Genetic mapping and QTL analysis for body weight in Jian carp (Cyprinus carpio var. Jian) compared with mirror carp (Cyprinus carpio L.)     

顾颖  鲁翠云  张晓峰  李超  俞菊华  孙效文 《中国海洋湖沼学报》2015,33(3):636-649

We report the genetic linkage map of Jian carp(C yprinus carpio var. Jian). An F1 population comprising 94 Jian carp individuals was mapped using 254 microsatellite markers. The genetic map spanned 1 381.592 c M and comprised 44 linkage groups,with an average marker distance of 6.58 c M. We identified eight quantitative trait loci(QTLs) for body weight(BW) in seven linkage groups,explaining 12.6% to 17.3% of the phenotypic variance. Comparative mapping was performed between Jian carp and mirror carp( Cyprinus carpio L.),which both have 50 chromosomes. One hundred and ninety-eight Jian carp marker loci were found in common with the mirror carp map,with 186(93.94%) showing synteny. All 44 Jian carp linkage groups could be one-to-one aligned to the 44 mirror carp linkage groups,mostly sharing two or more common loci. Three QTLs for BW in Jian carp were conserved in mirror carp. QTL comparison suggested that the QTL confidence interval in mirror carp was more precise than the homologous interval in Jian carp,which was contained within the QTL interval in Jian carp. The syntenic relationship and consensus QTLs between the two varieties provide a foundation for genomic research and genetic breeding in common carp.  相似文献   

基于分形理论的地形复杂性量化方法     

毛政利 《地理信息世界》2015,(1):43-46

地形的复杂性是地表崩塌、山体滑坡、泥石流等自然灾害的主要影响因素之一,近年来对地形复杂性的定量研究十分活跃,分形方法是其中主要的研究方法之一,但是目前的研究大多以沟壑分形、等高线分形、元分形等为主,难以对区域地形的整体复杂性进行定量描述;利用基于相对高差的地形分形研究方法,对三个形状和面积基本一致,地形起伏特征各不相同的区域,以相同的网度兼顾特殊地形位置布设样品点,统计样品点及其相对高差信息,并进行分形分析,分析结果表明,样品点的相对高差信息基本包含了其所在区域的地形特征信息,地形的相对高差信息服从分形分布,其分维值的变化趋势与地形复杂性相反,由此提出将其分维值的倒数定义为地形复杂性指数,地形复杂性指数的变化趋势与地形复杂性一致,它很好地拟合了地形的实际特征,定量地刻划了地形的复杂程度。  相似文献   

Waveform-based point cloud classification in land-cover identification     

《International Journal of Applied Earth Observation and Geoinformation》2015

Full-waveform topographic LiDAR data provide more detailed information about objects along the path of a laser pulse than discrete-return (echo) topographic LiDAR data. Full-waveform topographic LiDAR data consist of a succession of cross-section profiles of landscapes and each waveform can be decomposed into a sum of echoes. The echo number reveals critical information in classifying land cover types. Most land covers contain one echo, whereas topographic LiDAR data in trees and roof edges contained multi-echo waveform features. To identify land-cover types, waveform-based classifier was integrated single-echo and multi-echo classifiers for point cloud classification.The experimental area was the Namasha district of Southern Taiwan, and the land-cover objects were categorized as roads, trees (canopy), grass (grass and crop), bare (bare ground), and buildings (buildings and roof edges). Waveform features were analyzed with respect to the single- and multi-echo laser-path samples, and the critical waveform features were selected according to the Bhattacharyya distance. Next, waveform-based classifiers were performed using support vector machine (SVM) with the local, spatial features of waveform topographic LiDAR information, and optical image information. Results showed that by using fused waveform and optical information, the waveform-based classifiers achieved the highest overall accuracy in identifying land-cover point clouds among the models, especially when compared to an echo-based classifier.  相似文献   

Classification of vegetation in an open landscape using full-waveform airborne laser scanner data     

《International Journal of Applied Earth Observation and Geoinformation》2015

Airborne laser scanning (ALS) is increasingly being used for the mapping of vegetation, although the focus so far has been on woody vegetation, and ALS data have only rarely been used for the classification of grassland vegetation. In this study, we classified the vegetation of an open alkali landscape, characterized by two Natura 2000 habitat types: Pannonic salt steppes and salt marshes and Pannonic loess steppic grasslands. We generated 18 variables from an ALS dataset collected in the growing (leaf-on) season. Elevation is a key factor determining the patterns of vegetation types in the landscape, and hence 3 additional variables were based on a digital terrain model (DTM) generated from an ALS dataset collected in the dormant (leaf-off) season. We classified the vegetation into 24 classes based on these 21 variables, at a pixel size of 1 m. Two groups of variables with and without the DTM-based variables were used in a Random Forest classifier, to estimate the influence of elevation, on the accuracy of the classification. The resulting classes at Level 4, based on associations, were aggregated at three levels — Level 3 (11 classes), Level 2 (8 classes) and Level 1 (5 classes) — based on species pool, site conditions and structure, and the accuracies were assessed. The classes were also aggregated based on Natura 2000 habitat types to assess the accuracy of the classification, and its usefulness for the monitoring of habitat quality. The vegetation could be classified into dry grasslands, wetlands, weeds, woody species and man-made features, at Level 1, with an accuracy of 0.79 (Cohen’s kappa coefficient, κ). The accuracies at Levels 2–4 and the classification based on the Natura 2000 habitat types were κ: 0.76, 0.61, 0.51 and 0.69, respectively. Levels 1 and 2 provide suitable information for nature conservationists and land managers, while Levels 3 and 4 are especially useful for ecologists, geologists and soil scientists as they provide high resolution data on species distribution, vegetation patterns, soil properties and on their correlations. Including the DTM-based variables increased the accuracy (κ) from 0.73 to 0.79 for Level 1. These findings show that the structural and spectral attributes of ALS echoes can be used for the classification of open landscapes, especially those where vegetation is influenced by elevation, such as coastal salt marshes, sand dunes, karst or alluvial areas; in these cases, ALS has a distinct advantage over other remotely sensed data.  相似文献   

Detecting subpixel deciduous components to complement traditional land cover classifications in Southwest Finland     

《International Journal of Applied Earth Observation and Geoinformation》2015

To ensure successful conservation of ecological and cultural landscape values, detailed and up-to-date spatial information of existing habitat patterns is essential. However, traditional satellite-based and raster classifications rely on pixels that are assigned to a single category and often generalized. For many fragmented key habitats, such a strategy is too coarse and complementary data is needed. In this paper, we aim at detecting pixel-wise fractional coverage of broadleaved woodland and grassland components in a hemiboreal landscape. This approach targets ecologically relevant deciduous fractions and complements traditional crisp land cover classifications. We modeled fractional components using a k-NN approach, which was based on multispectral satellite data, assisted by a digital elevation model and a contemporary map database. The modeled components were then analyzed based on landscape structure indicators, and evaluated in conjunction with CORINE classification. The results indicate that both broadleaved forest and grassland components are widely distributed in the study area, principally organized as transition zones and small patches. Landscape structure indicators show a substantial variation based on the fractional threshold, pinpointing their dependency on the classification scheme and grain. The modeled components, on the other hand, suggest high internal variation for most CORINE classes, indicating their heterogeneous appearance and showing that the presence of deciduous components in the landscape are not properly captured in a coarse land cover classification. To gain a realistic perception of the landscape, and use this information for the needs of spatial planning, both fractional results and existing land cover classifications are needed. This is because they mutually contribute to an improved understanding of habitat patterns and structures, and should be used to complement each other.  相似文献   

球形标靶的固定式扫描大点云自动定向方法   总被引：1，自引：0，他引：1  

姚吉利  马宁  贾象阳  徐广鹏  谢建春 《测绘学报》2015,44(4):431-437

根据目前地面激光扫描数据获取速度快、数据量大、测量距离远、专用特殊材料制作的标靶识别距离近、点云定向数据处理相对滞后、自动化程度低、不能适应远距离地形测量的现状,提出了从大点云中(每站1亿点以上)自动探测远距离标靶的点云定向方法。该方法首先根据标靶控制点的工程测量坐标信息,搜索到标靶所在点云环,然后对各点云环进行扇形分区,快速探测标靶,获取标靶中心扫描坐标,最后平差计算扫描仪位置参数和姿态参数,实现点云坐标到工程测量坐标的转换。该方法在普通配置的计算机上得到实现,并成功用于远距离山区地形测量,其中定向标靶半径0.162m,标靶到扫描站距离在180~700m之间。  相似文献   

联合使用位模型和地形信息的陆区航空重力向下延拓方法   总被引：1，自引：0，他引：1  

黄谟涛  宁津生  欧阳永忠  邓凯亮  翟国君  陆秀平  吴太旗 《测绘学报》2015,44(4):355-362

为了规避传统逆Poisson积分向下延拓解算过程的不适定性问题,借鉴导航定位中的"差分"概念,利用超高阶位模型直接计算海域航空重力测量向下延拓改正数的方法。本文在此基础上提出联合使用重力位模型和地形高数据,计算陆部航空重力向下延拓总改正数的改进方案,以飞行高度面与地面对应点的位模型差分信息表征总改正数的中长波分量,以相对应的局部地形改正差分修正量表征总改正数的中高频成分,从而实现航空重力数据点对点向地面的全频段延拓。在地形变化不同区域,联合使用EGM2008位模型、地面实测重力和高分辨率高程数据进行了实际数值计算和精度评估,验证了该方法的有效性。  相似文献   

道路网络示意图的多边形生长算法     

张蓝  李佳田  徐珩  贺飞越  徐燕竹  王红梅 《测绘学报》2015,44(3):346-352

道路网络示意图是实体网络的抽象表示,因其更加符合人的认知习惯,在地图服务与地图制图领域已得到初步应用。以路径为单位的网络示意图自动生成算法只顾及节点与线段的局部布置,且较难以维护网络拓扑一致性。本文以闭合多边形(网眼)为基本单位,利用网眼的独立性与邻接性,提出了多边形生长算法,核心思想是将道路网络分类为闭合多边形与非闭合线段,以闭合多边形提取、映射、优化为主线,辅助组合非闭合线段。算例分析验证,本算法在网络均衡分布及拓扑一致性方面具有优势。  相似文献   

Landsat8和MODIS融合构建高时空分辨率数据识别秋粮作物   总被引：2，自引：0，他引：2  

谢登峰  张锦水  潘耀忠  孙佩军  袁周米琪 《遥感学报》2015,19(5):791-805

本文利用Wu等人提出的遥感数据时空融合方法 STDFA(Spatial Temporal Data Fusion Approach)以Landsat 8和MODIS为数据源构建高时间、空间分辨率的遥感影像数据。以此为基础,构建15种30 m分辨率分类数据集,然后利用支持向量机SVM(Support Vector Machine)进行秋粮作物识别,验证不同维度分类数据集进行秋粮作物识别的适用性。实验结果显示,不同分类数据集的秋粮作物分类结果均达到了较高的识别精度。综合各项精度指标分析,Red+Phenology数据组合对秋粮识别效果最好,水稻识别的制图精度和用户精度分别达到91.76%和82.49%,玉米识别的制图精度和用户精度分别达到85.80%和74.97%,水稻和玉米识别的总体精度达到86.90%。  相似文献   

一种基于球体分片射线的大数据体渲染方法     

王伟  张学全  颜士威  张少洪 《测绘科学》2015,40(5):60-62

针对大数据量、大范围对象的体渲染效果不够精细美观的问题,文章提出了一种基于球体分片射线的体渲染方法:通过将立方体形式的数据组织转变为环绕球体的弧形数据组织方式,并对体数据依次分片,逐片进行渲染。详细论述了该方法的原理及流程,并在某四维气象演示系统的台风登陆模拟中得到了很好的验证。实验表明,该方法能有效地渲染大数据量大范围对象的细节,提高了可视化效果。  相似文献