Observations of Chromospheric Anemone Jets with Hinode SOT and Hida Ca II Spectroheliogram

We present the first simultaneous observations of chromospheric "anemone" jets in solar active regions with Hinode SOT Ca II H broadband filetergram and Ca II K spetroheliogram on the Domeless Solar Telescope (DST) at Hida Observatory. During the coordinated observation, 9 chromospheric anemone jets were simultaneously observed with the two instruments. These observations revealed three important features, i.e.: (1) the jets are generated in the lower chromosphere, (2) the length and lifetime of the jets are 0.4-5 Mm and 40-320 sec, (3) the apparent velocity of the jets with Hinode SOT are 3-24 km/s, while Ca II K3 component at the jets show blueshifts (in 5 events) in the range of 2- 6 km/s. The chromospheric anemone jets are associated with mixed polarity regions which are either small emerging flux regions or moving magnetic features. It is found that the Ca II K line often show red or blue asymmetry in K2/K1 component: the footpoint of the jets associated with emerging flux regions often show redshift (2-16 km/s), while the one with moving magnetic features show blueshift (around 5 km/s). Detailed analysis of magnetic evolution of the jet foaming regions revealed that the reconnection rate (or canceling rate) of the total magnetic flux at the footpoint of the jets are of order of 10^{16} Mx/s, and the resulting magnetic energy release rate (1.1-10) x 10^{24} erg/s, with the total energy release (1-13) x 10^{26} erg for the duration of the magnetic cancellations, 130s. These are comparable to the estimated total energy, 10^{26} erg, in a single chromospheric anemone jet. An observation-based physical model of the jet is presented. The relation between chromospheric anemone jets and Ellerman bombs is discussed.Comment: 22 pages, 27 figures, accepted for Publications of the Astronomical Society of Japa

Towards the use of sequential patterns for detection and characterization of natural and agricultural areas

Nowadays, a huge amount of high resolution satellite images are freely available. Such images allow researchers in environmental sciences to study the different natural habitats and farming practices in a remote way. However, satellite images content strongly depends on the season of the acquisition. Due to the periodicity of natural and agricultural dynamics throughout seasons, sequential patterns arise as a new opportunity to model the behaviour of these environments. In this paper, we describe some preliminary results obtained with a new framework for studying spatiotemporal evolutions over natural and agricultural areas using k-partite graphs and sequential patterns extracted from segmented Landsat images.Postprint (author’s final draft

Modeling Complex Object Changes in Satellite Image Time-Series: Approach based on CSP and Spatiotemporal Graph

This paper proposes a method for automatically monitoring and analyzing the evolution of complex geographic objects. The objects are modeled as a spatiotemporal graph, which separates filiation relations, spatial relations, and spatiotemporal relations, and is analyzed by detecting frequent sub-graphs using constraint satisfaction problems (CSP). The process is divided into four steps: first, the identification of complex objects in each satellite image; second, the construction of a spatiotemporal graph to model the spatiotemporal changes of the complex objects; third, the creation of sub-graphs to be detected in the base spatiotemporal graph; and fourth, the analysis of the spatiotemporal graph by detecting the sub-graphs and solving a constraint network to determine relevant sub-graphs. The final step is further broken down into two sub-steps: (i) the modeling of the constraint network with defined variables and constraints, and (ii) the solving of the constraint network to find relevant sub-graphs in the spatiotemporal graph. Experiments were conducted using real-world satellite images representing several cities in Saudi Arabia, and the results demonstrate the effectiveness of the proposed approach

An Analysis of Shoreline Changes Using Combined Multitemporal Remote Sensing and Digital Evaluation Model

Cua Dai estuary belonged to Quang Nam province is considered to be one of the localities of Vietnam having a complex erosion and accretion process. In this area, sandbars are recently observed with lots of arguments about the causes and regimes of formation. This could very likely result of not reliable source of information on shoreline evolution and a lack of historical monitoring data. Accurately identification of shoreline positions over a given period of time is a key to quantitatively and accurately assessing the beach erosion and accretion. The study is therefore to propose an innovative method of accurately shoreline positions for an analysis of coastal erosion and accretion in the Cua Dai estuary. The proposed technology of multitemporal remote sensing and digital evaluation model with tidal correction are used to analyse the changes in shoreline and estimate the rate of erosion and accretion. An empirical formula is, especially, exposed to fully interpret the shoreline evolution for multiple scales based on a limitation of satellite images during 1965 to 2018. The results show that there is a significant difference of shoreline shift between corrections and non-corrections of tidal. Erosion process tends to be recorded in the Cua Dai cape located in the Cua Dai ward, especially in the An Luong cape located in the Duy Hai commune with the length of 1050 m. Furthermore, it is observed that there is much stronger erosion in the north side compared with south side of Cua Dai estuary

Extracting individual contributions from their mixture: a blind source separation approach, with examples from space and laboratory plasmas

Multipoint or multichannel observations in plasmas can frequently be modelled as an instantaneous mixture of contributions (waves, emissions, ...) of different origins. Recovering the individual sources from their mixture then becomes one of the key objectives. However, unless the underlying mixing processes are well known, these situations lead to heavily underdetermined problems. Blind source separation aims at disentangling such mixtures with the least possible prior information on the sources and their mixing processes. Several powerful approaches have recently been developed, which can often provide new or deeper insight into the underlying physics. This tutorial paper briefly discusses some possible applications of blind source separation to the field of plasma physics, in which this concept is still barely known. Two examples are given. The first one shows how concurrent processes in the dynamical response of the electron temperature in a tokamak can be separated. The second example deals with solar spectral imaging in the Extreme UV and shows how empirical temperature maps can be built.Comment: expanded version of an article to appear in Contributions to Plasma Physics (2010

The Use of Surveillance Cameras for the Rapid Mapping of Lava Flows: An Application to Mount Etna Volcano

In order to improve the observation capability in one of the most active volcanic areas in the world, Mt. Etna, we developed a processing method to use the surveillance cameras for a quasi real-time mapping of syn-eruptive processes. Following an evaluation of the current performance of the Etna permanent ground NEtwork of Thermal and Visible Sensors (Etna_NETVIS), its possible implementation and optimization was investigated to determine the locations of additional observation sites to be rapidly set up during emergencies. A tool was then devised to process time series of ground-acquired images and extract a coherent multi-temporal dataset of georeferenced map. The processed datasets can be used to extract 2D features such as evolution maps of active lava flows. The tool was validated on ad-hoc test fields and then adopted to map the evolution of two recent lava flows. The achievable accuracy (about three times the original pixel size) and the short processing time makes the tool suitable for rapidly assessing lava flow evolutions, especially in the case of recurrent eruptions, such as those of the 2011–2015 Etna activity. The tool can be used both in standard monitoring activities and during emergency phases (eventually improving the present network with additional mobile stations) when it is mandatory to carry out a quasi-real-time mapping to support civil protection actions. The developed tool could be integrated in the control room of the Osservatorio Etneo, thus enabling the Etna_NETVIS for mapping purposes and not only for video surveillance.Published1925V. Sorveglianza vulcanica ed emergenzeJCR Journalope

Automatic extraction of water inundation areas using Sentinel-1 dnata for large plain areas.

Accurately quantifying water inundation dynamics in terms of both spatial distributions and temporal variability is essential for water resources management. Currently, the water map is usually derived from synthetic aperture radar (SAR) data with the support of auxiliary datasets, using thresholding methods and followed by morphological operations to further refine the results. However, auxiliary datasets may lose efficacy on large plain areas, whilst the parameters of morphological operations are hard to be decided in different situations. Here, a heuristic and automatic water extraction (HAWE) method is proposed to extract the water map from Sentinel-1 SAR data. In the HAWE, we integrate tile-based thresholding and the active contour model, in which the former provides a convincing initial water map used as a heuristic input, and the latter refines the initial map by using image gradient information. The proposed approach was tested on the Dongting Lake plain (China) by comparing the extracted water map with the reference data derived from the Sentinel-2 dataset. For the two selected test sites, the overall accuracy of water classification is between 94.90% and 97.21% whilst the Kappa coefficient is within the range of 0.89 and 0.94. For the entire study area, the overall accuracy is between 94.32% and 96.7% and the Kappa coefficient ranges from 0.80 to 0.90. The results show that the proposed method is capable of extracting water inundations with satisfying accuracy

Global spatial and temporal analysis of human settlements from Optical Earth Observation: Concepts, procedures, and preliminary results

This report provides an overview on the concepts, processing procedures and examples used to quantify changes in built-up land from optical satellite imagery. This is part of the larger work of the Global Human Settlement (GHS) team from the Joint Research Centre (JRC) that aims to measure the spatial extent of global human settlements, to monitor its changes over time and characterize the morphology of settlements. This built-up change analysis addresses the quantification of urbanization including some socio-economic and physical processes associated with urbanization. This includes the quantification of the building stock for modeling physical exposure in disaster risk modeling, as background layer for emergency response when a disaster unfolds and as background building stock layer for normalizing physical loss data. Based on the application of three of the most used change detection methods, Principal Component Analysis, Image Differencing Comparison, and Post-Classification Comparison, we present and discuss preliminary results, and try to identify future research directions for developing an appropriate approach for GHSL result images. The case studies were carried on Alger and Dublin city areas.JRC.G.2-Global security and crisis managemen