Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem
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 en...
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doaj-66e571fcf1254a9a9e0fabaa9d14a6aa2020-11-25T00:36:42ZengMDPI AGRemote Sensing2072-42922017-10-01910107110.3390/rs9101071rs9101071Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland EcosystemDawn M. Browning0Jason W. Karl1David Morin2Andrew D. Richardson3Craig E. Tweedie4Jornada Experimental Range, USDA-ARS, P.O. Box 30003, MSC 3JER, Las Cruces, NM 88003, USADepartment Forest, Rangeland, and Fire Sciences, University of Idaho, Moscow, ID 83844, USAJornada Experimental Range, New Mexico State University, P.O. Box 30003, MSC 3JER, Las Cruces, NM 880033, USASchool of Informatics, Computing, and Cyber Systems and Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ 86011, USADepartment Biological Science, The University of Texas at El Paso, El Paso, TX 79968, USANear 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.https://www.mdpi.com/2072-4292/9/10/1071phenologyphenocamdrylandsinstrument intercomparisonecological scalingecosystem productivityUSA-NPN protocolsgrowing seasonunfolded leavesrangeland |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dawn M. Browning Jason W. Karl David Morin Andrew D. Richardson Craig E. Tweedie |
spellingShingle |
Dawn M. Browning Jason W. Karl David Morin Andrew D. Richardson Craig E. Tweedie Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem Remote Sensing phenology phenocam drylands instrument intercomparison ecological scaling ecosystem productivity USA-NPN protocols growing season unfolded leaves rangeland |
author_facet |
Dawn M. Browning Jason W. Karl David Morin Andrew D. Richardson Craig E. Tweedie |
author_sort |
Dawn M. Browning |
title |
Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem |
title_short |
Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem |
title_full |
Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem |
title_fullStr |
Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem |
title_full_unstemmed |
Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem |
title_sort |
phenocams bridge the gap between field and satellite observations in an arid grassland ecosystem |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2017-10-01 |
description |
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. |
topic |
phenology phenocam drylands instrument intercomparison ecological scaling ecosystem productivity USA-NPN protocols growing season unfolded leaves rangeland |
url |
https://www.mdpi.com/2072-4292/9/10/1071 |
work_keys_str_mv |
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