Automated Prediction of CMEs Using Machine Learning of CME – Flare Associations

Machine-learning algorithms are applied to explore the relation between significant flares and their associated CMEs. The NGDC flares catalogue and the SOHO/LASCO CME catalogue are processed to associate X and M-class flares with CMEs based on timing information. Automated systems are created to process and associate years of flare and CME data, which are later arranged in numerical-training vectors and fed to machine-learning algorithms to extract the embedded knowledge and provide learning rules that can be used for the automated prediction of CMEs. Properties representing the intensity, flare duration, and duration of decline and duration of growth are extracted from all the associated (A) and not-associated (NA) flares and converted to a numerical format that is suitable for machine-learning use. The machine-learning algorithms Cascade Correlation Neural Networks (CCNN) and Support Vector Machines (SVM) are used and compared in our work. The machine-learning systems predict, from the input of a flare’s properties, if the flare is likely to initiate a CME. Intensive experiments using Jack-knife techniques are carried out and the relationships between flare properties and CMEs are investigated using the results. The predictive performance of SVM and CCNN is analysed and recommendations for enhancing the performance are provided.     

The NASA Lunar Impact Monitoring Program

NASA’s Meteoroid Environment Office has implemented a program to monitor the Moon for meteoroid impacts from the Marshall Space Flight Center. Using off-the-shelf telescopes and video equipment, the Moon is monitored for as many as 10 nights per month, depending on weather. Custom software automatically detects flashes which are confirmed by a second telescope, photometrically calibrated using background stars, and published on a website for correlation with other observations. Hypervelocity impact tests at the Ames Vertical Gun Range facility have begun to determine the luminous efficiency and ejecta characteristics. The purpose of this research is to define the impact ejecta environment for use by lunar spacecraft designers of the Constellation manned lunar program. The observational techniques and preliminary results will be discussed. The U.S. Government's right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.     

Comparison of Meteoroid Flux Models for Near Earth Space

Over the last decade several new models for the sporadic interplanetary meteoroid flux have been developed. These include the Divine-Staubach and the Dikarev model. They typically cover mass ranges from 10⁻¹⁸ g to 1 g and are applicable for model specific Sun distance ranges between 0.1 AU and 20 AU Near 1 AU averaged fluxes (over direction and velocities) for all these models are tuned to the well established interplanetary model by Grün et al. However, in many respects these models differ considerably. Examples are the velocity and directional distributions and the assumed meteoroid sources. In this paper flux predictions by the various models to Earth orbiting spacecraft are compared. Main differences are presented and analysed. The persisting differences even for near Earth space can be seen as surprising in view of the numerous ground based (optical and radar) and in situ (captured Inter Stellar Dust Particles, in situ detectors and analysis of retrieved hardware) measurements and simulations.     

澳门回归与粤澳经济和空间一体化

在澳门回归、广东与澳门之间政治关系转变的基础上, 结合改革开放后两地在经济与空间互补和紧密结合的历史事实, 指出澳门回归后, 在历史、经济、政治、文化等因素作用和影响下, 粤澳经济和空间一体化是一种必然趋势, 应充分利用两地资源和空间优势互补关系, 推动两个地区的发展。     

Analysis of thick, non-planar boundaries using the discontinuity analyser

The advent of missions comprised of phased arrays of spacecraft, with separation distances ranging down to at least mesoscales, provides the scientific community with an opportunity to accurately analyse the spatial and temporal dependencies of structures in space plasmas. Exploitation of the multi-point data sets, giving vastly more information than in previous missions, thereby allows unique study of their small-scale physics. It remains an outstanding problem, however, to understand in what way comparative information across spacecraft is best built into any analysis of the combined data. Different investigations appear to demand different methods of data co-ordination. Of the various multi-spacecraft data analysis techniques developed to affect this exploitation, the discontinuity analyser has been designed to investigate the macroscopic properties (topology and motion) of boundaries, revealed by multi-spacecraft magnetometer data, where the possibility of at least mesoscale structure is considered. It has been found that the analysis of planar structures is more straightforward than the analysis of non-planar boundaries, where the effects of topology and motion become interwoven in the data, and we argue here that it becomes necessary to customise the analysis for non-planar events to the type of structure at hand. One issue central to the discontinuity analyser, for instance, is the calculation of normal vectors to the structure. In the case of planar and ‘thin’ non-planar structures, the method of normal determination is well-defined, although subject to uncertainties arising from unwanted signatures. In the case of ‘thick’, non-planar structures, however, the method of determination becomes particularly sensitive to the type of physical sampling that is present. It is the purpose of this article to firstly review the discontinuity analyser technique and secondly, to discuss the analysis of the normals to thick non-planar structures detected in magnetometer data.     

The application of a shift theorem analysis technique to multipoint measurements

A Fourier domain technique has been proposed previously which, in principle, quantifies the extent to which multipoint in-situ measurements can identify whether or not an observed structure is time stationary in its rest frame. Once a structure, sampled for example by four spacecraft, is shown to be quasi-stationary in its rest frame, the structure’s velocity vector can be determined with respect to the sampling spacecraft. We investigate the properties of this technique, which we will refer to as a stationarity test, by applying it to two point measurements of a simulated boundary layer. The boundary layer was evolved using a PIC (particle in cell) electromagnetic code. Initial and boundary conditions were chosen such, that two cases could be considered, i.e. a spacecraft pair moving through (1) a time stationary boundary structure and (2) a boundary structure which is evolving (expanding) in time. The code also introduces noise in the simulated data time series which is uncorrelated between the two spacecraft. We demonstrate that, provided that the time series is Hanning windowed, the test is effective in determining the relative velocity between the boundary layer and spacecraft and in determining the range of frequencies over which the data can be treated as time stationary or time evolving. This work presents a first step towards understanding the effectiveness of this technique, as required in order for it to be applied to multispacecraft data.     

中国的空间环境研究与空间环境预报

本文主要介绍我国在空间环境研究与空间环境预报方面的进展, 包括空间环境资料和模式的收集、研究与应用; 空间环境与航天器的相互作用及其对航天器的影响; 以及空间环境预报方法和预报技术等的进展     

Space-time mapping of soil salinity using probabilistic bayesian maximum entropy

The mapping of saline soils is the first task before any reclamation effort. Reclamation is based on the knowledge of soil salinity in space and how it evolves with time. Soil salinity is traditionally determined by soil sampling and laboratory analysis. Recently, it became possible to complement these hard data with soft secondary data made available using field sensors like electrode probes. In this study, we had two data sets. The first includes measurements of field salinity (EC_a) at 413 locations and 19 time instants. The second, which is a subset of the first (13 to 20 locations), contains, in addition to EC_a, salinity determined in the laboratory (EC_2.5). Based on a procedure of cross-validation, we compared the prediction performance in the space-time domain of 3 methods: kriging using either only hard data (HK) or hard and mid interval soft data (HMIK), and Bayesian maximum entropy (BME) using probabilistic soft data. We found that BME was less biased, more accurate and giving estimates, which were better correlated with the observed values than the two kriging techniques. In addition, BME allowed one to delineate with better detail saline from non-saline areas.     

二次电流场多次叠加概率成像

基于地下电流场的积分公式,离散化的二次电流场被分解为电性不连续界面上的一系列点电荷电场的代数和.单位正点电荷电场被引入作为空间扫描函数（SDS）,积累电荷出现的概率（COP）函数定义为二次电流场与SDS的互相关.为对概率成像结果进行定量分析解释,提出了规范的积累电荷出现的概率（NCOP）函数.通过应用有限元算法对2D地电模型进行二次电流场合成,实现了二次电流场的多次叠加概率成像.结果表明对均匀半空间中赋存地质异常体的电性结构,概率成像方法对地下异常体的空间位置有较好的指示作用.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.