Tracking Phenological Status and Ecological Interactions in a Hawaiian Cloud Forest Understory using Low-Cost Camera Traps and Visual Foundation Models
Luke Meyers, Anirudh Potlapally, Yuyan Chen, Mike Long, Tanya Berger-Wolf, Hari Subramoni, Remi Megret, Daniel Rubenstein

TL;DR
This study employs low-cost camera traps and foundation vision models to monitor plant phenology and ecological interactions in a Hawaiian cloud forest, revealing detailed trends and drivers of ecological change.
Contribution
It introduces a novel, cost-effective method combining camera traps and foundation models for fine-grained phenological and ecological monitoring in tropical forests.
Findings
Detected phenological trends not visible with traditional sampling
Enabled detailed analysis of flora-faunal interactions
Demonstrated effectiveness of foundation models in ecological image analysis
Abstract
Plant phenology, the study of cyclical events such as leafing out, flowering, or fruiting, has wide ecological impacts but is broadly understudied, especially in the tropics. Image analysis has greatly enhanced remote phenological monitoring, yet capturing phenology at the individual level remains challenging. In this project, we deployed low-cost, animal-triggered camera traps at the Pu'u Maka'ala Natural Area Reserve in Hawaii to simultaneously document shifts in plant phenology and flora-faunal interactions. Using a combination of foundation vision models and traditional computer vision methods, we measure phenological trends from images comparable to on-the-ground observations without relying on supervised learning techniques. These temporally fine-grained phenology measurements from camera-trap images uncover trends that coarser traditional sampling fails to detect. When combined…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRemote Sensing in Agriculture · Species Distribution and Climate Change · Smart Agriculture and AI
