A multi-method approach with machine learning to evaluating the distribution and intensity of prehistoric land use in Eastern Iberia

Keyphrases

• Machine Learning 100%
• Multi-method 100%
• Historical Land Use 100%
• Human Presence 100%
• Early Neolithic 100%
• Eastern Iberia 100%
• Ecosystem Management 50%
• Farmland 50%
• Human Population 50%
• Climate Events 50%
• High Temperature 50%
• Europe 50%
• Global Climate 50%
• Population Trends 50%
• Archaeological Survey 50%
• Land Use Strategies 50%
• Spatial Analysis 50%
• Radiocarbon Dating 50%
• Population Expansion 50%
• Surface Artifacts 50%
• Late Pleistocene 50%
• Social Systems 50%
• Boom-bust 50%
• Paleoenvironmental 50%
• Unmixing 50%
• Regional Climate 50%
• Systematic Evaluation 50%
• Biophysical Systems 50%
• Early Holocene 50%
• Late Holocene 50%
• Column Sampling 50%
• Human Land Use 50%
• Summed Probability Distribution 50%
• Climatic Regimes 50%
• Late Neolithic 50%
• Patch-based 50%
• Sediment Column 50%
• Middle Palaeolithic 50%
• Eastern Mediterranean 50%
• Upper Palaeolithic 50%
• Mediterranean Iberia 50%
• Continuous Distribution 50%
• Intensity Map 50%
• Pleistocene-Holocene 50%
• Summer Drought 50%
• Land Use Intensity 50%
• Farming Strategies 50%
• Neolithic Farming 50%
• Recursive Interactions 50%
• Late Neolithic-Chalcolithic 50%
• Middle Neolithic 50%
• Probability Density Curves 50%
• Charcoal Analysis 50%

Earth and Planetary Sciences

• Machine Learning 100%
• Prehistoric 100%
• Land Use 100%
• Regional Geography 75%
• Ecosystem Resource Management 25%
• Europe 25%
• Regional Climate 25%
• Late Pleistocene 25%
• Holocene 25%
• Early Holocene 25%
• Population Trend 25%
• Survey Method 25%
• Pleistocene-Holocene Boundary 25%
• Agriculture 25%