Foliar Functional Trait Mapping of a mixed temperate forest using imaging spectroscopy contains mapped predictions, uncertainties, and model data for leaf traits in a Quebec forest. The dataset includes field-measured foliar traits, mean canopy reflectance per tree crown, and brightness-normalized reflectance. It was authored by Gravel, Laliberté, and Kalacska and published in 2024.
Use Cases
- Modeling forest productivity and nutrient cycling based on mapped foliar functional traits.
- Calibrating remote sensing algorithms using field-measured foliar traits and canopy reflectance data.
- Assessing prediction uncertainty in ecological mapping based on the provided uncertainty and relative uncertainty layers.
- Studying trait-environment relationships in temperate forests using the combined spatial and field measurement data.
Strengths
- Includes both the final mapped predictions and the underlying model coefficients and training data.
- Provides uncertainty and relative uncertainty estimates for the trait predictions.
- Combines field-measured foliar traits with remotely sensed canopy reflectance data.
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count and file size are unknown, which may limit suitability assessment.
Provenance
- Source
- Gravel, A., Laliberté, E., Kalacska, M. via Federated Research Data Repository.
- Collection Method
- Field measurements and imaging spectroscopy (hyperspectral) data collection.
- Freshness
- Last updated 2026-06-06 04:11:09; freshness should be verified.
- Geography
- A mixed temperate forest in Quebec, Canada.