北斗卫星导航系统SISURE初步评估

北斗导航系统自2018年12月27日提供全球服务以来,其服务性能受到了极大关注.以上海天文台iGMAS (International GNSS MonitoringAssessment System)分析中心发布的精密轨道、钟差产品作为基准,评估了2019年年积日3–12 d的北斗二号、北斗三号以及GPS广播星历的轨道、钟差和空间信号用户测距误差(Signal in Space User Ranging Error, SISURE,简称为URE),并且对北斗卫星导航系统结果进行了详细的分析.结果表明:在评估时间段内,北斗三号广播星历轨道精度、URE均明显优于北斗二号,且部分结果优于GPS.北斗三号广播星历轨道径向精度最高,优于0.2 m.北斗三号全部卫星URE均值优于0.4 m, URE RMS (root mean square)优于0.5 m.北斗二号每颗卫星URE均值、95%URE (置信度为95%的URE)、URE RMS小于2 m,北斗三号每颗卫星URE均值、95%URE、URE RMS小于1 m,均达到了系统公开承诺的服务性能标准.     

基准影像数据辅助遥感影像几何定位

针对遥感卫星影像几何定位时实测控制数据不足的情况,提出利用影像范围内基准影像数据辅助定位提高精度的方法。由遥感影像匹配得到同名像点,利用高精度影像数据和高程数据获取物方平面和高程坐标后,将其视为精度较低的控制点参与区域网平差,从而实现在不额外增加实测控制条件的情况下提高定位精度。经过在国内外3个地区进行一系列试验,验证了方法的可行性和有效性,对提升线阵遥感影像几何定位精度效果显著。     

北斗地基增强系统框架下流动站定位精度分析

江苏连续运行的参考站(CORS)苏州分中心已经建成覆盖全市的北斗地基增强系统框架网络,并基于此框架网络对区域用户提供服务,针对流动站在不同环境下连接各种源节点的稳定性和局限性问题进行了一系列测试.结果表明,在卫星不被遮挡的情况下,无论接收机是采用单星模式、双星模式,还是三星模式,其定位精度均能满足要求,即平面精度优于5cm,高程精度优于10cm.在卫星被遮挡的情况下,三星模式优势尤其明显,其初始化时间、稳定性以及定位精度均优于其他两种模式.     

资源三号测绘卫星影像中水体信息提取方法研究

以江苏省宜兴市为研究区,利用资源三号测绘卫星多光谱数据提取该区内水体信息。首先利用ERDAS软件QUAC工具进行大气纠正,对典型地物以及多种水体遥感反射率光谱特征进行分析;随后构建几种常用水体提取指数,通过对比实验确定各指数阈值,提取水体信息;对水体提取效果进行目视分析与抽样调查分析,结果表明:几种算法对于水体提取敏感性各有侧重,其中水体提取效果较好的算法有NDWI-B指数法和NDWI指数法。     

基于旋翼无人机倾斜摄影测量的城市三维实景建模研究

针对旋翼无人机倾斜摄影在三维建模的可行性及精度是否满足测量要求问题,本文以兰州市某区为例,利用ContextCapture软件对旋翼无人机倾斜摄影采集的数据进行了三维实景建模,并采用测区范围内均匀采集的外业实测控制点、检查点及测量数据验证所建立体模型的平面精度及测量精度。实验表明:采用多旋翼倾斜无人机获取数据,建立实景三维模型的中误差小于2像素,为后期行业应用提供了一定技术参考。     

Vertical accuracy evaluation of freely available latest high-resolution (30 m) global digital elevation models over Cameroon (Central Africa) with GPS/leveling ground control points.

Digital Elevation Models (DEMs) contain topographic relief data that are vital for many geoscience applications. This study relies on the vertical accuracy of publicly available latest high-resolution (30?m) global DEMs over Cameroon. These models are (1) the ALOS World 3D-30?m (AW3D30), (2) the Shuttle Radar Topography Mission 1 Arc-Second C-Band Global DEM (SRTM 1) and (3) the Advanced Spaceborne Thermal Emission and Reflection Global DEM Version 2 (ASTER GDEM 2). After matching their coordinate systems and datums, the horizontal positional accuracy evaluation was carried out and it shows that geolocation errors significantly influence the vertical accuracy of global DEMs. After this, the three models are compared among them, in order to access random and systematic effects in the elevation data each of them contains. Further, heights from 555 GPS/leveling points distributed all over Cameroon are compared to each DEM, for their vertical accuracy determination. Traditional and robust statistical measures, normality test, outlier detection and removal were used to describe the vertical quality of the DEMs. The test of the normality rejected the hypothesis of normal distribution for all tested global DEMs. Overall vertical accuracies obtained for the three models after georeferencing and gross error removal in terms of Root Mean Square (RMS) and Normalized Median Absolute Deviation (NMAD) are: AW3D30 (13.06?m and 7.75?m), SRTM 1 (13.25?m and 7.41?m) and ASTER GDEM 2 (18.87?m and 13.30?m). Other accuracy measures (MED, 68.3% quantile, 95% quantile) supply some evidence of the good quality of AW3D30 over Cameroon. Further, the effect of land cover and slope on DEM vertical accuracy was also analyzed. All models have proved to be worse in the areas dominated by forests and shrubs areas. SRTM 1 and AW3D30 are more resilient to the effects of the scattering objects respectively in forests and cultivated areas. The dependency of DEMs accuracy on the terrain roughness is evident. In all slope intervals, AW3D30 is performing better than SRTM 1 and ASTER GDEM 2 over Cameroon. AW3D30 is more representative of the external topography over Cameroon in comparison with two others datasets and SRTM 1 can be a serious alternative to AW3D30 for a range of DEM applications in Cameroon.     

东南太平洋秘鲁鳀资源量预报模型的构建

秘鲁鳀（Engraulis ringens）是栖息于东南太平洋沿岸的一种小型中上层鱼类。有效地对秘鲁鳀资源量进行预报将有助于为我国鱼粉进口企业提供决策支撑。为此,本研究结合秘鲁鳀生物（上一个渔汛季度的资源量、渔获物中的幼鱼比例）和环境（渔场水温和nino1+2区的温度距平）因素及捕捞量为预报因子,利用主成分分析和多元线性回归的方法对17个渔汛季度（2006年至2014年第一渔汛季度）秘鲁鳀的资源量建立预报模型并利用主成分分析的结果对影响秘鲁鳀资源变动的因子进行初步评价。研究表明,随着时间的推移样本量的增加,模型拟合资源量与真实资源量的平均相对误差逐渐下降,拟合资源量序列与真实资源量序列的相关系数逐渐增加。最终模型5（建模数据为2006-2013年第二渔汛季度的数据,验证数据为2014年第一渔汛季度的数据）能够很好地拟合出秘鲁鳀资源量的大小及变动趋势拟合资源量序列与真实资源量序列的相关系数为0.861;拟合资源量序列与真实资源量序列的平均相对误差为12%;预报得到的2014年第一渔汛季度的数据与真实值相比,相对误差为1%。结合主成分分析的结果对影响秘鲁鳀资源变动的因素进行评价结果表明,第一主成分的方差贡献率为46%,其中环境因素占据了最大的载荷;第二主成分的方差贡献率为23%,同样环境因素占据了最大载荷,但是,排名第二和第三的因素分别是上一个渔汛季度的资源量和捕捞量,其载荷相当;第三和第四主成分的方差贡献率分别为9%和7%,其中幼鱼比例占的载荷最大。根据各主成分得分序列与资源量序列的相关系数结果,环境因子对秘鲁鳀资源变动有重要影响。     

A simple and direct method to analyse the influences of sampling fractions on modelling intra-city human mobility

Sampling fraction is crucial to sampling-related studies and applications, especially in the big data era when most data are neither originally designed nor controllable in the data collection process. A common concern among researchers is ‘what’s the modelling accuracy when using a sample?’. Taking intra-city human mobility as the study objective, this study utilizes a simple and direct method to analyse the influences of various sampling fractions on modelling accuracy. Five common intra-city human mobility indicators (travel distance, travel time, travel frequency, radius of gyration and movement entropy) are evaluated considering mean value, median and probability distribution. Experimental results demonstrate that the representativeness of each considered indicator converges to 1 in its own unique rate and variances. The minimum required sampling fractions to satisfy specific accuracies differ for various indicators and evaluation measures. To further investigate how related factors influence the modelling accuracy of sampling fractions, additional experiments are conducted considering multiple sampling methods, study scopes, and data sources. Several interesting general findings are observed. This study provides a reference for other sampling-based applications.     

Application of tank,NAM, ARMA and neural network models to flood forecasting

Two lumped conceptual hydrological models, namely tank and NAM and a neural network model are applied to flood forecasting in two river basins in Thailand, the Wichianburi on the Pasak River and the Tha Wang Pha on the Nan River using the flood forecasting procedure developed in this study. The tank and NAM models were calibrated and verified and found to give similar results. The results were found to improve significantly by coupling stochastic and deterministic models (tank and NAM) for updating forecast output. The neural network (NN) model was compared with the tank and NAM models. The NN model does not require knowledge of catchment characteristics and internal hydrological processes. The training process or calibration is relatively simple and less time consuming compared with the extensive calibration effort required by the tank and NAM models. The NN model gives good forecasts based on available rainfall, evaporation and runoff data. The black‐box nature of the NN model and the need for selecting parameters based on trial and error or rule‐of‐thumb, however, characterizes its inherent weakness. The performance of the three models was evaluated statistically. Copyright © 2000 John Wiley & Sons, Ltd.     

降水临近预报及其在水文预报中的应用研究进展

随着全球气候变化、自然变迁及陆表生境改变,极端天气频发且呈现出多尺度时空变异特征,对其进行预报和预警一直是气象水文领域关注的焦点。临近预报可较准确地预报未来短时间天气显著变化,是当前预报强降水等极端事件的主要手段。从基于天气雷达0~3 h外推临近预报、融合数值模式0~6 h临近预报的发展历程梳理了临近预报的研究进展,阐述了雷达外推算法的发展进程、雷达外推预报与数值模式预报融合技术进展,指出"取长补短"的0~6 h融合预报在提高降水预报精度、延长降水预见期等多方面有较大的发展潜力,进一步探寻及提升融合技术是未来融合预报发展的核心。将临近预报以气象水文耦合的方式引入水文预报是从源头提高水文预报精度、保障水文预报效果的主要途径,总结了现阶段主流耦合方式、空间尺度匹配技术、水文模型不确定等陆气耦合中的关键问题,阐述了外推临近预报、融合临近预报作为水文预报输入的研究进展,明确了融合临近预报在延长洪水预见期、提高洪水预报精度中存在优势,并讨论了未来的研究重点及发展方向。