Enhanced forest cover mapping using spectral unmixing and object-based classification of multi-temporal Landsat imagery

These results show that more detailed and accurate forest mapping is possible using a combination of multi-temporal imagery, spectral unmixing, and rule-based classification techniques. Improved large-scale forest mapping has important implications for natural resource management and other modeling applications.