3 citations · 4 across the 4 of their papers we have counts for
4 papers
STeMP: Spatio-Temporal Modelling Protocol
Jan Linnenbrink, Jakub Nowosad, Marvin Ludwig +4
Spatio-temporal machine-learning modelling is an important tool in environmental research. However, machine-learning models are highly sensitive to both the characteristics of the…
Moving beyond spatial and random cross-validation in environmental modelling: a call for prediction-domain adaptive evaluation
Jan Linnenbrink, Jakub Nowosad, Hanna Meyer
With the growing application of spatial predictive modeling in ecology, the question of how to appropriately evaluate the resulting maps has gained increasing attention. While ther…
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…
The landscapemetrics and motif packages for measuring landscape patterns and processes
Jakub Nowosad, Maximilian H. K. Hesselbarth
This book chapter emphasizes the significance of categorical raster data in ecological studies, specifically land use or land cover (LULC) data, and highlights the pivotal role of…