14 citations as recorded by crossref.

1. Identifying critical fire spread to the wildland–urban interface using cellular automata and reinforcement learning J. González-Villa et al. https://doi.org/10.1016/j.mlwa.2025.100779
2. Spatial entropy drives the maintenance and dissemination of transferable plasmids W. Xue et al. https://doi.org/10.1038/s44320-025-00110-8
3. In-silico CT simulations of deep learning generated heterogeneous phantoms C. Salinas et al. https://doi.org/10.1088/2057-1976/ade9c9
4. ALGR: A multi-purpose agricultural landscape generator in R E. Goldstein et al. https://doi.org/10.1371/journal.pone.0334745
5. Generation of random geological models using multi-randomization for machine learning K. Gao & T. Chen https://doi.org/10.1016/j.cageo.2026.106133
6. A least-cost network neutral landscape model of human sites and routes T. Etherington et al. https://doi.org/10.1007/s10980-024-01836-w
7. A multi-view approach for bulk material volume estimation D. Picchi & S. Brell-Cokcan https://doi.org/10.1007/s41693-026-00179-z
8. One cannot have it all: Trading-off ecosystem services and biodiversity bundles in landscape connectivity restoration M. Neyret et al. https://doi.org/10.1016/j.biocon.2024.110946
9. Adaptive Traversability Policy Optimization for an Unmanned Articulated Road Roller on Slippery, Geometrically Irregular Terrains W. Qiang et al. https://doi.org/10.3390/machines14010079
10. Impact of noise on landscapes and metrics generated with stream power models M. Morris & G. Roberts https://doi.org/10.5194/esurf-13-1003-2025
11. Rapid urban flood inundation forecasting using a physics-informed deep learning approach F. Yang et al. https://doi.org/10.1016/j.jhydrol.2024.131998
12. A Space-Time Plume Algorithm to Represent and Compute Dynamic Places B. Dell & M. Yuan https://doi.org/10.3390/computers14070278
13. Computational Methods in Landscape Ecology M. Hesselbarth et al. https://doi.org/10.1007/s40823-024-00104-6
14. Binary space partitioning generates hierarchical and rectilinear neutral landscape models suitable for human-dominated landscapes T. Etherington et al. https://doi.org/10.1007/s10980-022-01452-6