Geospatial Systems - Luis Patino Velasquez
In partnership with
Luis Patino Velasquez
G.19a Cassie Building, Newcastle University, NE1 7RU
About Luis Patino Velasquez
My name is Luis Felipe and I am originally from Colombia, but I have been settled in the UK for almost 15 years now. I hold a MSc in Environmental Mapping from University College London and after completing my degree I spent over 8 years in industry. My background is in the use, development, deployment and management of desktop and web-based geographic information systems (GIS) and business intelligence (BI) systems.
Before joining the CDT I worked as a GIS researcher and project coordinator. I worked for and in partnership with NGOs, in both corporate and governmental organisations. This included planning and delivering GIS solutions for research and engagement purposes in international projects, focused on the sustainability of natural ecosystems and citizen science.
Some of the projects that I have worked on include:
- The development of a global web-based catchment hydrological information platform (CatchX- https://ewgis.org/catchx-global/) providing access to standard water balance information at a river catchment level, without the need for complex GIS or hydrological modelling skills. This project was funded by the Natural Environmental Research Council (NERC) as it was a partnership between University of Leeds, University of Rhodes – South Africa, and Earthwatch Institute
- The development of The Bath Spa Observer (https://www.bathspa.ac.uk/projects/bath-spa-observer/), a digital mapping platform to facilitate student learning by using state of the art technology for data capture and use in the classroom.
Additionally, I have had the opportunity of working as part of teams delivering projects funded as part of the European Union’s Horizon 2020 research and innovation programme. These include projects developing citizen observatories focusing on flora and fauna, water availability and water quality, as well as measuring the impact of citizen science.
Alongside my previous work and now studies, I volunteer for MapAction, which provides emergency mapping in humanitarian disasters, as well as training and capacity building for disaster management.
Working on the PhD as part of the ESPRC Centre for Doctoral Training is a great opportunity to work, share and learn from leaders in the field of Geospatial technologies in the areas of research and industry. Moreover, having the opportunity of being part of this programme has enabled me to start fulfilling a life goal of becoming an accredited researcher.
In the long term, I have an ambitious plan to work in the use of GeoAI to enable a greater understand of the impacts of climate change in Water Risks and Food Security in a humanitarian context in the Global South. This is with the desire to produce actionable knowledge for the benefit of society as a whole.
Coupling a physically-based, spatially distributed hydrological model with an Open Data Cube (ODC) ecosystem as data repository and analysis tool to quantify the impacts of climate change in water security.
For many areas across the globe physically-based hydrological models have a fundamental role helping devise a comprehensive and robust plan for future climate change adaption and preparedness, informing water management and flood initiatives, as well as enhancing knowledge of local and regional hydrological processes. Whilst the use of physically-based hydrological models have been restricted by the nature of the process i.e. large data volumes and greater computational resources required (Lewis et at., 2018), recent advances on satellite derived analysis ready data (ARD) availability and computational environments (online and local deployments) have served as catalyst to a wider use of these models (Sun et al., 2019, Saran et al., 2021).
In this context, this research has the purpose to examine the effects of climate change on water security through the application of the open and freely available earth observation satellite data architecture made available by the Open Data Cube project (https://www.opendatacube.org) in conjunction with the SHETRAN model (Ewen et al., 2000) utilising a freely available computation environment (JupyterHub). This research will be expected to contribute towards the implementation and adaptation strategies of the Sustainable Development Goals (SDG’s), in particular SDG 6 (clean water and sanitation), SDG 11 (Sustainable cities and communities) and SDG 13 (climate action).