High‑resolution elevation data underpins almost every spatial analysis we do in GIS—especially in forests where vertical structure defines habitat, biomass, wind exposure, fire behavior, hydrology, and the microclimates that sustain rare species. In rugged or densely vegetated environments, a coarse or biased elevation model propagates error everywhere: orthorectification drifts, hillshades mislead, slope/aspect misclassify, and canopy metrics saturate. The result is decisions made on blurred terrain that hides the very patterns we seek to manage. Precision elevation—derived from airborne LiDAR (Light Detection and Ranging)—solves this by separating the ground from the vegetation and delivering both a bare‑earth Digital Terrain Model (DTM) and a Digital Surface Model (DSM). Subtracting DTM from DSM gives a Canopy Height Model (DHM) that captures the true vertical architecture of the forest at sub‑meter resolution.
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Tracking COVID19 TIA 14d a 20220310
sa mejora drásticamente, una incidencia 10 veces menor (de media) que la de hace solo dos meses, que llegó a algunos máximos en determinadas ZBS a una incidencia de 4,500 casos por 100,000 habitantes… La presión en la calle baja levemente, ya se permite desde hace un par de semanas ir sin mascarilla por la calle y se comenta que la semana que viene probablemente se quitarán las mascarillas en interiores (qué ganas!).