Habitat inference from biodiversity field notes

Mozhdehi, Mahsa Hadikhah, Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881, Perkins, Sarah E. ORCID: https://orcid.org/0000-0002-7457-2699 and Jones, Christopher B. ORCID: https://orcid.org/0000-0001-6847-7575 2026. Habitat inference from biodiversity field notes. Presented at: KDD '26: The 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Jeju Island, Republic of Korea, 9-13 August 2026. Published in: Kim, Won, Lee, Jae-Gil and Shim, Kyuseok eds. KDD '26: Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, pp. 11038-11049. 10.1145/3770855.3818941

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Abstract

Systematic land-cover products derived from remote sensing extend back only a few decades, leaving major gaps for earlier periods. In contrast, biodiversity occurrence repositories provide vast numbers of geo-referenced records spanning much longer time horizons, and many records include free-text habitat notes describing local conditions. This motivates habitat inference from text as a scalable route to extending habitat knowledge before the satellite era. However, this problem has thus far received limited attention and is technically challenging. To support work on this topic, we introduce a benchmark that aggregates habitat-note text into spatial grid-cell documents with proxy supervision from land-cover maps, and we present an extensive analysis of text-based predictors and graph-enriched classification pipelines for inferring standard habitat classes. Among others, we find that LLM encoders struggle with the noisy nature of the input texts and the subtle distinctions between the labels, while taking into account geographic proximity and environmental similarity can significantly boost results.

Item Type:	Conference or Workshop Item - published (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Computational & Mathematical Sciences Schools > Computer Science & Informatics Schools > Biosciences
Publisher:	ACM
ISBN:	9798400722592
Date of First Compliant Deposit:	13 August 2026
Last Modified:	13 Aug 2026 13:00
URI:	https://orca.cardiff.ac.uk/id/eprint/188969

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