地震异构云管理平台的技术架构设计     

郭凯  姜立新  刘晓雨  班世敏 《中国地震》2020,36(1):153-161

基于Open Stack的开源标准体系,结合中国地震台网中心和中国地震局第二监测中心的云基础设施现状,设计两级云管理架构,以异构云管理平台作为综合管理平台,纳管区域云管理平台,以统一门户的方式对地震行业云计算资源进行统一管理;通过容器化部署异构云管理平台,初步实现对地震行业云计算资源的统一监控和运行管理。  相似文献   

南极中山站全天信息采集系统     

王宇  辛玉新  姜鹏  杨勇  伦宝利  王传军  余晓光  常亮  范玉峰 《天文研究与技术》2021,(2):272-282

南极高原拥有独特的天文观测优势,为了对南极中山站夜天文观测条件进行实测研究,中国科学院云南天文台专门研制了一套具有耐低温、自动除雪除霜等适应南极气候特征的全自动全天信息采集系统,该系统可以提供实时的全天云量、天光背景和全天图像,并将信息推送到网页实时显示。介绍了系统的研制及为适应南极气候进行的耐低温实验,统计分析了中山站2016~2017年的全天信息数据,结果显示,中山站2016和2017年的可观测时间为772.21 h和437.38 h,可观测夜数为93 d和51 d,天光背景最大真实值为22.05 Mag/arcsec 2,年平均气温为-10.6℃,最高气温19.1℃,最低气温为-44℃,2016年平均相对湿度为55.2%。  相似文献   

Integration of hyperspectral and LiDAR data for mapping small water bodies     

《International Journal of Applied Earth Observation and Geoinformation》2020

Inland water bodies are globally threatened by environmental degradation and climate change. On the other hand, new water bodies can be designed during landscape restoration (e.g. after coal mining). Effective management of new water resources requires continuous monitoring; in situ surveys are, however, extremely time-demanding. Remote sensing has been widely used for identifying water bodies. However, the use of optical imagery is constrained by accuracy problems related to the difficulty in distinguishing water features from other surfaces with low albedo, such as tree shadows. This is especially true when mapping water bodies of different sizes. To address these problems, we evaluated the potential of integrating hyperspectral data with LiDAR (hereinafter “integrative approach”). The study area consisted of several spoil heaps containing heterogeneous water bodies with a high variability of shape and size. We utilized object-based classification (Support Vector Machine) based on: (i) hyperspectral data; (ii) LiDAR variables; (iii) integration of both datasets. Besides, we classified hyperspectral data using pixel-based approaches (K-mean, spectral angle mapper). Individual approaches (hyperspectral data, LiDAR data and integrative approach) resulted in 2–22.4 % underestimation of the water surface area (i.e, omission error) and 0.4–1.5 % overestimation (i.e., commission error).The integrative approach yielded an improved discrimination of open water surface compared to other approaches (omission error of 2 % and commission error of 0.4 %). We also evaluated the success of detecting individual ponds; the integrative approach was the only one capable of detecting the water bodies with both omission and commission errors below 10 %. Finally, the assessment of misclassification reasons showed a successful elimination of shadows in the integrative approach. Our findings demonstrate that the integration of hyperspectral and LiDAR data can greatly improve the identification of small water bodies and can be applied in practice to support mapping of restoration process.  相似文献   

云平台下地震监测台网软件系统的应用方案研究     

李勇  段毅 《震灾防御技术》2018,13(1):245-253

针对数字化地震台网JOPENS软件系统的技术特点及功能需求，在对当前各种主流云计算平台进行比较的基础上，基于较为合适的阿里云计算平台，提出了在云环境下部署JOPENS系统的应用方案。测试结果表明JOPENS系统部署在云环境下能够提升测震台网中心运行的稳定性及可扩展性，并节约运行维护成本。该研究对于当前三网融合新形势下云南省地震台网的建设及运行工作具有借鉴意义。  相似文献   

Some Thoughts on the Earthquake Science Experimental Site——The Underground Cloud Map   总被引：1，自引：0，他引：1  

CHEN Yong  XU Yihe  CAI Huiteng  LI Wen 《中国地震研究》2019,33(1):1-8

The Western Yunnan Earthquake Predication Test Site set up jointly by the China Earthquake Administration, the National Science Foundation Commission of America, and United States Geological Survey has played an important role in development of early earthquake research work in China. Due to various objective reasons, most of the predicted targets in the earthquake prediction test site have not been achieved, and the development has been hindered. In recent years, the experiment site has been reconsidered, and renamed the “Earthquake Science Experimental Site”. Combined with the current development of seismology and the practical needs of disaster prevention and mitigation, we propose adding the “Underground Cloud Map” as the new direction of the experimental site. Using highly repeatable, environmentally friendly and safe airgun sources, we could send constant seismic signals, which realizes continuous monitoring of subsurface velocity changes. Utilizing the high-resolution 3-D crustal structure from ambient noise tomography, we could obtain 4-D (3-D space + 1-D time) images of subsurface structures, which we termed the “Underground Cloud Map”. The “Underground Cloud Map” can reflect underground velocity and stress changes, providing new means for the earthquake monitoring forecast nationwide, which promotes the conversion of experience-based earthquake prediction to physics-based prediction.  相似文献   

基于云模型的海岸脆弱性评估 ——以厦门岛为例     

朱正涛  蔡锋  曹超  陈沈良 《海洋通报》2019,38(4):462-471

脆弱性评估很大程度上存在着模糊性和随机性,为有效解决评估过程中定性概念与评估指标按隶属函数定量描述这一不确定转换问题,本文基于云理论本文选取海岸地貌、海岸高程、海岸坡度、海岸缓冲能力、有效波高、道路价值和建筑价值为指标,构建了厦门岛海岸脆弱性评估指标体系,运用云模型评估手段定量测度了厦门岛海岸脆弱性空间分异特征。评估结果与客观情况比较吻合,检验了指标体系的合理性和评估模型的适用性。本文提出了海岸脆弱性综合评估模型,实用有效,可以推广到与厦门岛类似的区域,为海岸管理及规划提供科学指导。  相似文献   

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management   总被引：1，自引：0，他引：1  

Zizheng Guo  Yu Shi  Faming Huang  Xuanmei Fan  Jinsong Huang 《地学前缘(英文版)》2021,12(6):243-261

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.  相似文献   

APG:A novel python-based ArcGIS toolbox to generate absence-datasets for geospatial studies     

Seyed Amir Naghibi  Hossein Hashemi  Biswajeet Pradhan 《地学前缘(英文版)》2021,12(6):90-104

One important step in binary modeling of environmental problems is the generation of absence-datasets that are traditionally generated by random sampling and can undermine the quality of outputs.To solve this problem,this study develops the Absence Point Generation(APG)toolbox which is a Python-based ArcGIS toolbox for automated construction of absence-datasets for geospatial studies.The APG employs a frequency ratio analysis of four commonly used and important driving factors such as altitude,slope degree,topographic wetness index,and distance from rivers,and considers the presence locations buffer and density layers to define the low potential or susceptibility zones where absence-datasets are gener-ated.To test the APG toolbox,we applied two benchmark algorithms of random forest(RF)and boosted regression trees(BRT)in a case study to investigate groundwater potential using three absence datasets i.e.,the APG,random,and selection of absence samples(SAS)toolbox.The BRT-APG and RF-APG had the area under receiver operating curve(AUC)values of 0.947 and 0.942,while BRT and RF had weaker per-formances with the SAS and Random datasets.This effect resulted in AUC improvements for BRT and RF by 7.2,and 9.7％from the Random dataset,and AUC improvements for BRT and RF by 6.1,and 5.4％from the SAS dataset,respectively.The APG also impacted the importance of the input factors and the pattern of the groundwater potential maps,which proves the importance of absence points in environmental bin-ary issues.The proposed APG toolbox could be easily applied in other environmental hazards such as landslides,floods,and gully erosion,and land subsidence.  相似文献   

On the linkage between changes in cloud cover and precipitation extremes over Central India     

《Dynamics of Atmospheres and Oceans》2019

In this study, linkage between changing characteristics of precipitation extremes and cloud covers over Central India is explored during summer monsoon period using Satellite data (1998–2015). This is a first attempt to relate the changes in cloud cover to the changes in precipitation extremes. Non-rainy cirrus clouds are excluded from this study. Results show that heavy rainfall (≥ 60 mm/day) is associated with cold cloud tops (Tb≤220 K) while moderate rainfall (<60 mm/day and ≥20 mm) occurs mostly with middle clouds (Tb>220 K and ≤245 K). Low level clouds (Tb> 245 K) are responsible for light rainfall (<20 mm/day). Increases in top 20%, 10%, 5% and 1% heavy precipitation relate well with the increases in very deep convective, deep convective and convective cloud cover. Among these relations, increase in top 5% heavy precipitation relates best with increase in very deep convective cloud cover. Decrease in bottom 30% low precipitation relates with decrease in low level cloud cover. The results reported in this study fit into the framework of how weather extremes respond to climate change.  相似文献   

毫米波雷达云回波的自动分类技术研究   总被引：1，自引：0，他引：1       下载免费PDF全文

杨晓  黄兴友  杨军  李培仁  李盈盈  杨敏  刘燕斐  张帅  闫文辉 《气象学报》2019,77(3):541-551

毫米波雷达在云探测方面比厘米波天气雷达和激光雷达具有显著优势,可获得更多的云粒子信息,是研究云特性的主要遥感探测设备。为了开展对毫米波雷达探测的云回波进行自动分类的研究,利用161次云回波的个例数据,统计得到了卷云、高层云、高积云、层云、层积云和积云6类云型的特征量和其他参量的数值范围,利用分级的多参数阈值判别方法,达到了自动分类的目标,通过与人工分类的初步验证,两种分类结果的一致性达到84%,其中,层云和积云的识别一致较低的原因在于样本数据有限,仅有6次层云和8次积云的个例样本数据。通过更多样本的处理,提取的特征参量更可靠,自动分类的准确率会得到提高,以便将基于毫米波雷达的云分类技术应用于将来的云观测自动化业务。   相似文献