Validating the use of metre-scale multi-spectral satellite image data for identifying tropical forest tree species

ABSTRACT Identifying and mapping tropical trees at the species level from space can support an improved assessment of forest composition, forest carbon uptake, tree species distribution and preferred habitat as well as a better understanding of the response of forests to climate change. In this study, the development of a validated data and image-processing schema demonstrated the capability of current metre-scale satellite technology (WorldView-3) to identify specific tree species within an unmanaged tropical forest. The experimental site, La Selva Biological Station in Costa Rica, provided access for field validation and spectral data acquisition of individual tree canopies from established canopy towers. It is also a representative biome of diverse lowland Atlantic tropical forests in Central America. The process defined in this paper calibrated and corrected field-acquired ASD field spectra for ten tree species and corrected WorldView-3 image data for viewing and illumination geometry. In addition, assessments of three current atmospheric compensation methods for correcting recent WorldView-3 satellite imagery established the most accurate compensation process for a tropical forest setting. Corrected reflectance in the satellite data matched the spectrometer data to ±0.25% for visible bands and ±0.5% for near-infrared bands. This study shows that spectral data from the satellite and field spectrometer data are nearly equivalent when applying the appropriate atmospheric compensation, band response emulation, and viewing correction processes established in this study.

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