Spatial Scenarios of Land-Use/Cover Change for the Management and Conservation of Paramos and Andean Forests in Boyacá, Colombia

Abstract

The aims of this study were to identify the dynamics of land use change, the factors associated to these changes, and potential transformations of paramo and Andean forest, through the modeling of land use change scenarios in the department of Boyacá, Colombia. Throughout the classification of satellite images, we assessed land use change in two time periods: 1998 to 2010 and 2010 to 2018. Seven transition sub-models were analyzed and associated to 36 explanatory variables. Three future scenarios of land use change were projected for the years 2030 and 2050: trend, agricultural expansion and conservation scenarios. We found a gradual reduction in paramos and Andean forests, together with an increase in secondary vegetation. The most relevant variables explaining land use change were: elevation, distance to roads and distance to protected areas. The scenario with the greatest impact in paramos and Andean forest was Agricultural Expansion, where forest would have a loss of 29% and 41% for 2030 and 2050, and Paramos 44% and 59% for the same years. Forest and paramos in the central eastern area showed critical losses and highly fragmented distributions in all scenarios; hence, we recommend focusing conservation efforts in these areas.

Scenarios of land use and land cover change in the Colombian Amazon to evaluate alternative post-conflict pathways

“…Neural network analysis and land use change factors. The artificial neural network multi-layer perceptron (ANN-MLP) is a multivariate statistical algorithm of machine learning widely used in the analysis of factors associated with changes in land use [44][45][46] . MLP algorithm used in the LCM is an adaptation specially designed for the land change analysis 34 .…”

Forests and Peace in alternative pathways: scenarios of land use and land cover change for the Colombian Amazon

“…The Artificial Neural Network Multi-Layer Perceptron (ANN-MLP) is a multivariate statistical algorithm of machine learning widely used in the analysis of factors associated with changes in land use [33][34][35][36] . ANN-MLP is a suitable classification method to solve non-linear relationships in complex data sets 37,38 such as those in this study.…”