Methodology
ORBIDENSE combines environmental science, geospatial analysis, statistical modelling and reproducible data engineering while distinguishing observation, prediction, association and causal interpretation.
Geospatial analysis
Spatial datasets are aligned, transformed and analysed with explicit attention to coordinate systems, scale, temporal coverage and the spatial resolution appropriate to the research question.
Statistical modelling
Predictive, spatial, Bayesian and causal methods are considered according to the scientific question rather than treating any single modelling technique as universally preferable.
Validation and provenance
Research outputs are intended to document source datasets, assumptions, processing steps, limitations and uncertainty so that users can distinguish measured information from model-derived results.
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