The centerlines of polygons can be generated with the use of various methods. The aim of this study was to propose an algorithm for generating the centerline of an elongated polygon based on the transformation of vector data. The proposed method involves the determination of base points denoting the direction of river flow. These points were also used to map two polygon boundaries. A Triangulated Irregular Network (TIN) was created based on the polygon’s breakpoints. Edges that intersect the river channel in a direction perpendicular to river flow (across) were selected from a set of TIN edges. The polygon was partitioned into segments with the use of the selected TIN edges. The midpoints of selected TIN edges were used to generate the polygon’s centerline based on topological relations. The presented methodology was tested on a polygon representing a 15-km-long section of a river intersecting the city of Olsztyn (a university center). The analyzed river is a highly meandering watercourse, and its channel is narrowed down by hydraulic structures. The river features an island and distributary channels. The generated centerline effectively fits the polygon, and, unlike the solution modeled with the Medial Axis Transformation (MAT) algorithm, it does not feature branching streams.

Recommendations of the International Reference Ionosphere (IRI) Workshop 2017 in Taoyuan City, Taiwan and International GNSS Service (IGS) Workshop 2018 in Wuhan, China included establishment of an ionosphere mapping service that would fuse measurements from two independent sensor networks: IGS permanent GNSS receivers providing the vertical total electron content (VTEC) measurements and ionosondes of the Global Ionosphere Radio Observatory (GIRO) that compute the bottomside vertical profiles of the ionospheric plasma density. Using available GAMBIT software at GIRO, we introduced new VTEC products to its data roster: previously unavailable global average (climate) maps of VTEC and slab thickness based on climatological capabilities of IRI. Incorporation of the VTEC and maps into the GAMBIT Explorer environment provided data analysts with nearly 10-year history of the reference average VTEC records and opened access to the GAMBIT toolkit for evaluation and validation of the computations. This result is the first step towards establishing an infrastructure and the data workflow to provide GAMBIT users with the low latency and consistent quality and usability of the ionospheric weather-climate specifications. Combination of IGS-provided VTEC and GIRO-provided peak density of F2 layer NmF2 allows ground-based evaluation of the equivalent slab thickness , a derived property of the near-Earth plasma that characterizes the skewness of its vertical profile up to the GNSS spacecraft altitudes.

Automatic methods for constructing navigation routes do not fully meet all requirements. The aim of this study was to modify the methodology for generating indoor navigation models based on the Medial Axis Transformation (MAT) algorithm. The simplified method for generating corridor axes relies on the Node-Relation Structure (NRS) methodology. The axis of the modeled structure (corridor) is then determined based on the points of the middle lines intersecting the structure (polygon). The proposed solution involves a modified approach to the segmentation of corridor space. Traditional approaches rely on algorithms for generating Triangulated Irregular Networks (TINs) by Delaunay triangulation or algorithms for generating Thiessen polygons known as Voronoi diagrams (VDs). In this study, both algorithms were used in the segmentation process. The edges of TINs intersected structures. Selected midpoints on TIN edges, which were located in the central part of the structure, were used to generate VDs. Corridor structures were segmented by polygon VDs. The identifiers or structure nodes were the midpoints on the TIN edges rather than the calculated centroids. The generated routes were not zigzag lines, and they approximated natural paths. The main advantage of the proposed solution is its simplicity, which can be attributed to the use of standard tools for processing spatial data in a geographic information system.

The INSPIRE project was dedicated to the study of physical processes and their effects in ionosphere which could be determined as earthquake precursors together with detailed description of the methodology of ionospheric pre-seismic anomalies definition. It was initiated by ESA and carried out by an international consortium. The full set of key parameters of the ionospheric plasma was selected based on the retrospective analysis of the ground-based and satellite measurements of pre-seismic anomalies. Using this classification the multi-instrumental database of worldwide relevant ionospheric measurements (ionosonde and GNSS networks, LEO-satellites with in situ probes including DEMETER and FORMOSAT/COSMIC ROC missions) was developed for the time intervals related to selected test cases. As statistical processing shows, the main ionospheric precursors appear approximately 5 days before the earthquake within the time interval of 30 days before and 15 days after an earthquake event. The physical mechanisms of the ionospheric pre-seismic anomalies generation from ground to the ionosphere altitudes were formulated within framework of the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model. The processes of precursor’s development were analyzed starting from the crustal movements, radon emission and air ionization, thermal and atmospheric anomalies, electric field and electromagnetic emissions generation, variations of the ionospheric plasma parameters, in particular vertical TEC and vertical profiles of the electron concentration. The assessment of the LAIC model performance with definition of performance criteria for earthquake forecasting probability has been done in statistical and numerical simulation domains of the Global Electric Circuit. The numerical simulations of the earthquake preparation process as an open complex system from start of the final stage of earthquake preparation up to the final point–main shock confirms that in the temporal domain the ionospheric precursors are one of the most late in the sequence of precursors. The general algorithm for the identification of the ionospheric precursors was formalized which also takes into account the external Space Weather factors able to generate the false alarms. The importance of the special stable pattern called the “precursor mask” was highlighted which is based on self-similarity of pre-seismic ionospheric variations. The role of expert decision in pre-seismic anomalies interpretation for generation of seismic warning is important as well. The algorithm performance of the LAIC seismo-ionospheric effect detection module has been demonstrated using the L’Aquila 2009 earthquake as a case study. The results of INSPIRE project have demonstrated that the ionospheric anomalies registered before the strong earthquakes could be used as reliable precursors. The detailed classification of the pre-seismic anomalies was presented in different regions of the ionosphere and signatures of the pre-seismic anomalies as detected by ground and satellite based instruments were described what clarified methodology of the precursor’s identification from ionospheric multi-instrumental measurements. Configuration for the dedicated multi-observation experiment and satellite payload was proposed for the future implementation of the INSPIRE project results. In this regard the multi-instrument set can be divided into two groups: space equipment and ground-based support, which could be used for real-time monitoring. Together with scientific and technical tasks the set of political, logistic and administrative problems (including certification of approaches by seismological community, juridical procedures by the governmental authorities) should be resolved for the real earthquake forecast effectuation.

Prompt and accurate imaging of the ionosphere is essential to space weather services, given a broad spectrum of applications that rely on ionospherically propagating radio signals. As the 3D spatial extent of the ionosphere is vast and covered only fragmentarily, data fusion is a strong candidate for solving imaging tasks. Data fusion has been used to blend models and observations for the integrated and consistent views of geosystems. In space weather scenarios, low latency of the sensor data availability is one of the strongest requirements that limits the selection of potential datasets for fusion. Since remote plasma sensing instrumentation for ionospheric weather is complex, scarce, and prone to unavoidable data noise, conventional 3D-var assimilative schemas are not optimal. We describe a novel substantially 4D data fusion service based on near-real-time data feeds from Global Ionosphere Radio Observatory (GIRO) and Global Navigation Satellite System (GNSS) called GAMBIT (Global Assimilative Model of the Bottomside Ionosphere with Topside estimate). GAMBIT operates with a few-minute latency, and it releases, among other data products, the anomaly maps of the effective slab thickness (EST) obtained by fusing GIRO and GNSS data. The anomaly EST mapping aids understanding of the vertical plasma restructuring during disturbed conditions.