File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Exploring the use of DSCOVR/EPIC satellite observations to monitor vegetation phenology

TitleExploring the use of DSCOVR/EPIC satellite observations to monitor vegetation phenology
Authors
KeywordsDSCOVR
EPIC
Land surface phenology
PhenoCam
Remote sensing
Vegetation phenology
Issue Date2020
Citation
Remote Sensing, 2020, v. 12, n. 15, article no. 2384 How to Cite?
AbstractVegetation phenology plays a pivotal role in regulating several ecological processes and has profound impacts on global carbon exchange. Large-scale vegetation phenology monitoring mostly relies on Low-Earth-Orbit satellite observations with low temporal resolutions, leaving gaps in data that are important for monitoring seasonal vegetation phenology. High temporal resolution satellite observations have the potential to fill this gap by frequently collecting observations on a global scale, making it easier to study change over time. This study explored the potential of using the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite, which captures images of the entire sunlit face of the Earth at a temporal resolution of once every 1-2 h, to observe vegetation phenology cycles in North America. We assessed the strengths and shortcomings of EPIC-based phenology information in comparison with the Moderate-resolution Imaging Spectroradiometer (MODIS), Enhanced Thematic Mapper (ETM+) onboard Landsat 7, and PhenoCam ground-based observations across six different plant functional types. Our results indicated that EPIC could capture and characterize seasonal changes of vegetation across different plant functional types and is particularly consistent in the estimated growing season length. Our results also provided new insights into the complementary features and benefits of the four datasets, which is valuable for improving our understanding of the complex response of vegetation to global climate variability and other disturbances and the impact of phenology changes on ecosystem productivity and global carbon exchange.
Persistent Identifierhttp://hdl.handle.net/10722/329641
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWeber, Maridee-
dc.contributor.authorHao, Dalei-
dc.contributor.authorAsrar, Ghassem R.-
dc.contributor.authorZhou, Yuyu-
dc.contributor.authorLi, Xuecao-
dc.contributor.authorChen, Min-
dc.date.accessioned2023-08-09T03:34:16Z-
dc.date.available2023-08-09T03:34:16Z-
dc.date.issued2020-
dc.identifier.citationRemote Sensing, 2020, v. 12, n. 15, article no. 2384-
dc.identifier.urihttp://hdl.handle.net/10722/329641-
dc.description.abstractVegetation phenology plays a pivotal role in regulating several ecological processes and has profound impacts on global carbon exchange. Large-scale vegetation phenology monitoring mostly relies on Low-Earth-Orbit satellite observations with low temporal resolutions, leaving gaps in data that are important for monitoring seasonal vegetation phenology. High temporal resolution satellite observations have the potential to fill this gap by frequently collecting observations on a global scale, making it easier to study change over time. This study explored the potential of using the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite, which captures images of the entire sunlit face of the Earth at a temporal resolution of once every 1-2 h, to observe vegetation phenology cycles in North America. We assessed the strengths and shortcomings of EPIC-based phenology information in comparison with the Moderate-resolution Imaging Spectroradiometer (MODIS), Enhanced Thematic Mapper (ETM+) onboard Landsat 7, and PhenoCam ground-based observations across six different plant functional types. Our results indicated that EPIC could capture and characterize seasonal changes of vegetation across different plant functional types and is particularly consistent in the estimated growing season length. Our results also provided new insights into the complementary features and benefits of the four datasets, which is valuable for improving our understanding of the complex response of vegetation to global climate variability and other disturbances and the impact of phenology changes on ecosystem productivity and global carbon exchange.-
dc.languageeng-
dc.relation.ispartofRemote Sensing-
dc.subjectDSCOVR-
dc.subjectEPIC-
dc.subjectLand surface phenology-
dc.subjectPhenoCam-
dc.subjectRemote sensing-
dc.subjectVegetation phenology-
dc.titleExploring the use of DSCOVR/EPIC satellite observations to monitor vegetation phenology-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.3390/RS12152384-
dc.identifier.scopuseid_2-s2.0-85089689555-
dc.identifier.volume12-
dc.identifier.issue15-
dc.identifier.spagearticle no. 2384-
dc.identifier.epagearticle no. 2384-
dc.identifier.eissn2072-4292-
dc.identifier.isiWOS:000559119900001-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats