Phenocams bridge the gap between field and satellite observations: Applications from agroecosystems

TitlePhenocams bridge the gap between field and satellite observations: Applications from agroecosystems
Publication TypeConference Paper
Year of Publication2018
AuthorsBrowning DM, Campos GPonce, Scott RL, Peters DC
Conference NameUS-International Association for Landscape Ecology
Date Published04/2018
Conference LocationChicago, Illinois
ARIS Log Number357902
Abstract

Agro-ecosystems represent a gap in national research networks established to address ecological questions that site-level research cannot address. The Long-Term Agroecosystem Research (LTAR) network established by the U.S.D.A. Agriculture Research Service is intended to fill this gap. In this study, we combine data from two LTAR network sites in the arid southwestern U.S. spanning 18 site-years to evaluate relationships between greenness index values derived from near-surface phenocams (GCC) and MODIS satellite imagery (NDVI) with measures of ecosystem productivity. Two core data sets for sites in the LTAR network are aboveground net primary production (ANPP) estimated in the field and gross primary production (GPP) modeled from eddy covariance flux towers. We explore relationships between remotely-derived greenness using camera GCC and MODIS NDVI indices and ANPP and GPP from 2013 to 2016. We used ANPP at three camera sites on the Jornada Experimental Range (JER) in southern New Mexico and GPP at two camera sites at the Walnut Gulch Experimental Watershed (WGEW) in southern Arizona. We calculated pairwise Pearson correlations between growing season integrals of GPP derived from CO2 flux measurements and remotely-sensed indicators (camera GCC and NDVI) at the two WGEW sites. At JER, we calculated correlations between ANPP and growing season integrals of GCC and NDVI. Our analysis showcases methods for comparing ANPP computed annually and GPP estimated daily with time series GCC and NDVI. As LTAR site locations accumulate phenocam imagery, analyses will be expanded across the network to quantitatively evaluate the role of growing season dynamics and climate on primary productivity in agro-ecosystems.