The importance of topological validation processes when managing changes in land property

Las tecnologías de la información y la comunicación están consiguiendo que la información geográfica sea asequible a un mayor número de profesionales a través de las Tecnologías de la Información Geográfica. La intervención multidisciplinar en el territorio enriquece la investigación y las formas de aplicación de este tipo de recursos tecnológicos. Pero esta facilidad tecnológica puede suponer el riesgo de un uso inadecuado, por falta de conocimientos técnicos adecuados a la complejidad de la información geográfica o por el mal uso de las aplicaciones informáticas. El trabajo catastral puede beneficiarse mucho del empleo de estas tecnologías de información geográfica, al facilitar el uso, la comunicación y su administración electrónica, pero el desconocimiento de las propiedades geométricas y topológicas de la información geográfica puede llevar a cometer errores de graves consecuencias a profesionales no especializados. En este artículo ofrecemos el resultado de la investigación del trabajo de diversos juristas y técnicos, con el objetivo de desarrollar métodos automatizados y aplicaciones informáticas que permitan a los especialistas no expertos en Cartografía usar este tipo de información con garantías de exactitud al más alto nivel, como una solución eficaz para que la información geográfica con calidad topológica enriquezca la seguridad jurídica en el tráfico inmobiliario.Information and Communications Technology (ICT) is making Geographic Information (GI) reachable to an increasing number of professionals through technology. A multidisciplinary approach to land resources assessment enriches research and encourages new implementations of this type of technological resources, but the affordability of Geographic Information Technology (GIT) may lead to misuse due to lack of knowledge about GI complexity or poor user skills when working with computer applications. Cadastral tasks can greatly benefit from the use of GIT to empower transparent transactions and e-government, but failing to handle geometric and topological properties when dealing with GI may lead to mistakes with serious consequences for non-skilled professionals. In this article, we show results of a research work conducted by a team of both, legal and technical professionals, whose main goal is the development of automated methods and mapping software that allow non-experts to fully embrace GI while preserving the highest level of accuracy. We foresee this as an effective solution to encompass real estate data transactions with topologically accurate GI and, thus, as a means to enforce for legal certainty.Este trabajo se ha realizado como resultados del Proyecto de Investigación Aplicada “Ramón Llull”, realizado en el Laboratorio de Geomática del Instituto Interuniversitario de Geografía y el Departamento de Derecho Civil de la Universidad de Alicante bajo el patrocinio del Consejo General del Notariado y Colegio Notarial de Valencia. Además, se inscribe en el marco del proyecto de investigación «El Registro de la Propiedad como instrumento vertebrador de la información territorial; datos espaciales, metadatos y Directiva INSPIRE (II)» (DER 2011-23321), financiado por el Ministerio de Economía y Competitividad

Estrategias de diseño de software para la actualización de parcelas catastrales: el caso del proyecto Ramón Llull

El Catastro Inmobiliario es un registro administrativo dependiente del Ministerio de Hacienda y Administraciones Públicas regulado por el Texto Refundido de la Ley del Catastro Inmobiliario 1/2004, que establece que la inscripción de un inmueble en el Catastro es obligatoria y gratuita. La representación cartográfica de los bienes inmuebles es uno de los aspectos fundamentales a la hora de inscribirlos en este registro oficial. Esta descripción gráfica cambia cuando se producen transacciones de fincas que afectan a la delimitación física de la propiedad, lo que conlleva tanto un control jurídico como técnico. El proyecto de investigación “Ramón Llull” se centra en el desarrollo de software de geoprocesamiento para comprobar y validar estos procesos de alteración catastral y subsanación de discrepancias en los que intervienen los Notarios. Uno de los logros fundamentales es una herramienta de gestión de expedientes de alteración que permite además coordinar el trabajo de la notaría con el del técnico competente e incorporar la información gráfica de la propiedad a la escritura. Para el desarrollo de esta aplicación ha sido preciso planificar el proceso de diseño que ha seguido el equipo investigador a la hora de escribir código fuente estable y de calidad. En el presente trabajo se analiza cómo han influido estas decisiones en el resultado. La valoración y la elección de software libre, los patrones de diseño de software y la interoperabilidad de datos y servicios son los factores en los que se centra el estudio. Todos ellos han condicionado el producto final: un sistema de geoprocesamiento que permite que una transacción inmobiliaria entre particulares y la correspondiente actualización de la cartografía catastral coincidan en tiempo y forma.Este trabajo se enmarca dentro del proyecto de investigación Ramón Llull dirigido por Alfredo Ramón Morte, profesor titular del Departamento de Análisis Geográfico Regional y Geografía Física, y por Antonio Jiménez Clar, profesor asociado del Departamento de Derecho Civil, y ha sido financiado por el Colegio Notarial de Valencia. Además, se inscribe en el marco del proyecto de investigación «El Registro de la Propiedad como instrumento vertebrador de la información territorial; datos espaciales, metadatos y Directiva INSPIRE (II)» (DER 2011-23321), financiado por el Ministerio de Economía y Competitividad

Leveraging Container Technologies in a GIScience Project: A Perspective from Open Reproducible Research

Scientific reproducibility is essential for the advancement of science. It allows the results of previous studies to be reproduced, validates their conclusions and develops new contributions based on previous research. Nowadays, more and more authors consider that the ultimate product of academic research is the scientific manuscript, together with all the necessary elements (i.e., code and data) so that others can reproduce the results. However, there are numerous difficulties for some studies to be reproduced easily (i.e., biased results, the pressure to publish, and proprietary data). In this context, we explain our experience in an attempt to improve the reproducibility of a GIScience project. According to our project needs, we evaluated a list of practices, standards and tools that may facilitate open and reproducible research in the geospatial domain, contextualising them on Peng’s reproducibility spectrum. Among these resources, we focused on containerisation technologies and performed a shallow review to reflect on the level of adoption of these technologies in combination with OSGeo software. Finally, containerisation technologies proved to enhance the reproducibility and we used UML diagrams to describe representative work-flows deployed in our GIScience project.This work has been funded by the Generalitat Valenciana through the “Subvenciones para la realización de proyectos de I+D+i desarrollados por grupos de investigación emergentes” programme (GV/2019/016) and by the Spanish Ministry of Economy and Competitiveness under the subprogrammes Challenges-Collaboration 2014 (RTC-2014-1863-8) and Challenges R+D+I 2016 (CSO2016-79420-R AEI/FEDER, EU). Sergio Trilles has been funded by the postdoctoral programme PINV2018 - Universitat Jaume I (POSDOC-B/2018/12) and stays programme PINV2018 - Universitat Jaume I (E/2019/031)

Objective assessment of land use in hydrographical studies

The behaviour of floods depends on two main factors: Manning’s roughness coefficient and the threshold runoff, P0. In both parameters, land cover plays a vital role in the characterisation of small streams, which traditionally are altered in the Mediterranean basin. However, in the absence of an assessment protocol that optimises the geographical information stored in the official repositories, studies in these areas tend to be subjective, depending on the personal criteria of the technicians in charge of the study. In this paper a new method is proposed for the determination of these parameters, based on the integration of the Spanish national system for the mapping of flood-prone areas (SNCZI), which was designed by the Spanish Geological and Mining Institute (IGME), and the spatial data of the Spanish land cover and use information system (SIOSE database), designed by the Spanish National Geographic Institute (IGN). The methodology generates roughness data based on objective criteria and on a threshold runoff map, which can be reviewed by the technician in charge of the study, but which is based on updated, regulated and open official data. The result is a thorough hydrological and hydraulic characterisation, which has been tested in a western Mediterranean area characterised by the complexity of land use: the foothills between Sierra Helada and Sierra de la Cortina in the Municipality of Benidorm, located in the province of Alicante, Spain.The authors are grateful to the SIOSE-INNOVA Project (CSO2016-79420-R AEI/FEDER UE) and Interuniversity Institute of Geography, University of Alicante

Should EU Land Use and Land Cover Data be managed with a NoSQL Document Store?

Land cover (LC) is a scientific landscape classification based on physical properties of earth materials. This information is usually retrieved through remote sensing techniques (e.g. forest cover, urban, clay content, among others). In contrast, Land use (LU) is defined from an anthropocentric point of view. It describes how a specific area is used (e.g. it is usual to indicate whether a territory supports an intensive, extensive use or it is unused). Both geospatial layers are essential inputs in many socio-economic and environmental studies. The INSPIRE directive provides technical data specifications for harmonization and sharing of voluminous LU/ LC datasets across all countries of the EU. The INSPIRE initiative proposes Object-Oriented Modelling as a data modelling methodology. However, the most used Geographic Information Systems (GIS) are built upon relational databases. This may jeopardize LU/LC data usability, since GIS practitioners will eventually face the object-relational impedance mismatch. In this paper, the authors introduce the SIOSE database (Spanish Land Cover and Land Use Information System), which was the first implementation of an object-oriented land cover and Land-use datamodel, in line with the recommendation of the INSPIRE Directive, separating both themes. SIOSE data can be downloaded as relational database files, where information describing each single LU/LC object is divided among several related tables, so database queries can be complex and time consuming. The authors show these technical complexities through a computational experience, comparing SQL and NoSQL databases for querying spatial data downloaded from SIOSE. Finally, the authors conclude that NoSQL geodatabases deserve to be further explored because they could scale for LU/LC data, both horizontally and vertically, better than relational geodatabases, improving usability and making the most of the EU harmonization efforts

Propuesta de una plataforma web para aplicar técnicas de visualización en didáctica de la Geografía

En esta comunicación se destaca el potencial pedagógico de las TICs en la enseñanza de los contenidos sobre la estructura y dinámica de la población. Las técnicas de visualización de datos cobran especial interés debido a su auge en numerosas disciplinas científicas. A pesar de los beneficios que pueden aportar, el uso de estas tecnologías no se ha generalizado tanto como sería esperable. Esta escasa adopción por parte de los docentes en Ciencias Sociales está relacionada con la complejidad de las herramientas y la ausencia de interfaces de usuario intuitivos. En esta comunicación se han diseñado herramientas que solucionen estos problemas

Advances in camera trap data management tools: Towards collaborative development and integration with GIS

Camera traps have become a widely used technique for conducting biological inventories, generating a large number of database records of great interest. The main aim of this paper is to describe a new free and open source software (FOSS), developed to facilitate the management of camera-trapped data which originated from a protected Mediterranean area (SE Spain). In the last decade, some other useful alternatives have been proposed, but ours focuses especially on a collaborative undertaking and on the importance of spatial information underpinning common camera trap studies. This FOSS application, namely, “Camera Trap Manager” (CTM), has been designed to expedite the processing of pictures on the .NET platform. CTM has a very intuitive user interface, automatic extraction of some image metadata (date, time, moon phase, location, temperature, atmospheric pressure, among others), analytical (Geographical Information Systems, statistics, charts, among others), and reporting capabilities (ESRI Shapefiles, Microsoft Excel Spreadsheets, PDF reports, among others). Using this application, we have achieved a very simple management, fast analysis, and a significant reduction of costs. While we were able to classify an average of 55 pictures per hour manually, CTM has made it possible to process over 1000 photographs per hour, consequently retrieving a greater amount of data.This project has been carried out thanks to the UNCROACH project (CGL-2011-30581-CC02-01) from the Spanish Ministry of Economy and Competitiveness; and has been partially funded by the public call for research projects of the Conselleria of Education (T6217-2010); and the Institute of Culture Juan Gil-Albert-Alicante

Open data repositories and Geo Small Data for mapping the wildfire risk exposure in wildland urban interface (WUI) in Spain: A case study in the Valencian Region

The risk of forest fires in areas of wildland urban-interface (WUI.) is increasing due to the increase in urbanized areas and the progressive abandonment of traditional farming and forest uses. The global increase in catastrophic episodes in regions with a Mediterranean climate is worrying. Resilient towns and villages have given way to extensive and scattered residential estates that are in contact with forest fuel. These changes in the landscape when added to those of the climate, increase the danger of what some call ‘igneous storms’. The risk in many areas has increased greatly in the last few decades. It is necessary to limit the growing exposure to this type of risk – and geographical information resources are essential for determining the territorial magnitude of the problem. Official libraries offering remote sensing data or geographical databases on land use and land cover (LULC) may be the best option (although accessing this data is complex for many end users). This research proposes identifying areas exposed to fire risk in the wildland-urban interface (WUI) through the automated integration of massive data from official geographic information sources. The application of this study to the region of Valencia (Spain) shows that the integration of these official sources of geographical information can achieve the objective at a detailed scale with relatively short processing times and for large geographical areas (approximately 8 h required to process about 70 Gb of LIDAR data). Geo Small Data techniques for the process of large datasets and its application to the objective of the study have been the best way to automate the analysis of lidar point clouds, with more than 5 billion echoes, through the use of free and open tools, containerization technologies, parallel processing and specific python libraries for geospatial data management. The LIDAR data has provided the necessary geometric definition to complement and improve the WUI area map from the reclassification of hundreds of thousands of polygons from the official Spanish land use geodatabase (SIOSE), achieving a map scale of more than 1: 25,000, for its part, the quality of the SIOSE geodatabase has allowed us to reduce the total LIDAR data to process by 97.8%.This work was supported by grants from the Spanish Ministry of Economy and Competitiveness (Project SIOSE-INNOVA - CSO 2016-79420-R AEI/FEDER.UE) and the methodology has been developed by the project research team. The cartographic result has been collected in an unpublished work that has been awarded the XII Edition ‘Pare Tosca’ Cartography Prize of the Valencian Government (Valencian Cartographic Institute - ICV)

Methodological Proposal for Automated Detection of the Wildland–Urban Interface: Application to the Metropolitan Regions of Madrid and Barcelona

Official information on Land Use Land Cover is essential for mapping wildland–urban interface (WUI) zones. However, these resources do not always provide the geometrical or thematic accuracy required to delimit buildings that are easily exposed to risk of wildfire at the appropriate scale. This research shows that the integration of active remote sensing and official Land Use Land Cover (LULC) databases, such as the Spanish Land Use Land Cover information system (SIOSE), creates the synergy capable of achieving this. An automated method was developed to detect WUI zones by the massive geoprocessing of data from official and open repositories of the Spanish national plan for territory observation (PNOT) of the Spanish national geographic institute (IGN), and it was tested in the most important metropolitan zones in Spain: Barcelona and Madrid. The processing of trillions of LiDAR data and their integration with thousands of SIOSE polygons were managed in a Linux environment, with libraries for geographic processing and a PostgreSQL database server. All this allowed the buildings that are exposed to wildfire risk with a high level of accuracy to be obtained with a methodology that can be applied anywhere in the Spanish territory.This research was funded by and conducted within the SIOSE-INNOVA Project (CSO2016-79420-R AEI/FEDER/UE, Ministry of Science and Innovation, Spain) and funded by the endowment of an award for conducting research with the objectives of sustainable development (SDGs) from the General Directorate for Cooperation and Solidarity of Government of Generalitat Valenciana (Spain)

A methodology for evacuation route planning inside buildings using geospatial technology

Evacuation route planning is a fundamental task for building engineering projects. Safety regulations are established so that all occupants are driven on time out of a building to a secure place when faced with an emergency situation. As an example, Spanish building code requires the planning of evacuation routes on large and, usually, public buildings. Engineers often plan these routes on single building projects, repeatedly assigning clusters of rooms to each emergency exit in a trial-and-error process. But problems may arise for a building complex where distribution and use changes make visual analysis cumbersome and sometimes unfeasible. This problem could be solved by using well-known spatial analysis techniques, implemented as a specialized software able to partially emulate engineer reasoning. In this paper we propose and test an easily reproducible methodology that makes use of free and open source software components for solving a case study. We ran a complete test on a building floor at the University of Alicante (Spain). This institution offers a web service (WFS) that allows retrieval of 2D geometries from any building within its campus. We demonstrate how geospatial technologies and computational geometry algorithms can be used for automating the creation and optimization of evacuation routes. In our case study, the engineers’ task is to verify that the load capacity of each emergency exit does not exceed the standards specified by Spain’s current regulations. Using Dijkstra’s algorithm, we obtain the shortest paths from every room to the most appropriate emergency exit. Once these paths are calculated, engineers can run simulations and validate, based on path statistics, different cluster configurations. Techniques and tools applied in this research would be helpful in the design and risk management phases of any complex building project