Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006

M.A. White, K.M. de Beurs, K. Didan, D.W. Inouye, A.D. Richardson, O.P. Jensen, J. Magnuson, J. O'Keefe, G. Zhang, R.R. Nemani, W.J.D. van Leeuwen, J.F. Brown, A.J.W. de Wit, M.E. Schaepman, X. Lin, M. Dettinger, A. Bailey, J. Kimball, M.D. Schwartz, D.D. Baldocchi & 2 others J.T. Lee, W.K. Lauenroth

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.
Original languageEnglish
Pages (from-to)2335-2359
JournalGlobal Change Biology
Volume15
Issue number10
DOIs
Publication statusPublished - 2009

Fingerprint

phenology
Remote sensing
Satellites
remote sensing
Springs (water)
Advanced very high resolution radiometers (AVHRR)
Ice
Snow
Lakes
Time series
Soils
Monitoring
Temperature
North America
method
ice lake
ecoregion
AVHRR
snow cover
global change

Keywords

  • satellite sensor data
  • ndvi time-series
  • climate-change
  • united-states
  • deciduous forest
  • fourier-analysis
  • plant phenology
  • carbon-dioxide
  • trends
  • variability

Cite this

White, M. A., de Beurs, K. M., Didan, K., Inouye, D. W., Richardson, A. D., Jensen, O. P., ... Lauenroth, W. K. (2009). Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006. Global Change Biology, 15(10), 2335-2359. https://doi.org/10.1111/j.1365-2486.2009.01910.x
White, M.A. ; de Beurs, K.M. ; Didan, K. ; Inouye, D.W. ; Richardson, A.D. ; Jensen, O.P. ; Magnuson, J. ; O'Keefe, J. ; Zhang, G. ; Nemani, R.R. ; van Leeuwen, W.J.D. ; Brown, J.F. ; de Wit, A.J.W. ; Schaepman, M.E. ; Lin, X. ; Dettinger, M. ; Bailey, A. ; Kimball, J. ; Schwartz, M.D. ; Baldocchi, D.D. ; Lee, J.T. ; Lauenroth, W.K. / Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006. In: Global Change Biology. 2009 ; Vol. 15, No. 10. pp. 2335-2359.
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title = "Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006",
abstract = "Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12{\%} of North America and were divided between trends towards both earlier and later spring.",
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White, MA, de Beurs, KM, Didan, K, Inouye, DW, Richardson, AD, Jensen, OP, Magnuson, J, O'Keefe, J, Zhang, G, Nemani, RR, van Leeuwen, WJD, Brown, JF, de Wit, AJW, Schaepman, ME, Lin, X, Dettinger, M, Bailey, A, Kimball, J, Schwartz, MD, Baldocchi, DD, Lee, JT & Lauenroth, WK 2009, 'Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006', Global Change Biology, vol. 15, no. 10, pp. 2335-2359. https://doi.org/10.1111/j.1365-2486.2009.01910.x

Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006. / White, M.A.; de Beurs, K.M.; Didan, K.; Inouye, D.W.; Richardson, A.D.; Jensen, O.P.; Magnuson, J.; O'Keefe, J.; Zhang, G.; Nemani, R.R.; van Leeuwen, W.J.D.; Brown, J.F.; de Wit, A.J.W.; Schaepman, M.E.; Lin, X.; Dettinger, M.; Bailey, A.; Kimball, J.; Schwartz, M.D.; Baldocchi, D.D.; Lee, J.T.; Lauenroth, W.K.

In: Global Change Biology, Vol. 15, No. 10, 2009, p. 2335-2359.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006

AU - White, M.A.

AU - de Beurs, K.M.

AU - Didan, K.

AU - Inouye, D.W.

AU - Richardson, A.D.

AU - Jensen, O.P.

AU - Magnuson, J.

AU - O'Keefe, J.

AU - Zhang, G.

AU - Nemani, R.R.

AU - van Leeuwen, W.J.D.

AU - Brown, J.F.

AU - de Wit, A.J.W.

AU - Schaepman, M.E.

AU - Lin, X.

AU - Dettinger, M.

AU - Bailey, A.

AU - Kimball, J.

AU - Schwartz, M.D.

AU - Baldocchi, D.D.

AU - Lee, J.T.

AU - Lauenroth, W.K.

N1 - Online first

PY - 2009

Y1 - 2009

N2 - Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.

AB - Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.

KW - satellite sensor data

KW - ndvi time-series

KW - climate-change

KW - united-states

KW - deciduous forest

KW - fourier-analysis

KW - plant phenology

KW - carbon-dioxide

KW - trends

KW - variability

U2 - 10.1111/j.1365-2486.2009.01910.x

DO - 10.1111/j.1365-2486.2009.01910.x

M3 - Article

VL - 15

SP - 2335

EP - 2359

JO - Global Change Biology

JF - Global Change Biology

SN - 1354-1013

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ER -