Mapping plant growth forms using structure-from-motion data combined with spectral image derivatives

Mapping plant growth forms is useful to classify and monitor chaparral shrubland community types in southern California. This study evaluates the utility of plant height information, derived from high spatial resolution aerial images and structure-from-motion photogrammetry, for the purpose of distinguishing tree, shrub and sub-shrub growth forms from herbs and bare ground. Canopy height models (CHMs) were derived for two chaparral sites on Santa Rosa Plateau which contain intermixed growth forms. A multi-criterion, knowledge-based thresholding approach was used to classify growth forms based on spectral data (Normalized Difference Vegetation Index, hue, intensity, and focal texture) alone, CHM data alone, and hybrid combinations of spectral and CHM data. Overall accuracies were 66.0-69.0% from spectral data, 72.0-75.5% from CHM data, and 80.5-82.5% from the hybrid data sets. This study highlights the utility in combining multi-spectral and canopy height data for characterizing Mediterranean-type plant communities and changes therein.