Location: Range Management ResearchTitle: Phenocams bridge the gap between field and satellite observations in an arid grassland ecosystem
|MORAN, DAVID - New Mexico State University|
|RICHARDSON, ANDREW - Harvard University|
|TWEEDIE, CRAIG - University Of Texas - El Paso|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/18/2017
Publication Date: 10/21/2017
Publication URL: http://handle.nal.usda.gov/10113/5883115
Citation: Browning, D.M., Karl, J.W., Moran, D., Richardson, A.D., Tweedie, C.E. 2017. Phenocams bridge the gap between field and satellite observations in an arid grassland ecosystem. Remote Sensing of Environment. 9(10):1071. https://doi.org/10.3390/rs9101071.
Interpretive Summary: Land managers, researchers, and private land owners seek ways to monitor landscape condition and greenness. Information about landscape greenness often comes from imagery acquired by satellite or aircraft. But there is a gap between the imagery acquired and data needed to make land management decisions. We evaluated the utility and limitations of inexpensive (~$1,000) digital cameras mounted on towers at heights of 2- to 6-m for capturing the timing of canopy greenness patterns for black grama grass, honey mesquite shrub, and the landscape containing a mix of these species. We examined measurements of vegetation greenness (Normalized Difference Vegetation Index; NDVI and Green Chromatic Coordinate; GCC) obtained from satellite imagery and digital cameras with weekly data collected on honey mesquite and black grama plants to identify plant growth stages (phenology). Our data showed that the cameras were well correlated with weekly field measurements. In addition, cameras captured honey mesquite phenology very well, but were less effective for capturing black grama initial growth. The ability to monitor vegetation greenness with cameras fills a data gap and provides information for tracking wildlife habitat and forage production as well as natural resource monitoring programs at a fraction of the cost of collecting field data. These capabilities can benefit state and federal land managers, private land owners, and ecologists.
Technical Abstract: Near surface (i.e., camera) and satellite remote sensing metrics have become widely used indicators of plant growing seasons. While robust linkages have been established between field metrics and ecosystem exchange in many land cover types, assessment of how well remotely-derived season start and end dates depict field conditions in arid ecosystems remain unknown. We evaluated the correspondence between field measures of start (SOS; leaves unfolded and canopy greenness > 0) and end of season (EOS) and canopy greenness for two widespread species in southwestern U.S. ecosystems with those metrics estimated from near-surface cameras and MODIS NDVI for five years (2012-2016). Using the Timesat software to estimate SOS and EOS from the phenocam green chromatic coordinate (GCC) greenness index resulted in good agreement with ground observations for honey mesquite but not black grama. Despite differences in the detectability of SOS and EOS for the two species, GCC was significantly correlated with field estimates of canopy greenness for both species throughout the growing season. MODIS NDVI for this arid grassland site was driven by the black grama signal although a mesquite signal is discernable in average rainfall years. Our findings suggest phenocams could help meet myriad needs in natural resource management.