Currently, new tools have been implemented that merge high-resolution temporal and spatial images for detection of change land cover. With the purpose of evaluate this type of techniques we generated a time series with Landsat satellite imagery and a time series with simulated images Landsat-MODIS, with the purpose of determining which of the two methods provides the best results in the change quantification in the Sabana of Bogota between 2007 and 2013. The processing consists of (i) Time Series with images Landsat trough BFAST, (ii) getting synthetic images through the ESTARFM algorithm; (iii) time series through BFAST with the use of simulated images. In the time series process, the series incorporating synthetic images and images corrected by the gaps generated the best accuracy indexes (global accuracy: 88.16% y Kappa: 76.52%) with respect to the series that incorporated only the images Landsat (global accuracy: 83% y Kappa: 65.18%); it indicates that densification of time series allow to get the best results in the quantification of changes and dynamics of land cover. The methodology applied represents an advance about generation of synthetic images and monitoring and detection of changes in land cover through time series. This is one of the first studies realized in the country that includes this type of process. ; Actualmente, se han implementado nuevas herramientas para la fusión de imágenes de alta resolución temporal y espacial y para la detección de cambios de coberturas. Con el fin de evaluar este tipo de técnicas se generó una serie de tiempo con imágenes Landsat y una serie de tiempo con imágenes sintéticas LandsatMODIS, con el fin de determinar cuál de los dos métodos proporciona los mejores resultados en la cuantificación de los cambios de las coberturas de la Sabana de Bogotá entre los años 2007 y 2013. El procesamiento consiste en: (i) Serie Temporal con imágenes Landsat a través de BFAST (Breaks For Additive Seasonal and Trend), (ii) Obtención de imágenes sintéticas por medio del algoritmo ...