Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification from VHR Imagery
(2020)
Journal Article
Lv, Z., Li, G., Jin, Z., Benediktsson, J. A., & Foody, G. M. (2021). Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification from VHR Imagery. IEEE Transactions on Geoscience and Remote Sensing, 59(1), 139-150. https://doi.org/10.1109/TGRS.2020.2996064
© 1980-2012 IEEE. Imbalanced training sets are known to produce suboptimal maps for supervised classification. Therefore, one challenge in mapping land cover is acquiring training data that will allow classification with high overall accuracy (OA) in... Read More about Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification from VHR Imagery.