Mapping tree species in temperate deciduous woodland using time‐series multi‐spectral data

By Ross A. Hill, A. Wilson, M. George, Shelley A. Hinsley. 2010

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Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data (2012, background): “79 Fraxinus excelsior, Quercus robur, Acer campestre, Betula pendula, Populus tremula & Ulmus minor [89]”
Combining ensemble modeling and remote sensing for mapping individual tree species at high spatial resolution (2013, result): “Finally, multi-temporal data (e.g. Key et al., 2001; Hill et al., 2010) could also represent a possible option to improve model predictive accuracy as was found e.g. in Schwarz and Zimmermann (2005).”
Enhanced forest cover mapping using spectral unmixing and object-based classification of multi-temporal Landsat imagery (2017, background): “Previous broadband sensor-based studies have shown the utility of using multiple phenologically-important image dates and vegetation indices when classifying heterogeneous forest cover at the species-type level (e.g. Dymond et al., 2002; Hill et al., 2010).”