Extraction of Solar Coronal Magnetic Loops with the Directional 2D Morlet Wavelet Transform

We present an automated extraction method based on the continuous wavelet transform (CWT) for analyzing solar magnetic loops. The aim of the work is to extract, from the images taken from solar EUV telescopes, the traces of bright loops presumably shaped by the magnetic field of the solar corona. The technique is that of wavelet analysis, using the two-dimensional Morlet wavelet, because of its efficiency in detecting oriented features, which allows us to follow closely the curvature of the loops. Next, we segment the wavelet modulus image and we threshold it, both globally and locally (i.e., adaptively), in order to eliminate the remaining noise. Altogether, our method performs well, it is robust and fast, and could be used as a standard tool for analyzing large data sets expected from missions like SDO.     

Corridor location: the multi-gateway shortest path model

The problem of corridor location can be found in a number of fields including power transmission, highways, and pipelines. It involves the placement of a corridor or rights-of-way that traverses a landscape starting at an origin and ending at a destination. Since most systems are subject to environmental review, it is important to generate competitive, but different alternatives. This paper addresses the problem of generating efficient, spatially different alternatives to the corridor location problem. We discuss the weaknesses in current models and propose a new approach which is designed to overcome many of these problems. We present an application of this model to a real landscape and compare the results to past work. Overall, the new model called the multi-gateway shortest path problem can generate a wide variety of efficient alignments, which eclipse what could be generated by past work.     

TWO STRUCTURAL MODELS FOR THE WESTERN FLANK OF THE BRABANT MASSIF*

This paper is concerned with an interpretation of the Bouguer anomaly on the Western flank of the Brabant Massif (Belgium). The position, shape, and density contrast of elementary bodies in the upper part of the earth's crust are determined in a purely numerical manner. A batholith-like body and a basin-type structure both adequately account for the observed surface field, at least from a one-sided geophysical and mathematical point of view. Since seismological control is lacking the two models are representative of the ambiguity and indeterminacy of the definitions of the geologic cause of the anomalous features, if the data are restricted to gravity information alone.     

Very faint blue objects in the Virgo Cluster Region

Für 95 sehr schwache blaue Objekte in der Nähe des Zentrums des Virgo-Galaxienhaufens werden Auffindungskarten, Koordinaten, Schätzungen des (U – B)-Farbenindexes und grobe B-Helligkeiten mitgeteilt. Die Objekte wurden durch Blinken einer Tautenburger U- und B-Schmidtplatte gefunden.     

The fine structure of the geomagnetic field

It was shown in our previous works that the dipole part of the geomagnetic field direction is mainly represented by the 1200-yr variation. According to some indications, the residual of the dipole part of the field, the so-called δ variation, may be classified as standing waves. Average values of δ are calculated for each hemisphere. In this work, the difference values equal to the δ variations for each territory minus δ averages over hemispheres (western or eastern) are calculated. The resulting values, fine structure (FS) variations, characterize the FS of the geomagnetic field. The study of the activity of the FS variations and specific features of their N-S and E-W behavior and the comparative analysis of dynamic characteristics (activity and rate) give grounds to classify the FS variations (as well as the δ variations) as standing waves of the nondipole field.     

The Digital Belt and Road program in support of regional sustainability

The Belt and Road initiative has a significant focus on infrastructure, trade, and economic development across a vast region, and it also provides significant opportunities for sustainable development. The combined pressure of climate variability, intensified use of resources, and the fragility of ecosystems make it very challenging, however, to achieve future sustainability. To develop the path in a sustainable way, it is important to have a comprehensive understanding of these issues across nations and evaluate them in a scientific and well-informed approach. In this context, the Digital Belt and Road (DBAR) program was initiated as an international venture to share expertise, knowledge, technologies, and data to demonstrate the role of Earth observation science and technology and big Earth data applications to support large-scale development. In this paper, we identify pressing challenges, present the research priorities and foci of the DBAR program, and propose solutions where big Earth data can make significant contributions. This paper calls for further joint actions and collaboration to build a digital silk road in support of sustainable development at national, regional and global levels.     

A Hybrid Multi-scale Spatial Filtering and Minimum Spanning Forest for Spectral–Spatial Hyperspectral Image Classification

Integration of spatial and spectral information is an effective way in improving classification accuracy. In this article a new framework, based on multi-scale spatial weighted mean filtering (MSWMF) and minimum spanning forest, is proposed for the spectral–spatial classification of hyperspectral images. In the proposed framework, at first the image is smoothed by MSWMF and then the first eight principal components are extracted. Using support vector machine, at each scale of MSWMF, a classification map is produced in order to generate a marker map in the next step. Then, the minimum spanning forest is built on the marker map. Finally, in order to create a final classification map, all the classification maps of each scale are merged with a majority vote rule. The experimental results of the hyper-spectral images indicate that the suggested framework enhances the classification accuracy, in comparison with previously classification techniques. So, it is interesting for hyperspectral images classification.     

A strip adjustment procedure to mitigate the impact of inaccurate mounting parameters in parallel lidar strips

Lidar (laser scanning) technology has been proven as a prominent technique for the acquisition of high-density and accurate topographic information. Because of systematic errors in the lidar measurements (drifts in the position and orientation information and biases in the mirror angles and ranges) and/or in the parameters relating the system components (mounting parameters), adjacent lidar strips may exhibit discrepancies. Although position and orientation drifts can have a more significant impact, these errors and their impact do not come as a surprise if the quality of the GPS/INS integration process is carefully examined. Therefore, the mounting errors are singled out in this work. The ideal solution for improving the compatibility of neighbouring strips in the presence of errors in the mounting parameters is the implementation of a rigorous calibration procedure. However, such a calibration requires the original observations, which may not be usually available. In this paper, a strip adjustment procedure to improve the compatibility between parallel lidar strips with moderate flight dynamics (for example, acquired by a fixed-wing aircraft) over an area with moderately varying elevation is proposed. The proposed method is similar to the photogrammetric block adjustment of independent models. Instead of point features, planar patches and linear features, which are represented by sets of non-conjugate points, are used for the strip adjustment. The feasibility and the performance of the proposed procedure together with its impact on subsequent activities are illustrated using experimental results from real data.