A landscape metrics-based sample weighting approach for forecasting land cover change with deep learning models
Author:
Affiliation:
1. Spatial Analysis and Modeling Laboratory, Department of Geography, Simon Fraser University, Burnaby, BC, Canada
Funder
Natural Sciences and Engineering Research Council (NSERC) of Canada
Publisher
Informa UK Limited
Subject
Water Science and Technology,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/10106049.2023.2240283
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1. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) after fifteen years: Review of global products
2. Spatial Validation of Land Use Change Models Using Multiple Assessment Techniques: A Case Study of Transition Potential Models
3. A new framework to deal with the class imbalance problem in urban gain modeling based on clustering and ensemble models
4. Evaluation of Model Validation Techniques in Land Cover Dynamics
5. Introducing landscape accuracy metric for spatial performance evaluation of land use/land cover change models
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