一例异育银鲫(Carassius auratus gibelio)暴发性出血病病原分析

2016年6月,江苏某异育银鲫(Carassius auratus gibelio)养殖场暴发一种传染性急性出血病,造成养殖银鲫大量死亡。为分析此次疾病病因及流行规律,本研究从发病养殖场采集患出血病的异育银鲫,从细菌、病毒及寄生虫三个方面对病原进行了分析。采用病原菌分离、组织病理学观察、超薄切片电镜观察、病毒核酸分析、回感实验等对病原进行鉴定。结果显示从发病鲫鱼体内分离到病毒一株,未发现寄生虫及细菌感染。经测序及序列分析,该病毒为鲤疱疹病毒Ⅱ型(Cyprinid herpesvirus2,CyHV-2)病毒,组织病理学观察结果显示患病鱼的鳃和肾脏有明显病变,电镜下可观察到病鱼脾脏组织有带囊膜的球形病毒,囊膜直径约为170—200nm,病毒衣壳直径约为110—120nm,核心直径约为60nm,用组织匀浆感染鲫鱼囊胚细胞系(CGB)可稳定地观察到典型的细胞病变,用患病鱼组织匀浆液人工感染异育银鲫的死亡率高达100%,荧光定量PCR检测到该病毒可感染多器官,其中以脾脏中病毒含量最高,其次是脑,肝脏中最少。本研究可为CyHV-2的诊断防控及疫苗研制提供资料。     

额河源流采金矿区不同恢复措施对矿区物种多样性和地上生物量的影响

以额河源流采金后废弃矿区为研究对象，于2011—2015年期间，通过采取不同恢复措施从被破坏矿区草地植物多样性和生物量的角度分析植被恢复效果。结果表明：（1）不同恢复措施促使各植物群落的物种数增加了5%～30%,说明采取恢复措施使得矿区生态环境得到了一定程度的恢复。（2）综合植被群落结构、盖度和地上生物量、物种多样性指数分析，措施A5（推平+圈羊）、A4（推平+补水）、A3（推平+覆土+黑加仑）较其他措施恢复效果更为显著。（3）通过对各样地植被丰富度指数（R）、Shannon Wiener指数(H′)、Simpson指数（D）、Pielou (Jsw)指数与地上生物量分别进行回归分析,发现指数曲线拟合关系最好。表明物种多样性与地上生物量均存在较显著的正相关关系(P <0.05)。本研究可为类似矿区的植被恢复与重建提供参考和借鉴。     

Efficient estimation of flood forecast prediction intervals via single‐ and multi‐objective versions of the LUBE method

Prediction intervals (PIs) are commonly used to quantify the accuracy and precision of a forecast. However, traditional ways to construct PIs typically require strong assumptions about data distribution and involve a large computational burden. Here, we improve upon the recent proposed Lower Upper Bound Estimation method and extend it to a multi‐objective framework. The proposed methods are demonstrated using a real‐world flood forecasting case study for the upper Yangtze River Watershed. Results indicate that the proposed methods are able to efficiently construct appropriate PIs, while outperforming other methods including the widely used Generalized Likelihood Uncertainty Estimation approach. Copyright © 2016 John Wiley & Sons, Ltd.     

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.     

Remote sensing of water depths in shallow waters via artificial neural networks

Determination of the water depths in coastal zones is a common requirement for the majority of coastal engineering and coastal science applications. However, production of high quality bathymetric maps requires expensive field survey, high technology equipment and expert personnel. Remotely sensed images can be conveniently used to reduce the cost and labor needed for bathymetric measurements and to overcome the difficulties in spatial and temporal depth provision. An Artificial Neural Network (ANN) methodology is introduced in this study to derive bathymetric maps in shallow waters via remote sensing images and sample depth measurements. This methodology provides fast and practical solution for depth estimation in shallow waters, coupling temporal and spatial capabilities of remote sensing imagery with modeling flexibility of ANN. Its main advantage in practice is that it enables to directly use image reflectance values in depth estimations, without refining depth-caused scatterings from other environmental factors (e.g. bottom material and vegetation). Its function-free structure allows evaluating nonlinear relationships between multi-band images and in-situ depth measurements, therefore leads more reliable depth estimations than classical regressive approaches. The west coast of the Foca, Izmir/Turkey was used as a test bed. Aster first three band images and Quickbird pan-sharpened images were used to derive ANN based bathymetric maps of this study area. In-situ depth measurements were supplied from the General Command of Mapping, Turkey (HGK). Two models were set, one for Aster and one for Quickbird image inputs. Bathymetric maps relying solely on in-situ depth measurements were used to evaluate resultant derived bathymetric maps. The efficiency of the methodology was discussed at the end of the paper. It is concluded that the proposed methodology could decrease spatial and repetitive depth measurement requirements in bathymetric mapping especially for preliminary engineering application.     

风暴分类识别技术在人工防雹中的应用

利用新一代多普勒天气雷达资料,在风暴跟踪识别算法的基础上,发展了风暴分类技术,以提高人工防雹作业指挥的效率。首先以SCIT算法为基础,结合风暴的结构特征,综合利用雷达、探空资料,自动提取风暴结构特征指数;其次采用基于决策树模型的风暴自动分类技术,将风暴按强度分为雷雨云、单体风暴、多单体风暴和强风暴;最后根据风暴强度、高度和位置等属性,对有可能产生冰雹的单体,结合GIS,自动对下游方向或附近作业点进行预警或输出作业参数。通过对2006—2014年期间重庆、辽宁大连和河南三门峡三地发生的较为典型的31次冰雹天气过程、182站次冰雹样本的检验来看:该方法通过对风暴按强度、垂直结构等综合属性进行分类,能有效提高冰雹识别的命中率、降低空报率,其中强风暴的命中率能达到100%,空报率仅为11.4%。能有效提高人工防雹作业的自动化程度,对防雹作业的科学决策有着重要参考作用。     

哈密地区空中水汽及增水潜力分析

采用哈密地区6站1975—2014年逐日地面水汽压和降水量资料,计算了哈密各站的大气可降水量、有效空中水资源量、自然降水产出率和人工增水潜力值,并分析了各量的时空分布特征。结果表明:哈密地区年平均整层大气可降水量为2560~4327 mm,年均有效空中水资源量约为232~828 mm,占整层大气可降水量的1/4~1/10;年均自然降水产出率在9%~28%,自然降水产出率与降水量成正比关系。哈密地区的年人工增水潜力理论计算值在844~2399 mm之间,潜力值在夏季最大,巴里坤和伊吾明显多于其它区域。     

利用双线偏振雷达分析人工防雹作业效果

以北京市平谷区2011年6月11日防雹作业为例,利用双线偏振雷达资料,选取与作业区条件十分接近的云块为对比区,根据回波移动方向和速度,跟踪分析在不同高度上防雹作业前后云体宏观结构特征和粒子相态等微物理变化过程。作业后云体所呈现特征为:1作业区的云顶高度、强回波中心高度迅速下降,对比区变化不明显;2作业区水平反射率Zh减小,差分反射率Zdr、零相关系数ρhv增大,单位差分传播相移Kdp小范围内波动,对比区Zh、Zdr、Kdp变化不明显;ρhv增大;3作业区对流减弱,高层较大冰雹粒子、大雨滴下沉明显,最终以霰粒子为主;而对比区域则对流仍然旺盛,冰雹粒子有增多趋势。以上特征表明防雹作业可有效抑制冰雹胚胎成长为冰雹的过程,通过偏振雷达观测参量可对防雹作业效果进行较好的验证。     

一种裸露土壤湿度反演方法

针对目前土壤湿度反演方法研究较少且缺少实时性的现状,该文提出一种土壤湿度反演方法——最小二乘支持向量机技术。以积分方程模型为正向算法,数值模拟不同雷达参数(频率、入射角及极化)下后向散射系数随土壤含水量和地表粗糙度的变化情况。经过数据敏感性分析,选取C-波段和X-波段、小入射角下的同极化后向散射系数作为支持向量回归的训练样本信息;经过适当的训练,利用支持向量回归技术对土壤含水量进行了反演研究;并考虑通过多频率、多极化、多入射角数据的组合,消除地表粗糙度的影响,提高反演精度。模拟结果表明,该方法反演土壤湿度具有较高的精度和较好的实时性;同时,与人工神经网络方法的结果比较,证明了该方法的有效性,为土壤湿度的反演研究提供了一种方法。     

面向应用的航天遥感科学论证研究

为适应中国民用航天遥感从科学试验向业务服务模式转变,更好地探索、了解与解决应用需求与航天遥感系统对接等方面遇到的技术问题,促进航天遥感统筹协调可持续发展,中国适时于2004年成立了国家航天局航天遥感论证中心。10余年来,论证中心以航天遥感系统为研究对象,系统开展了面向应用的航天遥感科学论证概念、理论方法、技术工程与应用研究。本文是论证中心团队长期从事航天遥感科学论证研究与实践的系统总结,介绍了遥感论证初步认知、遥感论证关注问题、遥感论证理论体系与模型方法集、遥感论证能力建设及遥感论证实践等方面内容,给出了遥感论证定义并详细分析了研究范围和内容,提出了由知识维、进程维和逻辑维所组成的遥感论证作用域3维空间结构,指出社会发展加快和信息化水平提高,带动整个航天遥感数据信息链向更大规模、更短响应时间周期、更综合数据集成、更高数据质量、更加智能化方向发展,航天遥感系统将进入新的"智慧遥感"发展阶段。得益于十余年来中国民用航天快速发展,我们经历了风云三号新型载荷校飞、多角度多光谱偏振遥感器论证、环境星应用工程论证等实践,取得了多方面理论方法的突破,并应用到2030民用航天发展规划、高分辨率对地观测系统、国家自然灾害空间信息基础设施、国家民用空间基础设施中长期发展、2030中国综合地球观测系统规划等论证当中。经过不断实践,快速迭代,形成了遥感论证理论体系及相应的十大模型方法,包括遥感信息流模型、遥感信息特征模型、遥感信息应用模型、遥感信息量分析模型、遥感数据工程模型、航天遥感系统结构模型、航天遥感系统状态描述模型、航天遥感系统质量模型、航天遥感系统发展动力模型及能力体系模型。这些模型方法全面反映了航天遥感系统特征、结构、状态、发展动力、条件等,可广泛用于对航天遥感系统进行顶层设计、规划、考察、分析、评价、预测,并开展实践探索。