data and onto accept Raster* (raster) and stars objects in addition to SpatRaster, and the result is returned in the class of onto. The new output argument requests a specific class.
onto may be an sf or SpatVector of points: the fitted relationship is evaluated at each point and returned as a prediction column, with the points carrying the fine predictor values as attributes. This makes downscaling to station or plot locations a single call. The coefficients and anomaly results are returned as columns in the same way.
topocast 0.0.2
topocast() derives a coarse predictor from onto when the predictor named in the formula is not a layer of data, aggregating it to the response grid with the new aggregate argument. The one-DEM case is now a single call from a coarse climate layer and a fine elevation model (#1).
coefficients = TRUE returns the fitted layer together with the (Intercept) and per-predictor slope grids on the onto grid, so the local relationship, such as a precipitation lapse rate, can be mapped (#2).
Coordinate reference systems that share an EPSG code are treated as equal even when their WKT strings differ, as happens with cross-source lon/lat data. A genuine mismatch now names both systems and suggests how to align them (#3).
topocast 0.0.1
First release.
topocast() downscales a coarse raster onto fine terrain by moving-window regression. The relationship is a formula of layer names (prec ~ elev + slope); the response and coarse predictors live in one data raster and the fine predictors in onto. Coefficient grids are estimated with summed-area tables, so the cost is independent of the window radius.
A time series is downscaled by passing a stack of coarse periods as anomaly: the baseline climatology is downscaled once and each period’s anomaly is carried onto it, type = "ratio" or type = "additive".