delaunay三角网的构建速度。实验结果表明,此算法和前面3种算法相比,效率有了很大提高。     

A Space-Time GIS Approach to Exploring Large Individual-based Spatiotemporal Datasets

The increasing number of large individual-based spatiotemporal datasets in various research fields has challenged the GIS community to develop analysis tools that can efficiently help researchers explore the datasets in order to uncover useful information. Rooted in Hägerstrand's time geography, this study presents a generalized space-time path (GSTP) approach to facilitating visualization and exploration of spatiotemporal changes among individuals in a large dataset. The fundamental idea of this approach is to derive a small number of representative space-time paths (i.e. GSTPs) from the raw dataset by identifying spatial cluster centers of observed individuals at different time periods and connecting them according to their temporal sequence. A space-time GIS environment is developed to implement the GSTP concept. Different methods of handling temporal data aggregation and the creation of GSTPs are discussed in this article. Using a large individual-based migration history dataset, this study successfully develops an operational space-time GIS prototype in ESRI's ArcScene and ArcMap to provide a proof-of-concept study of this approach. This space-time GIS system demonstrates that the proposed GSTP approach can provide a useful exploratory analysis and geovisualization environment to help researchers effectively search for hidden patterns and trends in such datasets.     

Comparative assessment of thematic accuracy of GLC maps for specific applications using existing reference data

Inputs to various applications and models, current global land cover (GLC) maps are based on different data sources and methods. Therefore, comparing GLC maps is challenging. Statistical comparison of GLC maps is further complicated by the lack of a reference dataset that is suitable for validating multiple maps. This study utilizes the existing Globcover-2005 reference dataset to compare thematic accuracies of three GLC maps for the year 2005 (Globcover, LC-CCI and MODIS). We translated and reinterpreted the LCCS (land cover classification system) classifier information of the reference dataset into the different map legends. The three maps were evaluated for a variety of applications, i.e., general circulation models, dynamic global vegetation models, agriculture assessments, carbon estimation and biodiversity assessments, using weighted accuracy assessment. Based on the impact of land cover confusions on the overall weighted accuracy of the GLC maps, we identified map improvement priorities. Overall accuracies were 70.8 ± 1.4%, 71.4 ± 1.3%, and 61.3 ± 1.5% for LC-CCI, MODIS, and Globcover, respectively. Weighted accuracy assessments produced increased overall accuracies (80–93%) since not all class confusion errors are important for specific applications. As a common denominator for all applications, the classes mixed trees, shrubs, grasses, and cropland were identified as improvement priorities. The results demonstrate the necessity of accounting for dissimilarities in the importance of map classification errors for different user application. To determine the fitness of use of GLC maps, accuracy of GLC maps should be assessed per application; there is no single-figure accuracy estimate expressing map fitness for all purposes.     

国际地震研究发展态势文献计量分析

以ISI Web of Science论文数据库为数据源,采用美国汤姆森科技信息集团开发的专业数据分析工具TDA(Thomson Data Analyzer)对1900年至2010年(数据入库时间至2010年)国际地震研究发展特点及其现状予以分析。结果显示:国际地震研究持续增长,特别是近20年,增速显著;美国在该领域居于引领优势;政府科研机构、国立科研机构和公共研究机构是该领域研究的主导力量;国际地震研究主要集中于地震机理及成因、地震监测、地震影响及效应等方向;中国虽然已经步入地震研究的主要国家行列,但影响十分有限。     

四套全球网格降水数据集在伊朗的适用性评估

伊朗由于其独特的地理位置和脆弱的生态环境一直以来都是气候变化研究的热点区域,降水作为伊朗水资源的重要来源对生态环境和社会经济发展尤为重要,因此评估降水数据集的适用性是进行科学研究的基础。本文利用伊朗1988—2017年103个观测站的年降水数据（OBS）,以平均偏差（Mean Error,ME）、均方根误差（Root Mean Square Error,RMSE）、相关系数（correlation coefficient,R）对Global Precipitation Climatology Centre（GPCC）V2020、Climatic Research Unit（CRU）TS 4.05、Terrestrial Air Temperature and Precipitation: Monthly and Annual Time Series（UDEL）V5.01和NOAA's Precipitation Reconstruction over Land（PREC）四套全球网格降水数据集在伊朗的适用性进行评估,并进一步分析了地形对不同数据集精度的影响。研究结果显示：① GPCC降水数据偏差最小,与观测数据相关性最高,最适合伊朗现代气候变化研究。② GPCC、CRU、和UDEL均能反映伊朗降水的基本特征,但普遍会低估降水高值,PREC数据不能准确反映伊朗降水的空间分布模态,因此使用PREC数据分析伊朗降水特征时应当谨慎。③ 海拔和坡度对ME、RMSE以及R有一定影响,坡向对数据集精度影响不大。以上结论可为四套数据的订正及其在伊朗地区气候变化研究中的应用提供科学依据。     

3种再分析资料的高空温度与中国探空温度资料的对比:年平均特征

利用中国105站的探空资料以及NCEP/NCAR、ERA和JRA 3种再分析资料,采用线性趋势、标准差、相关系数、EOF分析等多种统计分析方法,对再分析资料年平均的高空温度在中国区域的可信度进行了分析.研究表明:在数值上,3种再分析资料的高空温度均小于探空资料的高空温度,NCEP/NCAR资料在对流层上层更接近于探空资料,ERA和JRA资料则在对流层中下层与探空资料更为接近;在描述年际变化和长期变化趋势方面,ERA资料在我国北方的对流层上层的再现能力较好,NCEP/NCAR资料在我国南方的对流层上层的再现能力较好,而3种再分析资料在对流层中下层的再现能力相当;在时空变化特征方面,NCEP/NCAR和ERA资料能较好地表现高空温度的年代际变化特征,而ERA和JRA资料则能较好地表现年际变化特征.     

一种基于场景合成和锚点约束的SAR目标检测网络

随着深度学习方法在计算机视觉领域的崛起,如何将其应用于具有全天时、全天候等优点的SAR图像也成为一大研究重点.相较于传统图像,SAR图像由于其难判读、应用人群较少等原因难以获得大量标注数据.本文提出一种基于场景合成和锚点约束的SAR图标检测方法.通过区域生长算法和阈值法对SAR车辆目标及其阴影进行分割,然后随机嵌入SAR复杂场景中的合理区域来合成目标检测数据集.针对SAR车辆目标的几何特性、图像分辨率参数,对Faster-RCNN中的锚点大小进行约束,减少不符合SAR车辆目标检测框尺寸的候选框,大量约简冗余计算,提升训练、测试效率及精度.     

Quantifying TiO_2 Abundance of Lunar Soils:Partial Least Squares and Stepwise Multiple Regression Analysis for Determining Causal Effect

Partial least squares(PLS) regression was applied to the Lunar Soil Characterization Consortium(LSCC) dataset for spectral estimation of TiO2.The LSCC dataset was split into a number of subsets including the low-Ti,high-Ti,total mare soils,total highland,Apollo 16,and Apollo 14 soils to investigate the effects of interfering minerals and nonlinearity on the PLS performance.The PLS weight loading vectors were analyzed through stepwise multiple regression analysis(SMRA) to identify mineral species driving and...