Species–specific contributions to moderate resolution vegetation indices derived from sub-decimeter aerial photography – Prospects for phenological monitoring

TitleSpecies–specific contributions to moderate resolution vegetation indices derived from sub-decimeter aerial photography – Prospects for phenological monitoring
Publication TypeConference Paper
Year of Publication2010
AuthorsBrowning D.M., Laliberte, Andrea S., Rango A.
Conference NameAmerican Society for Photogrammetry and Remote sensing Proceedings
Date Published04/2010
Conference LocationSan Diego, California
Accession NumberJRN50017
ARIS Log Number247216
Abstract

High spatial heterogeneity in ground cover, large amounts of exposed bare soil, and modest cover from shrubs and grasses in arid and semi-arid ecosystems challenge the integration of field observations of phenology and remotely sensed data to monitor changes in land surface phenology. This research conducted at the Jornada Basin Long-Term Ecological Research (LTER) site in southern New Mexico capitalizes on object-based classification of sub-decimeter (4 cm) aerial photography to examine species-specific contributions to vegetation index values calculated across a range of grain sizes. Drawing on established field protocols for reproductive phenology, sub-decimeter imagery (4 cm), and object-based image analysis, we explore the relationship between field phenology and vegetation index values and quantify the contribution of individual species to spectral vegetation index values derived from 4 cm imagery aggregated incrementally to 30 m spatial resolution. Color-infrared imagery from a digital mapping camera was collected June 2007 across 15 LTER study sites that transect five distinct vegetation communities along a continuum of grass to shrub dominance. Object-based image analysis of 4 cm imagery provides a detailed depiction of ground cover and allows us to extract species-specific contributions to spectral vegetation indices. The ability to discern species- or functional-group contributions to remotely sensed signals of vegetation greenness can greatly enhance the design of field sampling protocols for phenological research. Furthermore, imagery from unmanned aerial vehicles (UAV) is a cost-effective and increasingly available resource and generation of UAV mosaics has been accomplished so that larger study areas can be addressed. This technology can provide a robust basis for scaling relationships for phenology-based research applications.