Geo-AI for landslide susceptibility in Rwanda: integrating LiDAR, soil moisture, and historical data

Moradeke Grace Adewumi, Isaac Olajide Areo, Kalisa Theotime Muhigira, Thompson Faraday Ediagbonya

Open source

DOI: 10.1080/10106049.2026.2696122
Published: 12
Container: Geocarto International
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1080/10106049.2026.2696122,
  title = {Geo-AI for landslide susceptibility in Rwanda: integrating LiDAR, soil moisture, and historical data},
  author = {Moradeke Grace Adewumi and Isaac Olajide Areo and Kalisa Theotime Muhigira and Thompson Faraday Ediagbonya},
  year = {2026},
  journal = {Geocarto International},
  doi = {10.1080/10106049.2026.2696122},
  url = {https://doi.org/10.1080/10106049.2026.2696122}
}

RIS

TY  - JOUR
TI  - Geo-AI for landslide susceptibility in Rwanda: integrating LiDAR, soil moisture, and historical data
AU  - Moradeke Grace Adewumi
AU  - Isaac Olajide Areo
AU  - Kalisa Theotime Muhigira
AU  - Thompson Faraday Ediagbonya
PY  - 2026
JO  - Geocarto International
DO  - 10.1080/10106049.2026.2696122
UR  - https://doi.org/10.1080/10106049.2026.2696122
ER  -

APA

Adewumi, M. G., Areo, I. O., Muhigira, K. T., & Ediagbonya, T. F. (2026). Geo-AI for landslide susceptibility in Rwanda: integrating LiDAR, soil moisture, and historical data. Geocarto International. https://doi.org/10.1080/10106049.2026.2696122

Source records

doaj · retrieved 2026-09-25T22:55:05.343Z