LAND COVER CHANGES IN COFFEE CULTURAL LANDSCAPES OF PEREIRA (COLOMBIA) BETWEEN 1997 AND 2014

Understanding how and what land cover changes and transitions have occurred in a territory is crucial to planning and managing high-demand surfaces. At the landscape level, the challenge is determining the allocation and management of various land cover options. Therefore, for natural resources planning and management, a study characterizing and analysing the territory of interest should be included. This work aimed to analyse the changes and land cover patterns in the city of Pereira, Colombia, within the framework of the Colombian Coffee Cultural Landscape. The evaluated period was between 1997 and 2014, and a Geographic Information System, ENVI 4.8 programme and QGIS programme were used for multitemporal analysis. To describe the land cover transitions, two temporal moments were analysed with Landsat satellite images: one moment was for the year 1997, which was taken in August (Landsat 5), and the other moment was for the year 2014, which was taken in July (Landsat 8). At level 1 of CORINE (Coordination of information on the environment), the areas of land cover corresponding to agricultural areas, forests and semi-natural areas decreased most in the analysis period, while artificial surfaces increased. At level 3, the cover with the greatest decrease in territory was coffee crops, which showed a negative annual loss rate of -3.97%, followed by permanent crops (2.67%). The continuous and discontinuous urban fabric showed the greatest growth with a positive annual rate of 4.14%. In conclusion, the land cover that lost the most territory was coffee crop, mainly due to political-economic factors, such as the dissolution of the International Coffee Agreement and the National Federation of Coffee Growers that discouraged coffee cultivation and permanent crops. Likewise, sociocultural factors, such as smallholder farmers have guided the changes in land cover and have stimulated productive styles to adapt and remain, increasing heterogeneous agricultural areas.