CrowNet is a continuous canopy monitoring system based on time-lapse trail cameras. The method was firstly proposed by Chianucci et al. 2021. After this first study, I created the collaborative CrowNet project, by installing several trail cameras in different forest sites in Italy, from 2022 to 2024.
Results of this first monitoring effort was recently accepted in Agricultural and Forest Meteorology (Chianucci et al. 2025. CrowNet: a trail-camera canopy monitoring system. Agr. For. Meteor. 10.1016/j.agrformet.2025.110596). After 3 years, more than 44,000 images were collected in 20 stands in 3 different forest areas over 3 years (The dataset is freely available at: Chianucci, Francesco; Lenzi, Alice; Minari, Emma; Gonnelli, Marco (2025), “CrowNet: a trail-camera canopy monitoring system”, Mendeley Data, V1, doi: 10.17632/gkr667jvhx.1)
Continuous daily time-series of leaf area index (Le) in beech forests derived from trail cameras in 2024. The grey dots refer to raw daily Le values, the black lines indicated the daily Le average, the orange line the fitted double-logistic phenological curve.
We further illustrated the potential of the trail-camera monitoring system by comparing continuous canopy estimates against repeated multispectral and LiDAR data. Additionally, we showed example on species-oriented phenology analysis based on canopy time-series
Difference in start and end of season (vertical dashed lines) in different tree species in mixed forests.
This study highlighted the reliability of CrowNet to provide reliable and continuous estimates of canopy structure. The analysis also confirmed the potential of these data for complementing, integrating or validating multi-temporal remotely-sensed data, and for performing vegetation phenology analyses at tree to stand scale.
The analysis also showed rooms for improvement of the monitoring system, which could involve more professional equipment such as security webcams, with weatherproof domes, and a power and transmission protocol for remotely-check data acquisition, storage and processing. We are already working on CrowNet 2.0!
Additionally, new studies are ongoing to demonstrate the potential of CrowNet also for supporting precision poplar plantation forestry… stay tuned!
The article is available at: Chianucci F., Lenzi A., et al. CrowNet: A trail-camera monitoring system. Agricultural and Forest Meteorology 2025,, doi:10.1016/j.agrformet.2025.110596