A high-reliability, high-resolution method for land cover classification into forest and non-forest

Authors:
Roger Trias-Sanz;Didier Boldo
Affiliations:
Institut Géographique National, Saint-Mandé, France;Institut Géographique National, Saint-Mandé, France
Venue:
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Year:
2005

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Abstract

We present several methods for per-region land-cover classification based on distances on probability distributions and whole-region probabilities. We present results on using this method for locating forest areas in high-resolution aerial images with very high reliability, achieving more than 95% accuracy, using raw radiometric channels as well as derived color and texture features. Region boundaries are obtained from a multi-scale hierarchical segmentation or from a registration of cadastral maps.