Evaluación de una metodología para la generación de modelos digitales del terreno a partir de estereofotogrametría digital aplicando el modelo de correlación por mínimos cuadrados mediante una red neuronal artificial
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Nowadays on the development of a variety of huge projects is necessary in the engineering field, more specifically in the Geomatic field, automation of many processes with high accuracy levels because of that the modeling of all factors zone could be more realistic as possible. This document makes a general approach to three fundamental topics to work on a project which overall objective is to evaluate a methodology for digital terrain model (DTM) production adding the artificial neural network (ANN) theory by the least squares model correlation. The high accuracy DTM development becomes an important data input in the implementation of risk mitigation projects by natural phenomena either land use planning or watersheds behavior; and so on, there are many other knowledge fields that detailed land measure of the area in a large scales provides characteristics that are the basis for specific analyzes on each one.
