PhD in Geospatial Systems CDT | Urban mobility https://research.ncl.ac.uk/geospatial-systems/According to the United Nations, an estimated 55.3 per cent of the world’s population lived in urban settlements in 2018. By 2030, urban areas are projected to house 60 per cent of people globally, with one in every three people living in cities with at least half a million inhabitants. This rapid increase of population in cities will generate important daily challenges to face, therefore, city authorities must develop new ways to provide efficient services for their citizens, being crucial to the implementation of the 2030 Agenda for Sustainable Development. This combination of growth in cities with the development and improvement of new technologies (e.g., AI, big data, smart sensors, simulations, modelling) opens an interesting and important time to face present and future urban challenges. One of these challenges refers to the development of a sustainable urban mobility. During this PhD I pretend to help in the improvement of ways people move in urban areas, reducing congestion and pollution for a more sustainable and resilient life. I am keen on urban mobility, modelling, simulations, geospatial data, smart city, urban policies and geo visualisation.

Discussion of spatio-temporal transport scenarios simulated using MATSim (agent-based model tool).Scenarios to increase the use of active modes and achieve a more sustainable transport sector were developed and analysed.

As a GIS Specialist I work with GIS data using QGIS and developing Python scripts. Also I work with PostGIS database in order to store GIS data related with different stages of projects. Until now, I have created a Python program that stamps the name of features that appear in images taken from a helicopter based on geometry and mathematical calculus, and I have created a tracking database to store and track the data at different stages of a project.

This is a personal project, related with the city of York and maps. I am passionate of maps, cartography, open data and GIS and as a combination of all of them, 'The new York Maps' website arose. There you can find:• Modern and interactive maps.• Different cartographic techniques to show data on maps.• Web mapping products.• Story maps related with features of York.The aim of the website is to: • Show the city from a different point of view.• Analyse the city using open data and data I acquire myself.• Empower inhabitants and turist with more data and information related with York.

BIM/CAD Processing Surveyor in TSP Projects (York, United Kingdom). I was involved in more than 20 projects in the railway environment. In this position I was in charge of:• Processing CAD and laser scanner data to create 3D models and drawings• Supporting other teams with CAD queries for different disciplines. • Carring out quality controls of point clouds, GIS data and AutoCAD deliverables.• Member of the “GIS Working Group”, which was created to introduce the GIS technology within the company, doing awareness campaigns for the employees.• Collecting data on site, using laser scanner, total station and levels.Some of the main projects were:• 3D models of Leeds and Huddersfield train stations in a great level of detail.• SuperGreens• TRU (Transpennine Route Upgrade) project.• Oxford corridor project.90% of success in terms of deadlines and final results.

Surveyor in Murphy Surveys Ltd. (Dublin, Ireland).I was involved in the AMHS project, in the upgrade of the INTEL factory (Fab24). In this project I was in charge of:• Industrial surveying works (setting out, leveling and as builts) in a high accurate clean room and other areas of the factory.• Scanning areas to create 3D deliverables.Also, I did scans on site, leveling and as builts in different locations of London and Cardiff.90% of success in the daily duties, reducing 25% of the deadlines in some of the tasks.

Scholarship holder at Technical University of Madrid.I was involded in the team in charge of the studies of the seismic hazard, risk, associated effects (landslides) and image classification to detect urban features in the SISMO-HAITI III project. This project was done using GIS technology and remote sensors (satellite images and LiDAR data).