An identification for GEMINGA: A review of all the available data

Dedicated X-ray, optical and radio observations aimed at the identification of the bright γ-ray source 2CG195+04 (GEMINGA) are presented. A very promising candidate is found and its properties are discussed in the context of possible astrophysical scenarios.     

Prediction of landslides using ASTER imagery and data mining models

The aim of this study was to identify landslide-related factors using only remotely sensed data and to present landslide susceptibility maps using a geographic information system, data-mining models, an artificial neural network (ANN), and an adaptive neuro-fuzzy interface system (ANFIS). Landslide-related factors were identified in Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. The slope, aspect, and curvature of topographic features were calculated from a digital elevation model that was made using the ASTER imagery. Lineaments, land-cover, and normalized difference vegetative index layers were also extracted from the imagery. Landslide-susceptible areas were analyzed and mapped based on occurrence factors using the ANN and ANFIS. The generalized bell-shaped built-in membership function of the ANFIS was applied to landslide susceptibility mapping. Analytical results were validated using landslide test location data. In the validation results, the ANN model showed 80.42% prediction accuracy and the ANFIS model showed 86.55% prediction accuracy. These results suggest that the ANFIS model has a better performance than does the ANN in predicting landslide susceptibility.     

Method for statistical comparison of geophysical data by multiple instruments which have differing accuracies

A novel correlative technique is introduced for intercomparison of measurements of similar quantities made using different techniques. This process involves a generalized least-squares fitting method which can be used to estimate the slope of the best-fitting straight line that results when two separate data sets which are expected to be linearly correlated are compared via scatter-plots. The different data types may be subject to different uncertainties in their measurements. The algorithm determines and graphs the interrelationship between the errors in each method and the slope of the line of best fit, assuming Gaussian statistics.     

Linear and circular structures of the Bohemian Massif — Comparison of satellite and geophysical data

Two structural schemes of the Bohemian Massif are presented and compared. The first one is a result of interpretation of various geophysical data and the second one is compiled on the basis of decoding of space imagery from different sources (Kosmos, Landsat etc.). Both schemes have many structural features in common, but there are diversities namely in the hierarchy of directions and regional distribution of linear structures. These problems are discussed in detail. For example, the most impressive system of structures is the NW-SE system in both schemes, whereas the NE-SW is more remarkable in the geophysical scheme; the N-S and the E-W systems are best expressed in the scheme of photolineaments. These facts are due to the genesis, age, development and dynamic characteristics of respective structural systems. The circular structural features namely those of large size are mostly remarkable in space imagery. At present, they are not distinguished genetically but only described regionally.     

Comprehensive comparison of VHR 3D spatial data acquired from IKONOS and TerraSAR-X imagery

With the launch of very high resolution (VHR) optical and synthetic aperture radar (SAR) remote sensing satellites such as IKONOS and TerraSAR-X, a new era has begun in 3D spatial data acquirement. IKONOS provided the first VHR data is still being preferred for many remote sensing applications. TerraSAR-X is considered as a revolution in SAR imaging as a result of 1 m resolution imaging capability. The imaging principles of these satellites are quite different and include advantages and disadvantages that have considerable effects on the quality of acquired 3D spatial data.     

A review of geostationary satellite alternatives for retrieving data from long duration balloon flights

Low speed data from high altitude scientific balloon flights can be retrieved by geostationary satellites through existing data collection platform systems. Higher speed data of the order of 1 kbit/s create a more difficult problem, particularly if a response is to be made to the balloon payload in near real time. Different geostationary satellite methods to achieve these more demanding requirements are reviewed, and the more interesting cases identified for possible future experiments.     

Planetary landings with terrain sensing and hazard avoidance: A review

The site selection and certification processes for planetary landers equipped with hazard avoidance capability are reviewed. The prior (large-scale) ‘landability’ of the target areas determined from orbital remote sensing can be only a few tens of per cent (～40 % for Perseverance, ～80–90 % for Apollo 11 and 60–70 % for subsequent Apollo landers) because on-board sensing is able to find safe areas at smaller scales (meters to tens of meters) than the delivery ellipse which may be several to several tens of kilometers across. This contrasts with the ‘blind’ landings of unguided missions, where safe terrain occupying 95–99 % of the landing ellipse are typically sought. The particulars of Apollo 11 and Perseverance/Ingenuity are discussed, together with the similar Chang-E-3 and Tianwen-1 Moon and Mars landers, and the Hayabusa-2 and OSIRIS-REx asteroid contacts, since these missions all used on-board terrain-relative navigation to steer relative to hazards either mapped previously or detected in real-time. These missions set the context for the application of these techniques to the Dragonfly mission to Titan, which has a more austere remote sensing basis on which to select a landing site, but whose rotor propulsion allows substantial divert capability.     

Application of WorldView-3 imagery and ASTER TIR data to map alteration minerals associated with the Rodalquilar gold deposits,southeast Spain

The Rodalquilar epithermal quartz-alunite gold deposits that occur within the Rodalquilar caldera complex in southeast Spain, are associated with a pronounced hydrothermal alteration of the country rocks. The hydrothermal alteration zones that are exposed on the surface consist of the vuggy silica zone, the advanced argillic alteration zone, the intermediate argillic alteration zone, the propylitic alteration zone, and a second stage supergene acid sulfate alteration. High spatial resolution multispectral imagery recorded by the WorldView-3 satellite was used in this study to map the spatial distribution of the main alteration minerals in the Rodalquilar caldera complex. Thermal infrared (TIR) data of the ASTER satellite were used to detect the quartz-rich zones. The analysis of the Rodalquilar WorldView-3 data was based on the Adaptive Coherence Estimator (ACE), a partial unmixing algorithm. The ACE processing accurately mapped the spatial distribution of alunite, kaolinite, illite and goethite. Alunite is abundant in the vuggy silica and advanced argillic alteration zones, and in the second stage supergene acid sulfate alteration. Kaolinite is predominant in the intermediate argillic alteration zone. Illite is abundant in the outer parts of the intermediate argillic alteration zone. Goethite image maps gossans that mainly occur in the vuggy silica and advanced argillic alteration zones, and in the areas characterized by the second stage supergene acid sulfate alteration. The detection of quartz-rich zones from the ASTER TIR data complemented the WorldView-3 mapping results. The study shows the efficiency of high spatial resolution multispectral remote sensing imagery recorded by the WorldView-3 satellite for district-level mineral exploration studies.     

Astrophysical and geophysical observations with piramig/salyut 7 experiment

The facility offered by the Salyut 7 vehicle has allowed teams of scientists of 3 CNRS french laboratories to develop an instrument optimized for several disciplines in astrophysics and geophysics. P.I.R.A.M.I.G. (Photography Infra-Red Atmosphere, Interplanetary Medium, Galaxies) is a wide field (10° and 40°) camera devoted to high sensitivity photographic photometry. The spectral range is limited to the visible and near-infrared (400–850 nm), the main advantage being to observe above the absorving and emitting layers of the atmosphere.     

The accuracy of SST retrievals from AATSR: An initial assessment through geophysical validation against in situ radiometers,buoys and other SST data sets

The Advanced Along-Track Scanning Radiometer (AATSR) was launched on Envisat in March 2002. The AATSR instrument is designed to retrieve precise and accurate global sea surface temperature (SST) that, combined with the large data set collected from its predecessors, ATSR and ATSR-2, will provide a long term record of SST data that is greater than 15 years. This record can be used for independent monitoring and detection of climate change. The AATSR validation programme has successfully completed its initial phase. The programme involves validation of the AATSR derived SST values using in situ radiometers, in situ buoys and global SST fields from other data sets. The results of the initial programme presented here will demonstrate that the AATSR instrument is currently close to meeting its scientific objectives of determining global SST to an accuracy of 0.3 K (one sigma). For night time data, the analysis gives a warm bias of between +0.04 K (0.28 K) for buoys to +0.06 K (0.20 K) for radiometers, with slightly higher errors observed for day time data, showing warm biases of between +0.02 (0.39 K) for buoys to +0.11 K (0.33 K) for radiometers. They show that the ATSR series of instruments continues to be the world leader in delivering accurate space-based observations of SST, which is a key climate parameter.     

Survival of microorganisms in space: A review

Spores of $\text{Bacillus subtilis}$ were exposed to selected factors of space (vacuum, solar UV radiation, heavy ions of cosmic radiation), and their response was studied after recovery. These investigations were supplemented by ground-based studies under simulated space conditions. The vacuum of space did not inactivate the spores. However, vacuum-induced structural changes in the DNA, and probably in the proteins, caused a supersensitivity to solar UV radiation. This phenomenon is caused by the production of specific photoproducts in DNA and protein, which cannot be removed by normal cellular repair processes. In vegetative bacterial cells, exposed to vacuum, cell dehydration led to damage of the cell membrane, which could be partly repaired during subsequent incubation. The high local effectiveness of the cosmic heavy ions further decreases the chance that spores can survive for any length of time in space. Nonetheless, a spore travelling through space and protected from ultraviolet radiation could possibly survive an interplanetary journey. Such a situation favors panspermia as a possible explanation for the origin of life.     

Three-dimensional magnetic reconnection regimes: A review

The magnetic field in many astrophysical plasmas – such as the solar corona and Earth’s magnetosphere – has been shown to have a highly complex, three-dimensional structure. Recent advances in theory and computational simulations have shown that reconnection in these fields also has a three-dimensional nature, in contrast to the widely used two-dimensional (or 2.5-dimensional) models. Here we discuss the underlying theory of three-dimensional magnetic reconnection. We also review a selection of new models that illustrate the current state of the art, as well as highlighting the complexity of energy release processes mediated by reconnection in complicated three-dimensional magnetic fields.     

Evaluating the statistical performance of less applied algorithms in classification of worldview-3 imagery data in an urbanized landscape

In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other.     

Digital processing of spacelab imagery

A digital technique for processing and analyzing OH-cloud photographs to be retrieved from the ISRO-CNES collaborative experiment on the first Spacelab is presented and discussed here. The method adopted for processing the photographs incorporates into it the following major steps (i) digitising the OH photographs, (ii) applying corrections for vignetting, geometric distortions and brightness variations and (iii) superposing the geographic coordinates on the linearised OH photograph.     

A multi-spectral spatial convolution approach of rainfall forecasting using weather satellite imagery

Flood forecasting has long been a major topic of hydrologic research. Recent events and studies indicate that the success of flood forecasting in Taiwan depends heavily on the accuracy of real-time rainfall forecasting. In this study, we demonstrate a multi-spectral spatial convolution approach for real-time rainfall forecasting using geostationary weather satellite images. The approach incorporates cloud-top temperatures of three infrared channels in a spatial convolution context. It not only characterizes the input–output relationship between cloud-top temperature and rainfall at the ground level, but also is more consistent with physical and remote sensing principles than single-pixel matches. Point rainfall measurements at raingauge sites are up-scaled to pixel-average-rainfall by block kriging, then related to multi-spectral cloud-top temperatures derived from Geostationary Meteorological Satellite images by spatial convolution. The kernel function of the multispectral spatial convolution equation is solved by the least squares method. Through a cross-validation procedure, we demonstrate that the proposed approach is capable of achieving high accuracy for 1- to 3-h-lead pixel-average-rainfall forecasting.     

Integrating aeromagnetic data and Landsat-8 imagery for detection of post-accretionary shear zones controlling hydrothermal alterations: The Allaqi-Heiani Suture zone,South Eastern Desert,Egypt

The Arabian-Nubian Shield (ANS) underwent a regional carbonation event with CO₂ fluxes derived from the mantle and circulated along post-accretionary shear zones, thus affecting the redistribution of gold mineralization. Formerly, the analyses of remotely-sensed data have suggested regions of gold mineralization linked to the post-accretionary structured framework, but the results were insufficient for detailed prospecting in the ANS. In this research, aeromagnetic data and Landsat-8 imagery were integrated for delineating new high potential zones of gold mineralization in the Allaqi-Heiani Suture (AHS) zone, the ANS, South Eastern Desert (SED) of Egypt. Aeromagnetic data were enhanced using the Center for exploration targeting (CET) grid enhancement technique to detect the main structures that control hydrothermal alterations in the study area. Principal Component Analysis (PCA) technique and ratios of spectral bands were applied to Landsat-8 data for mapping zones of hydrothermal alteration associated with gold mineralization. The traced structural elements from RTP, CET and Landsat-8 maps were statistically plotted and interpreted using rose diagrams. These diagrams indicated that the NW and NE trends are the most dominant in the RTP map and that the intersection zones obtained from the CET analysis are aligned along the NW-oriented trend. While the NNW, WNW and NE trends were the most dominant ones in Landsat maps. The integration of the results indicates several new high potential zones of gold and Cu/Ni mineralization types, which are mostly concentrated at the western part of the AHS zone. The hydrothermal alteration zones and associated gold mineralization are strongly linked to NW, NE, E-W and WNW trending lineaments. The approach used in this study can be applied to other parts of the ANS and other regions with similar geological conditions around the world.     

信息缺失的航空发动机传感器数据重构

为处理传感器数据缺失问题,利用子空间表示系统演化特征,提出了基于极化增量矩阵填充(PIMC)的航空发动机传感器数据的在线重构模型。该模型通过历史数据获得当前的数据特征表示,并用新增的数据不断更新子空间以跟踪并表示数据发展特征。将本文模型用于仿真数据进行验证,重构结果和无噪数据的归一化均方误差(MSE)均小于1×10-5,实验结果显示本文模型对于航空发动机传感器数据重构有很好的应用价值,对缺失数据和噪声是鲁棒的。      

Driving major solar flares and eruptions: A review

This review focuses on the processes that energize and trigger M- and X-class solar flares and associated flux-rope destabilizations. Numerical modeling of specific solar regions is hampered by uncertain coronal-field reconstructions and by poorly understood magnetic reconnection; these limitations result in uncertain estimates of field topology, energy, and helicity. The primary advances in understanding field destabilizations therefore come from the combination of generic numerical experiments with interpretation of sets of observations. These suggest a critical role for the emergence of twisted flux ropes into pre-existing strong field for many, if not all, of the active regions that produce M- or X-class flares. The flux and internal twist of the emerging ropes appear to play as important a role in determining whether an eruption will develop predominantly as flare, confined eruption, or CME, as do the properties of the embedding field. Based on reviewed literature, I outline a scenario for major flares and eruptions that combines flux-rope emergence, mass draining, near-surface reconnection, and the interaction with the surrounding field. Whether deterministic forecasting is in principle possible remains to be seen: to date no reliable such forecasts can be made. Large-sample studies based on long-duration, comprehensive observations of active regions from their emergence through their flaring phase are needed to help us better understand these complex phenomena.     

一种保持数据完整性的数据集成机制的探讨

目前,企业数据往往分散于各个独立的业务系统中,因此不能很好的实现数据的统一管理和集成,基于对分布异构数据资源特点的分析,提出了一种保持数据完整性的数据集成机制.该机制通过三级模式(本地模式、局部模式和全局模式)的映射建立了层次化的数据模型,屏蔽了数据的异构性,并提出了一个数据完整性检查算法,即在数据集成中保证了基于全局模式的数据完整性,从而达到了既能实现数据资源的共享,又能将分布异构的数据资源形成有机整体的目的,最后以地震行业前兆数据集成平台的某一应用场景为例,说明了该数据集成机制具有保持数据完整性的能力.