1 citations · 2 across the 3 of their papers we have counts for
4 papers
A Machine Learning API for Earth Observation Data Cubes Based on openEO
Brian Pondi, Jonas Hurst, Rolf Simoes +3
Earth Observation (EO) data are increasingly organized as spatio-temporal data cubes, while machine learning (ML) methods operate on tabular feature matrices or structured tensor i…
Spatial Data Science Languages: commonalities and needs
Edzer Pebesma, Martin Fleischmann, Josiah Parry +8
Recent workshops brought together several developers, educators and users of software packages extending popular languages for spatial data handling, with a primary focus on R, Pyt…
Efficient data-driven gap filling of satellite image time series using deep neural networks with partial convolutions
Marius Appel
The abundance of gaps in satellite image time series often complicates the application of deep learning models such as convolutional neural networks for spatiotemporal modeling. Ba…
Spatiotemporal Multi-Resolution Approximations for Analyzing Global Environmental Data
Marius Appel, Edzer Pebesma
Technological developments and open data policies have made large, global environmental datasets accessible to everyone. For analysing such datasets, including spatiotemporal corre…