多功能测绘模拟实验系统摄影装置的设计与应用     

贾周云  张献伟  熊强  王春祥  胡倩伟 《测绘工程》2018,(8):72-75,80

对多功能测绘模拟实验系统摄影装置进行优化设计,能够搭载单相机、五镜头倾斜相机和云台+单相机3种摄影装置,通过控制系统控制可移动轨道和摄影装置运行,并使摄影装置拍摄轨道下方的沙盘影像,模拟室外航空摄影测量,生产出沙盘的"4D"成果和三维沙盘模型等成果,实现摄影测量从影像数据获取、数据生产、成果应用的全过程模拟。  相似文献   

三线阵影像外方位元素平滑方程自适应光束法平差   总被引：1，自引：1，他引：0  

王建荣  王任享  胡莘 《测绘学报》2018,47(7):968-972

外方位元素数据是影响光学卫星影像几何定位精度的重要因素,其精度不仅取决于姿态和轨道测定系统的精度,还与卫星平台稳定度紧密相关。在实际卫星工程中,姿态测定系统存在突变现象,导致处理航线中上下视差发生较大变化。本文在全三线交会EFP光束法平差理论基础上,提出在光束法平差中采用外方位元素自适应分段平滑策略及其数学模型。即根据立体影像上下视差差分数据,对立体影像进行自动分段;在此基础上,对不同段的外方位元素平滑方程赋予不同权值,共同参与光束法平差。通过实际卫星影像试验表明,该方法可有效抑制卫星姿态测定系统突变对立体影像无控定位精度的影响,尤其是高程精度改善显著。  相似文献   

北斗高精度长弧历书模型设计     

常志巧  胡小工  陈刘成  李晓杰  祖安然  唐成盼  黄华 《测绘学报》2018,47(3):298-307

历书参数可同时用于辅助常规导航和自主导航的信号捕获。延长历书参数的有效期不但可以使地面接收机启动时充分利用历书数据,对于基于星间链路观测的自主导航,历书参数的有效期还决定了地面注入历书的频度和占用的星上存储资源。通过对北斗3类导航卫星主要摄动力及其对轨道根数的长期项和长周期项的影响分析,设计了以6个轨道根数和5个摄动参数为播发参数的历书拟合模型。以一个自主运行周期90 d为时间尺度,对北斗在轨卫星进行了长弧段历书拟合试验,并同时分析了卫星位置和速度的拟合精度。结果表明新的历书拟合模型提高了历书拟合的精度,尤其对于地球静止轨道和倾斜地球同步轨道卫星,拟合精度提高显著。对于GEO和IGSO卫星,位置拟合误差大约从200 km降低至十几千米甚至几千米,速度拟合误差大约从15 m/s降低至0.6 m/s,新方法拟合精度提高了约20~30倍;对于中圆地球轨道卫星,无论采用哪种历书模型,位置拟合误差都在5 km左右,速度拟合误差都在0.6 m/s左右,新方法拟合精度提高约15%。针对星间链路卫星10 km位置误差上限的使用需求,对比了新老历书模型的拟合弧长,常规模型最大拟合弧长约为14 d,而新历书模型的最大拟合弧长可延长至45 d,新历书模型延长了历书使用期限,优化了北斗历书模型设计。  相似文献   

面向过程的城市公共安全风险监测评估建模方法     

胡传博  游兰  林珲 《测绘学报》2018,47(8):1062-1071

在虚拟地理环境（virtual geographic environments,VGE）的研究中,城市公共安全作为一种典型的应用,致力于实现风险的认知与表达。然而,针对城市突发公共事件风险评估的共享管理需求与即时性需求,尚缺乏一种面向过程的风险监测与评估的表达方法,难以提供快速、全面的决策支持。针对此问题,本文首先基于元对象设施（meta object facility,MOF）建模架构,提出统一时空框架下面向过程的风险评估建模方法,实现风险监测评估方法的共享与重用,并提供面向过程的即时风险评估个性化信息服务。其次,设计了风险评估过程管理原型系统,实现风险评估过程建模、注册、执行和可视化等功能。最后,通过试验模拟太原市燃气泄漏事件作为应用案例,验证了方法的可行性。  相似文献   

基于GIS的西宁市生态敏感性分析     

邹洪坤  胡勇  李艳红  王彬 《测绘与空间地理信息》2018,(4):21-24

国土优化开发和土地集约型利用是生态文明建设的重要一环,生态敏感性分析为优化国土空间和土地的开发利用提供参考基础,也可促进区域生态环境的可持续发展。借助GIS技术,选取高程、坡度、水域、NDVI和土地利用类型5个生态敏感性因子,利用层次分析法(AHP)确定因子权重,采用空间叠加分析对生态敏感度定量分析,将所得到的生态敏感的高低分为高度敏感区、中度敏感区、低度敏感区和非敏感区,对各个生态敏感区进行综合分析,得到西宁市单因子和综合生态敏感性分析结果,并对西宁城市群的开发提出分区保护与建设的对策建议。  相似文献   

Identification of Convective and Stratiform Clouds Based on the Improved DBSCAN Clustering Algorithm     

Yuanyuan ZUO  Zhiqun HU  Shujie YUAN  Jiafeng ZHENG  Xiaoyan YIN  Boyong LI 《大气科学进展》2022,39(12):2203-2212

A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. To identify convective and stratiform clouds in different developmental phases, two-dimensional (2D) and three-dimensional (3D) models are proposed by applying reflectivity factors at 0.5° and at 0.5°, 1.5°, and 2.4° elevation angles, respectively. According to the thresholds of the algorithm, which include echo intensity, the echo top height of 35 dBZ (ET), density threshold, and ε neighborhood, cloud clusters can be marked into four types: deep-convective cloud (DCC), shallow-convective cloud (SCC), hybrid convective-stratiform cloud (HCS), and stratiform cloud (SFC) types. Each cloud cluster type is further identified as a core area and boundary area, which can provide more abundant cloud structure information. The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing, Xuzhou, and Qingdao. The results show that cloud clusters can be intuitively identified as core and boundary points, which change in area continuously during the process of convective evolution, by the improved DBSCAN algorithm. Therefore, the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification. Because density thresholds are different and multiple elevations are utilized in the 3D model, the identified echo types and areas are dissimilar between the 2D and 3D models. The 3D model identifies larger convective and stratiform clouds than the 2D model. However, the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds. In addition, the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.  相似文献   

Spatiotemporal Variations of Microwave Land Surface Emissivity (MLSE) over China Derived from Four-Year Recalibrated Fengyun 3B MWRI Data     

Rui LI  Jiheng HU  Shengli WU  Peng ZHANG  Husi LETU  Yu WANG  Xuewen WANG  Yuyun FU  Renjun ZHOU  Ling SUN 《大气科学进展》2022,39(9):1536-1560

Microwave Land Surface Emissivity (MLSE) over China under both clear and cloudy sky conditions was retrieved using measurements of recalibrated microwave brightness temperatures (Tbs) from Fengyun-3B Microwave Radiation Imager (FY-3B MWRI), combined with cloud properties derived from Himawari-8 Advanced Himawari Imager (AHI) observations. The contributions from cloud particles and atmospheric gases to the upwelling Tbs at the top of atmosphere were calculated and removed in radiative transfer. The MLSEs at horizontal polarizations at 10.65, 18.7, and 36.5 GHz during 7 July 2015 to 30 June 2019 over China showed high values in the southeast vegetated area and low values in the northwest barren, or sparsely vegetated, area. The maximum values were found in the belt area of the Qinling-Taihang Mountains and the eastern edge of the Qinghai-Tibet Plateau, which is highly consistent with MLSEs derived from AMSR-E. It demonstrates that the measurements of FY-3B MWRI Tbs, including its calibration and validation, are reliable, and the retrieval algorithm developed in this study works well. Seasonal variations of MLSE in China are mainly driven by the combined effects of vegetation, rainfall, and snow cover. In tropical and southern forest regions, the seasonal variation of MLSE is small due to the enhancement from vegetation and the suppression from rainfall. In the boreal area, snow causes a significant decrease of MLSE at 36.5 GHz in winter. Meanwhile, the MLSE at lower frequencies experiences less suppression. In the desert region in Xinjiang, increases of MLSEs at all frequencies are observed with increasing snow cover.  相似文献   

A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image     

Chao LIU  Shu YANG  Di DI  Yuanjian YANG  Chen ZHOU  Xiuqing HU  Byung-Ju SOHN 《大气科学进展》2022,39(12):1994-2007

Cloud Masking is one of the most essential products for satellite remote sensing and downstream applications. This study develops machine learning-based (ML-based) cloud detection algorithms using spectral observations for the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. Collocated active observations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to provide reference labels for model development and validation. We introduce both daytime and nighttime algorithms that differ according to whether solar band observations are included, and the artificial neural network (ANN) and random forest (RF) techniques are adopted for comparison. To eliminate the influences of surface conditions on cloud detection, we introduce three models with different treatments of the surface. Instead of developing independent ML-based algorithms, we add surface variables in a binary way that enhances the ML-based algorithm accuracy by ~5%. Validated against CALIOP observations, we find that our daytime RF-based algorithm outperforms the AHI operational algorithm by improving the accuracy of cloudy pixel detection by ~5%, while at the same time, reducing misjudgment by ~3%. The nighttime model with only infrared observations is also slightly better than the AHI operational product but may tend to overestimate cloudy pixels. Overall, our ML-based algorithms can serve as a reliable method to provide cloud mask results for both daytime and nighttime AHI observations. We furthermore suggest treating the surface with a set of independent variables for future ML-based algorithm development.  相似文献   

CMIP6模式对青藏高原多年冻土变化的分析预估     

胡桃  吕世华  常燕  杨明鑫  罗江鑫  程新巧 《高原气象》2022,41(2):363-375

利用国际耦合模式比较计划第六阶段（CMIP6）多模式的模拟结果,对比观测和青藏高原冻土图评估各模式对当前（1985-2014年）青藏高原与冻土相关气候变量以及多年冻土的模拟能力,并应用多模式集合平均的方法预估了未来4个SSP情景下2021-2040年、2041-2060年、2081-2100年高原多年冻土的变化趋势。结果表明：CMIP6各模式都能够较好地模拟出与冻土相关气候变量的分布特征与趋势,但对于气温的模拟有着较为明显的冷偏差,对于积雪的模拟明显偏大;利用冻结数模型（SFI）计算的当前多年冻土分布与青藏高原冻土图有较好的吻合,1985-2014年的表面多年冻土面积约为134.52×10⁴km²（包含湖泊和冰川面积）;随着气温的升高,21世纪青藏高原多年冻土呈现区域退化的趋势,在SSP1-2.6、SSP2-4.5、SSP3-7.0和SSP5-8.5情景下,青藏高原东部、南部以及北部边缘地区多年冻土呈现区域性退化,至2041-2060年间多年冻土面积分别减少13.81×10⁴ km²、19.51×1...  相似文献   

HRCLDAS-V1.0和ERA5海面风场对比评估分析          下载免费PDF全文

渠鸿宇  黄彬  赵伟  宋佳凝  郭乙莹  胡海川  曹越男 《热带气象学报》2022,38(4):569-579

基于2020年中国近海31个浮标的逐小时数据,使用统计分析方法对中国气象局高分辨率陆面数据同化系统(HRCLDAS-V1.0)和欧洲中期天气预报中心第5代全球大气再分析数据(ERA5)海面风场进行了系统的检验,检验结果表明:两者在我国近海均具有较高的可信度,风速平均绝对误差(MAE)分别为1.16 m/s和1.09 m/s,风向MAE分别为23 °和22 °。随着风力增大两者的风速准确度均有所降低,当风力等级≥10级时,前者准确度优于后者;对于风向而言,随着风力增大,两者准确度均升高。此外,选取2020年典型的两次冷空气过程和2008号台风“巴威”过程,检验两者在不同天气过程影响下的准确度,两类融合产品均能较好地再现冷空气过程引起的风向变化,而对不同强度的冷空气过程下的风速反映存在差异;对于台风引起的大风,在风速较低时两者风速均具有不错的表现,但HRCLDAS-V1.0对峰值强度的表现优于ERA5。   相似文献