Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem
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 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 was discernable in average rainfall years. Our findings suggest phenocams could help meet myriad needs in natural resource management.
- Authors:
-
- US Dept. of Agriculture (USDA)., Las Cruces, NM (United States). Jornada Experimental Range
- Univ. of Idaho, Moscow, ID (United States). Dept. of Forest, Rangeland, and Fire Sciences
- New Mexico State Univ., Las Cruces, NM (United States). Jornada Experimental Range
- Northern Arizona Univ., Flagstaff, AZ (United States). School of Informatics, Computing, and Cyber Systems and Center for Ecosystem Science and Society
- Univ. of Texas, El Paso, TX (United States). Dept. of Biological Science
- Publication Date:
- Research Org.:
- Princeton Univ., NJ (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1499902
- Grant/Contract Number:
- SC0016011
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Remote Sensing
- Additional Journal Information:
- Journal Volume: 9; Journal Issue: 10; Journal ID: ISSN 2072-4292
- Publisher:
- MDPI
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 47 OTHER INSTRUMENTATION; phenology; phenocam; drylands; instrument intercomparison; ecological scaling; ecosystem productivity; USA-NPN protocols; growing season; unfolded leaves; rangeland
Citation Formats
Browning, Dawn, Karl, Jason, Morin, David, Richardson, Andrew, and Tweedie, Craig. Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem. United States: N. p., 2017.
Web. doi:10.3390/rs9101071.
Browning, Dawn, Karl, Jason, Morin, David, Richardson, Andrew, & Tweedie, Craig. Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem. United States. https://doi.org/10.3390/rs9101071
Browning, Dawn, Karl, Jason, Morin, David, Richardson, Andrew, and Tweedie, Craig. Sat .
"Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem". United States. https://doi.org/10.3390/rs9101071. https://www.osti.gov/servlets/purl/1499902.
@article{osti_1499902,
title = {Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem},
author = {Browning, Dawn and Karl, Jason and Morin, David and Richardson, Andrew and Tweedie, Craig},
abstractNote = {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 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 was discernable in average rainfall years. Our findings suggest phenocams could help meet myriad needs in natural resource management.},
doi = {10.3390/rs9101071},
journal = {Remote Sensing},
number = 10,
volume = 9,
place = {United States},
year = {Sat Oct 21 00:00:00 EDT 2017},
month = {Sat Oct 21 00:00:00 EDT 2017}
}
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