Mapping hydropower expansion and cash crop dynamics in Colombia using Landsat time series

Abstract

AbstractSatellite-based monitoring provides insights on synergies and trade-offs between energy production and land use and land cover (LULC) changes (LULCC) around hydropower dams. Using Landsat data, we mapped LULCC related to hydropower expansion to understand change dynamics of cash crop production in the Magdalena River basin (Colombian Andes). We leveraged secondary map products and an active learning routine to produce thematically detailed LULC maps, for 2009, 2015, and 2020, including key cash crops (rice and oil palm). Our area-adjusted accuracy assessment revealed high overall and class-specific user’s and producer’s accuracies, exceeding 80% for oil palm, rice, non-agricultural vegetation, wetlands, and grasslands, and accuracies of ∼60% for other temporary and permanent crops. We identified substantial losses of rice (10,6%) and grasslands (25,9%) in El Quimbo due to reservoir flooding. For Hidrosogamoso, there was a loss of wetlands downstream. Our products provide the basis for balancing social, economic, and environmental trade-offs related to conflicting land uses.

Keywords

• active learning
• Colombian Andes
• Google Earth Engine
• hydropower dams
• land use and land cover (LULC)
• water-energy-food nexus