TY - JOUR
T1 - PS3
T2 - The Pheno-Synthesis software suite for integration and analysis of multi-scale, multi-platform phenological data
AU - Morisette, Jeffrey T.
AU - Duffy, Katharyn A.
AU - Weltzin, Jake F.
AU - Browning, Dawn M.
AU - Marsh, R. Lee
AU - Friesz, Aaron M.
AU - Zachmann, Luke J.
AU - Enns, Kyle D.
AU - Landau, Vincent A.
AU - Gerst, Katharine L.
AU - Crimmins, Theresa M.
AU - Jones, Katherine D.
AU - Chang, Tony
AU - Miller, Brian W.
AU - Maiersperger, Thomas K.
AU - Richardson, Andrew D.
N1 - Funding Information:
The authors acknowledge funding for this work through NASA's AIST program ( 80NSSC17K0582 , 80NSSC17K0435 , 80NSSC17K0538 , and 80GSFC18T0003 ). The University of Arizona and the USA National Phenology Network was supported in part by US Geological Survey ( G14AC00405 , G18AC00135 ) and the US Fish and Wildlife Service ( F16AC01075 and F19AC00168 ). The development of PhenoCam was supported by the Northeastern States Research Cooperative , the NSF Macrosystems Biology program ( EF-1065029 and EF-1702697 ), the Department of Energy Regional and Global Climate Modeling program ( DE-SC0016011 ), the US National Park Service Inventory and Monitoring Program and the US Geological Survey ( G10AP00129 , G16AC00224 ). The development of dacqre and Greenwave tools was supported in part by the Southwest Climate Adaptation Science Center ( G17AC00247 ) and the Denver Zoological Foundation . This research was also supported in part by the North Central Climate Adaptation Science Center . NASA program managers Laura Rogers, Mike Frame, Woody Turner, and Jacqueline Le Moigne provided suggestions for the overall software design that improved the ultimate outcomes of the project. Thanks to Wavy, Mud, and KJ at the SWP in Tucson, AZ. Peter Ma and Sudipta Sarkar from the MODIS Land Data Operational Products Evaluation facility provided helpful guidance on the quality filtering. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The findings and conclusions in this article are those of the authors; they do not necessarily represent the views of the USDA and should not be construed to represent USDA agency determination or policy. The views and conclusions in this article do represent the views of the U.S. Geological Survey.
Funding Information:
The authors acknowledge funding for this work through NASA's AIST program (80NSSC17K0582, 80NSSC17K0435, 80NSSC17K0538, and 80GSFC18T0003). The University of Arizona and the USA National Phenology Network was supported in part by US Geological Survey (G14AC00405, G18AC00135) and the US Fish and Wildlife Service (F16AC01075 and F19AC00168). The development of PhenoCam was supported by the Northeastern States Research Cooperative, the NSF Macrosystems Biology program (EF-1065029 and EF-1702697), the Department of Energy Regional and Global Climate Modeling program (DE-SC0016011), the US National Park Service Inventory and Monitoring Program and the US Geological Survey (G10AP00129, G16AC00224). The development of dacqre and Greenwave tools was supported in part by the Southwest Climate Adaptation Science Center (G17AC00247) and the Denver Zoological Foundation. This research was also supported in part by the North Central Climate Adaptation Science Center. NASA program managers Laura Rogers, Mike Frame, Woody Turner, and Jacqueline Le Moigne provided suggestions for the overall software design that improved the ultimate outcomes of the project. Thanks to Wavy, Mud, and KJ at the SWP in Tucson, AZ. Peter Ma and Sudipta Sarkar from the MODIS Land Data Operational Products Evaluation facility provided helpful guidance on the quality filtering. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The findings and conclusions in this article are those of the authors; they do not necessarily represent the views of the USDA and should not be construed to represent USDA agency determination or policy. The views and conclusions in this article do represent the views of the U.S. Geological Survey. JTM would like to thank the entire PS3 team. The project spanned over three years, involving a considerable amount of collaboration. JFW, DMB, ADR made major contribution to the analysis, interpretation, and implications of the case study and PS3 in general. KAD was the lead ?wrangler? of code for the case study. Code leaders included LRM for rNPN, KJ for interface with NEON, KAD and KDE for phenoSynth, AMF for interfacing with AppEEARS, TC for dacqre; LJZ for Greenwave with VAL supporting coding and conception of the mathematical model. Project management included close coordination among key programs: TKM for overall project management, TMC and KLG with USA-NPN, ADR with the PhenoCam Network, and TKM, BWM, and JFW with USGS.
Publisher Copyright:
© 2021
PY - 2021/11
Y1 - 2021/11
N2 - Phenology is the study of recurring plant and animal life-cycle stages which can be observed across spatial and temporal scales that span orders of magnitude (e.g., organisms to landscapes). The variety of scales at which phenological processes operate is reflected in the range of methods for collecting phenologically relevant data, and the programs focused on these collections. Consideration of the scale at which phenological observations are made, and the platform used for observation, is critical for the interpretation of phenological data and the application of these data to both research questions and land management objectives. However, there is currently little capacity to facilitate access, integration and analysis of cross-scale, multi-platform phenological data. This paper reports on a new suite of software and analysis tools – the “Pheno-Synthesis Software Suite,” or PS3 – to facilitate integration and analysis of phenological and ancillary data, enabling investigation and interpretation of phenological processes at scales ranging from organisms to landscapes and from days to decades. We use PS3 to investigate phenological processes in a semi-aride, mixed shrub-grass ecosystem, and find that the apparent importance of seasonal precipitation to vegetation activity (i.e., “greenness”) is affected by the scale and platform of observation. We end by describing potential applications of PS3 to phenological modeling and forecasting, understanding patterns and drivers of phenological activity in real-world ecosystems, and supporting agricultural and natural resource management and decision-making.
AB - Phenology is the study of recurring plant and animal life-cycle stages which can be observed across spatial and temporal scales that span orders of magnitude (e.g., organisms to landscapes). The variety of scales at which phenological processes operate is reflected in the range of methods for collecting phenologically relevant data, and the programs focused on these collections. Consideration of the scale at which phenological observations are made, and the platform used for observation, is critical for the interpretation of phenological data and the application of these data to both research questions and land management objectives. However, there is currently little capacity to facilitate access, integration and analysis of cross-scale, multi-platform phenological data. This paper reports on a new suite of software and analysis tools – the “Pheno-Synthesis Software Suite,” or PS3 – to facilitate integration and analysis of phenological and ancillary data, enabling investigation and interpretation of phenological processes at scales ranging from organisms to landscapes and from days to decades. We use PS3 to investigate phenological processes in a semi-aride, mixed shrub-grass ecosystem, and find that the apparent importance of seasonal precipitation to vegetation activity (i.e., “greenness”) is affected by the scale and platform of observation. We end by describing potential applications of PS3 to phenological modeling and forecasting, understanding patterns and drivers of phenological activity in real-world ecosystems, and supporting agricultural and natural resource management and decision-making.
KW - Hierarchical modeling
KW - Landsat
KW - MODIS
KW - National Ecological Observatory Network
KW - PhenoCam
KW - Phenology
KW - Remote sensing
KW - USA National Phenology Network
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UR - http://www.scopus.com/inward/citedby.url?scp=85114096491&partnerID=8YFLogxK
U2 - 10.1016/j.ecoinf.2021.101400
DO - 10.1016/j.ecoinf.2021.101400
M3 - Article
AN - SCOPUS:85114096491
SN - 1574-9541
VL - 65
JO - Ecological Informatics
JF - Ecological Informatics
M1 - 101400
ER -