Quantifying uncertainty in elevation models using kriging
نویسنده
چکیده
Raster based digital elevation models (DEM) are the basis of some of the most important GIS workflows: hydrologic modeling, site suitability, and cost path analysis. While there are several techniques for generating digital elevation models (DEMs), none of them can produce a true elevation surface. Locally varying measurement error and the inexactness of the interpolation methods contribute to the uncertainty of the model’s estimate of the true elevation value. Kriging models and geostatistical simulations available in the Geostatistical Analyst extension for ArcGIS 10.1 for Desktop to quantify the spatially varying uncertainty of a DEM derived from lidar data.
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