Brian Pondi

26 Followers
23 Following
26 Posts
Researcher | Geospatial Machine Learning | PhD Geoinfomatics Candidate

Our paper, Machine Learning Model Specification for Cataloging Spatio-Temporal Models, is now available online. It will be presented at the ACM SIGSPATIAL 2024 (GeoSearch'24) conference, which starts tomorrow in Atlanta, Georgia, USA. #ml #GeoAI #geochat

Link to paper: https://doi.org/10.1145/3681769.3698586

Machine Learning Model Specification for Cataloging Spatio-Temporal Models (Demo Paper) | Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data

ACM Conferences

We're pleased to share our latest work, published in Earth Science Informatics: "OpenEOcubes: an open-source and lightweight R-based RESTful web service for analyzing earth observation data cubes". This work is now accessible as an open-access document

code: https://github.com/PondiB/openeocubes

paper: https://doi.org/10.1007/s12145-024-01249-y

#EarthObservation #OpenSource #RemoteSensing #gischat

GitHub - PondiB/openeocubes: A lightweight R-based RESTful service to analyze Earth Observation data cubes in the cloud.

A lightweight R-based RESTful service to analyze Earth Observation data cubes in the cloud. - PondiB/openeocubes

GitHub
We are seeking a highly motivated Doctoral Research Associate to work on an EU-funded project in the Spatio-Temporal Modelling Lab, led by Prof Edzer Pebesma. The project “Embed2Scale” is an EU-financed project which aims to develop AI-based compression methods to strongly reduce the size of very large Earth observation datasets, in order to make them more useful or to allow researchers to combine datasets hosted at different data centers.
Job Description: https://lnkd.in/eHX7pqSs
Wissenschaftliche Mitarbeiter