Both the increasing number of GPS-enabled mobile devices and the geographic crowd-sourcing initiatives, such as Open Street Map, are determinants for the large amount of vector spatial data that is ...currently being produced. On the other hand, the automatic generation of raster data by remote sensing devices and environmental modeling processes was always leading to very large datasets. Currently, huge data generation rates are reached by improved sensor observation systems and data processing infrastructures. As an example, the Sentinel Data Access System of the Copernicus Program of the European Space Agency (ESA) was publishing 38.71 TB of data per day during 2020. This paper shows how the assumption of a new spatial data model that includes multi-resolution parametric spatial data types, enables achieving an efficient implementation of a large scale distributed spatial analysis system for integrated vector-raster data lakes. In particular, the proposed implementation outperforms the state-of-the-art Spark-based spatial analysis systems by more than one order of magnitude during vector-raster spatial join evaluation.
One of the most socially and culturally advantageous uses of human-computer interaction is enhancing playing and learning for children. In this paper, gesture interactive game-based learning (GIGL) ...is tested to see if these kinds of applications are suitable to stimulate working memory (WM) and basic mathematical skills (BMS) in early childhood (5-6 years old) using a hand gesture recognition system. Hand gesture is being performed by the user and to control a computer system by that incoming information. The research was developed using a quasi-experimental design with a pre-test and post-test, using both an experimental and control group through three phases: the first one was the prior evaluation of the learner's skills; a second phase in which the use of the technology was developed; and a final phase of evaluation. In the evaluation phases, working memory was measured using the Corsi task, and the basic mathematical skills using the test for the diagnosis of basic mathematical competencies (TEDI-MATH). The results provide clear evidence that the use of these technologies improved both working memory and basic mathematical skills. We can conclude that the children who used GIGL technology showed a significant increase in their learning performance in WM and BMS, surpassing those who did normal school activities.
► We present an adaptive thresholding algorithm to segment oil spills. ► The segmentation algorithm is based on SAR images and wind field estimations. ► A Database of oil spill confirmations was used ...for the development of the algorithm. ► Wind field estimations have demonstrated to be useful for filtering look-alikes. ► Parallel programming has been successfully used to minimize processing time.
Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean’s surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time.
This paper describes a data access and interactive exploration infrastructure for High Frequency Radar (HF Radar) data, developed in the scope of the RADAR-ON-RAIA EU project. The data access server ...is based on the use of Open Geospatial Consortium (OGC) standards, namely, the Observations and Measurements (O&M) data model and the Sensor Observation Service (SOS) interface. The use of those standards in an efficient implementation for remote sensing data is an innovative work that solves some problems not tackled by the previously available infrastructure, based on a THREDDS Data Server (TDS). The data exploration infrastructure includes a web based Graphical User Interface (GUI) at the client side and spatio-temporal probabilistic structures at the server side and it enables the visualization of statistical summaries of the data at different levels of resolution with interactive response times.
•Indexing techniques are essential in large scale subgraph searching.•Three new indexing techniques proposed, which leverage the use of bitmaps.•Generic framework for filter-then-verify ...implementations on top of Apache Spark.•Evaluation shows that different indexes are suitable for different query selectivities.•A distributed approach is essential for very large databases and low selective queries.
Subgraph searching is an essential problem in graph databases, but it is also challenging due to the involved subgraph isomorphism NP-Complete sub-problem. Filter-Then-Verify (FTV) methods mitigate performance overheads by using an index to prune out graphs that do not fit the query in a filtering stage, reducing the number of subgraph isomorphism evaluations in a subsequent verification stage. Subgraph searching has to be applied to very large databases (tens of millions of graphs) in real applications such as molecular substructure searching. Previous surveys have identified the FTV solutions GraphGrepSX (GGSX) and CT-Index as the best ones for large databases (thousands of graphs), however they cannot reach reasonable performance on very large ones (tens of millions graphs). This paper proposes a generic approach for the distributed implementation of FTV solutions. Besides, three previous methods that improve the performance of GGSX and CT-Index are adapted to be executed in clusters. The evaluation shows how the achieved solutions provide a great performance improvement (between 70% and 90% of filtering time reduction) in a centralized configuration and how they may be used to achieve efficient subgraph searching over very large databases in cluster configurations.
Virtual integration of sensor observation data Regueiro, Manuel A.; Viqueira, José R.R.; Taboada, José A. ...
Computers & geosciences,
August 2015, 2015-08-00, 20150801, Volume:
81
Journal Article
Peer reviewed
This paper discusses the design, implementation and evaluation of a framework that enables the virtual integration of heterogeneous observation data sources through a Sensor Observation Service (SOS) ...standard interface. Currently available SOS implementations follow a data warehouse design approach for data integration. Contrary to this, the present framework uses a well-known Mediator/Wrapper virtual data integration architecture, enabling the direct access to the current data supplied by the data sources. Currently, the framework is being validated as the OGC compliant technology to publish the meteorological and oceanographic observation data generated by two public agencies of the regional government of Galicia (Northwest of Spain).
•Virtual observation data integration vs. prevailing data warehouse approaches.•Flexible combination of Mediator/Wrapper architecture with OGC SWE interfaces.•In situ and remote static and mobile sensors producing vector and raster data.•Multi-thread implementation to leverage current hardware multicore architectures.•Under validation in two Spanish public meteorological and oceanographic agencies.
Global trade is mainly supported by maritime transport, which generates important pollution problems. Thus, effective surveillance and intervention means are necessary to ensure proper response to ...environmental emergencies. Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillages on the oceans surface. Several decision support systems have been based on this technology. This paper presents an automatic oil spill detection system based on SAR data which was developed on the basis of confirmed spillages and it was adapted to an important international shipping route off the Galician coast (northwest Iberian Peninsula). The system was supported by an adaptive segmentation process based on wind data as well as a shape oriented characterization algorithm. Moreover, two classifiers were developed and compared. Thus, image testing revealed up to 95.1% candidate labeling accuracy. Shared-memory parallel programming techniques were used to develop algorithms in order to improve above 25% of the system processing time.
•An automatic oil spill detection system based on SAR images was developed.•A database with confirmed oil spills was used to develop the system.•Image testing revealed up to 95.1% candidate labeling accuracy.•Two classifiers were compared from the labeling accuracy viewpoint.•The processing time was optimized via shared memory parallelization techniques.
SODA: A framework for spatial observation data analysis Villarroya, Sebastián; Viqueira, José R. R.; Regueiro, Manuel A. ...
Distributed and parallel databases : an international journal,
03/2016, Volume:
34, Issue:
1
Journal Article
Peer reviewed
Very large amounts of geospatial data are daily generated by many observation processes in different application domains. The amount of produced data is increasing due to the advances in the use of ...modern automatic sensing devices and also in the facilities available to promote crowdsourcing data collection initiatives. Spatial observation data includes both data of conventional entities and also samplings over multi-dimensional spaces. Existing observation data management solutions lack declarative specification of spatio-temporal analytics. On the other hand, current data management technologies miss observation data semantics and fail to integrate the management of entities and samplings in a single data modeling solution. The present paper presents the design of a framework that enables spatio-temporal declarative analysis over large warehouses of observation data. It integrates the management of entities and samplings within a simple data model based on the well known mathematical concept of function. Observation data semantics are incorporated into the model with appropriate metadata structures.
Retelab is a virtual laboratory for the Oceanographic research community. It is supported by a Grid infrastructure and its main objective is to provide an easy and useful tool for oceanographers, ...where computer skills are not an obstacle. To achieve these goals, Retelab includes improved versions of portal and Grid technologies related to security, data access, and job management. A solution based on a Role Access Management Model has been built for user access and registration, looking for a balance between simplicity and robustness. The sharing and discovery of scientific data is accomplished using a virtual database focused on metadata and designed specifically to store geospatial information. Finally, a comfortable and transparent procedure to submit and to monitor jobs has been developed. It is based on the integration and adaptation of the GridWay metascheduler to the multiuser portal environment in such a way that a single UNIX account can use several proxy certificates. The Virtual Laboratory has been tested by the implementation and deployment of several oceanographic applications.
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