BUSCADOR RECOLECTA

The AIDA diabetes simulator has been used to generate 10 days of data for the different models implemented by the tool.

Providing citizens with the ability to move around in an accessible way is a requirement for all cities today. However, modeling city infrastructures so that accessible routes can be computed is a challenge because it involves collecting information from multiple, large-scale and heterogeneous data sources. In this paper, we propose and validate the architecture of an information system that creates an accessibility data model for cities by ingesting data from different types of sources and provides an application that can be used by people with different abilities to compute accessible routes. The article describes the processes that allow building a network of pedestrian infrastructures from the OpenStreetMap information (i.e., sidewalks and pedestrian crossings), improving the network with information extracted obtained from mobile-sensed LiDAR data (i.e., ramps, steps, and pedestrian crossings), detecting obstacles using volunteered information collected from the hardware sensors of the mobile devices of the citizens (i.e., ramps and steps), and detecting accessibility problems with software sensors in social networks (i.e., Twitter). The information system is validated through its application in a case study in the city of Vigo (Spain)., Ministerio de Economía, Industria y Competitividad | Ref. TIN2016-77158-C4-1-R, Ministerio de Economía, Industria y Competitividad | Ref. TIN2016-77158- C4-2-R, Ministerio de Economía, Industria y Competitividad | Ref. TIN2016-77158-C4-3-R, Agencia Estatal de Investigación | Ref. PID2019-105221RB-C41, Agencia Estatal de Investigación | Ref. PID2019-105221RB-C43, Agencia Estatal de Investigación | Ref. PID2019-105221RB-C44, Xunta de Galicia | Ref. ED431C 2017/58, Xunta de Galicia | Ref. IN852A 2018/14, Xunta de Galicia | Ref. ED431G 2019/01, Xunta de Galicia | Ref. ED481B-2019-061, Xunta de Galicia | Ref. ED481D 2019/020

Unamnned aerial systems (UAS) show great potential in operations related to surveillance. These systems can be successfully applied to the prevention of forest fires, especially those caused by human intervention. The present works focuses on a study of the operational possibilities of the unmanned system “AtlantikSolar” developed by the ETH Zurich for the prevention of forest fires in the Spanish natural park of Serra do Xurés, an area of 20,920 ha with height variations between 300 m and 1,500 m. The operation evaluation of AtlantikSolar is based on the use of Flir Tau 2 LWIR camera as imaging payload which could detect illegal activities in the forest, such as bonfires, uncontrolled burning or pyromaniacs. Flight surveillance is planned for an altitude of 100 m to obey the legal limit of the Spanish UAS regulation. This altitude produces a swath width of 346.4 m and pixel resolution between 1.5 and 1.8 pixels/m. Operation is planned to adapt altitude to the change on the topography and obtain a constant ground resolution. Operational speed is selected to 52 km/h. The UAS trajectory is adapted to the limits of the natural park and the border between Spain and Portugal. Matlab code is developed for mission planning. The complete surveillance of the natural park requires a total time of 15.6 hours for a distance of 811.6 km., Xunta de Galicia | Ref. ED431C 2016, Ministerio de Economía, Industria y Competitividad | Ref. TIN2016-77158-C4-1-R

[Abstract]
Providing citizens with the ability to move around in an accessible way is a requirement for all cities today. However, modeling city infrastructures so that accessible routes can be computed is a challenge because it involves collecting information from multiple, large-scale and heterogeneous data sources. In this paper, we propose and validate the architecture of an information system that creates an accessibility data model for cities by ingesting data from different types of sources and provides an application that can be used by people with different abilities to compute accessible routes. The article describes the processes that allow building a network of pedestrian infrastructures from the OpenStreetMap information (i.e., sidewalks and pedestrian crossings), improving the network with information extracted obtained from mobile-sensed LiDAR data (i.e., ramps, steps, and pedestrian crossings), detecting obstacles using volunteered information collected from the hardware sensors of the mobile devices of the citizens (i.e., ramps and steps), and detecting accessibility problems with software sensors in social networks (i.e., Twitter). The information system is validated through its application in a case study in the city of Vigo (Spain)., This work was supported in part by the project Friendly barrierLess AdapTable City (FLATCity) (Ministerio de Ciencia, innovación y Universidades/ERDF, EU) funded by the Spanish Agencia Estatal de Investigación (AEI, doi 10.13039/501100011033), and in part by the European Regional Development Fund (ERDF), under Grants TIN2016-77158-C4-1-R, TIN2016-77158-C4-2-R and TIN2016-77158-C4-3-R. This work was also supported in part by the project Massive Geospatial Data Storage and Processing for Intelligent and Sustainable Urban Transportation (MaGIST), funded by the Spanish Agencia Estatal de Investigación (AEI, doi 10.13039/501100011033) under grants PID2019-105221RB-C41, PID2019-105221RB-C43 and PID2019-105221RB-C44. The research of Miguel R. Luaces was also partially founded by: Xunta de Galicia/FEDER-UE GRC: ED431C 2017/58 and Xunta de Galicia/FEDER-UE, ConectaPeme, GEMA: IN852A 2018/14. Miguel R. Luaces also wishes to acknowledge the support received from the Centro de Investigación de Galicia “CITIC”, funded by Xunta de Galicia and the European Union (European Regional Development Fund- Galicia 2014-2020 Program), by grant ED431G 2019/01. Jesús Balado and Lucía Díaz-Vilariño would like to thank to the Xunta de Galicia given through human resources grants ED481B-2019-061 and ED481D 2019/020, respectively, Xunta de Galicia; ED431C 2017/58, Xunta de Galicia; IN852A 2018/14, Xunta de Galicia; ED481B-2019-061, Xunta de Galicia; ED481D2019/020, Xunta de Galicia; ED431G 2019/01

© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/. This version of the article “Brisaboa, N.R., Cerdeira-Pena, A., de Bernardo, G., Navarro, G., Pedreira, Ó., 2020. Extending general compact querieable representations to GIS applications. Information Sciences 506, 196–216” has been accepted for publication in Information Sciences. The Version of Record is available online at https://doi.org/10.1016/j.ins.2019.08.007, [Abstract]: The raster model is commonly used for the representation of images in many domains, and is especially useful in Geographic Information Systems (GIS) to store information about continuous variables of the space (elevation, temperature, etc.). Current representations of raster data are usually designed for external memory or, when stored in main memory, lack efficient query capabilities. In this paper we propose compact representations to efficiently store and query raster datasets in main memory. We present different representations for binary raster data, general raster data and time-evolving raster data. We experimentally compare our proposals with traditional storage mechanisms such as linear quadtrees or compressed GeoTIFF files. Results show that our structures are up to 10 times smaller than classical linear quadtrees, and even comparable in space to non-querieable representations of raster data, while efficiently answering a number of typical queries., Partially funded by: IMFD; Xunta de Galicia/FEDER-UE grants CSI:ED431G/01 and GRC:ED431C 2017/58; Xunta de Galicia/FEDER-UE, ConectaPeme grant
GEMA: IN852A 2018/14; Xunta de Galicia/GAIN grant Innovapeme: IN848D-2017-2350417; by MINECO-AEI/FEDER-UE grants Flatcity: TIN2016-77158-C4-3-R,
Datos 4.0: TIN2016-78011-C4-1-R and ETOME-RDFD3: TIN2015-69951-R; MICINN-AEI/FEDER-UE grants Steps: RTC-2017-5908-7 and BIZDEVOPS: RTI2018-
098309-B-C32; and EU H2020 MSCA RISE BIRDS: 690941. An early partial version of this article appeared in Proc SPIRE’13. Some parts of this work
also appeared in G. de Bernardo’s PhD thesis., Xunta de Galicia; ED431G/01, Xunta de Galicia; ED431C 2017/58, Xunta de Galicia; IN852A-2018/14, Xunta de Galicia; IN848D-2017-2350417