GeoKG-HSA: A framework for habitat suitability assessment with geospatial knowledge graphs

Habitat suitability, which reflects how well environmental conditions support species survival, growth, and reproduction, is highly sensitive to climate change and human activities and underpins effective conservation policy-making. Traditional machine learning models for habitat suitability assessm...

Descrizione completa

Dettagli Bibliografici

Autori principali:	Xin Xiao, Peng Wang, Yong Ge, Jin Luo, Hao Chen, Yufeng He, Die Zhang, Yankuo Li, Chaoyang Fang, Hui Lin
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2025-11-01
Serie:	International Journal of Applied Earth Observations and Geoinformation
Soggetti:	Habitat suitability assessment Geospatial knowledge graph Environmental modelling Knowledge-driven Machine learning
Accesso online:	http://www.sciencedirect.com/science/article/pii/S1569843225005680
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!