Generation of change data of land cover in the Bogotá savannah using time series with Landsat images and MODIS-Landsat synthetic images between 2007 and 2013
DOI:
https://doi.org/10.4995/raet.2019.12280Keywords:
synthetic images, MODIS, Landsat, time series, land coverAbstract
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.
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