ECOSENSE
@ecosense-sfb-1537.bsky.social
DFG funded collaborative research centre (SFB 1537). Multi-scale quantification and modelling of spatio-temporal dynamics of ecosystem processes by smart autonomous sensor networks.
Different sensors were evaluated for accuracy, stability, and field applicability. One focus was to achieve a reliable thermal contact between sensor and the leaf surface for long-term, minimally invasive measurements.
These results help improving continuous leaf monitoring in natural ecosystems.
These results help improving continuous leaf monitoring in natural ecosystems.
October 28, 2025 at 7:52 AM
Different sensors were evaluated for accuracy, stability, and field applicability. One focus was to achieve a reliable thermal contact between sensor and the leaf surface for long-term, minimally invasive measurements.
These results help improving continuous leaf monitoring in natural ecosystems.
These results help improving continuous leaf monitoring in natural ecosystems.
The lightweight and minimally invasive ECOvette enables real-time measurements of VOCs, CO₂, and water vapour at the leaf level. Integrated multi-sensor monitoring of leaf temperature as well as ambient temperature and humidity ensures robust field data under natural conditions.
The lightweight and minimally invasive ECOvette enables real-time measurements of VOCs, CO₂, and water vapour at the leaf level. Integrated multi-sensor monitoring of leaf temperature as well as ambient temperature and humidity ensures robust field data under natural conditions.
September 26, 2025 at 1:33 PM
The lightweight and minimally invasive ECOvette enables real-time measurements of VOCs, CO₂, and water vapour at the leaf level. Integrated multi-sensor monitoring of leaf temperature as well as ambient temperature and humidity ensures robust field data under natural conditions.
The lightweight and minimally invasive ECOvette enables real-time measurements of VOCs, CO₂, and water vapour at the leaf level. Integrated multi-sensor monitoring of leaf temperature as well as ambient temperature and humidity ensures robust field data under natural conditions.