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On the use of the advanced very high resolution radiometer for development of prognostic land surface phenology models

Author

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  • Kathuroju, Naven
  • White, Michael A.
  • Symanzik, Jürgen
  • Schwartz, Mark D.
  • Powell, James A.
  • Nemani, Ramakrishna R.

Abstract

Regulation of interannual phenological variability is an important component of climate and ecological models. Prior phenological efforts using the advanced very high resolution radiometer (AVHRR) as a proxy of vegetation dynamics have often simulated spring events only or failed to simulate interannual variability. Our aim is to address these shortcomings and to use the AVHRR to develop prognostic models for interannual land surface phenology and, critically, to test whether or not the developed models are superior to use of climatological phenology values from the AVHRR. Using datasets for the conterminous United States, we first filtered data to select regions and plant functional types for which the best-possible remotely sensed signal could be obtained. We then used a generalized linear model approach to model the relationship between an integrative productivity index and estimates of the start of season (SOS) and end of season (EOS) derived from the AVHRR, yielding models capable of prognostically predicting SOS/EOS events independently of satellite data. Mean absolute errors between the model-predicted and AVHRR-observed SOS/EOS ranged from 5.1 to 20.3 days. SOS errors were uniformly lower than EOS errors. SOS models for the deciduous broadleaf forest and grassland plant functional types produced lower errors than use of the climatological SOS values while all other models produced errors higher than those obtained from the climatological dates. Based on this criterion for success, we suggest that the AVHRR may not be appropriate for further development of prognostic land surface phenology models. However, an intercomparison of phenological dates from an independent spring index model, our model predictions, and the AVHRR observations indicated that interannual predictions from our models may be superior to the satellite data upon which they are based, implying that a further comparison between models based on the AVHRR and newer, superior sensors, should be conducted.

Suggested Citation

  • Kathuroju, Naven & White, Michael A. & Symanzik, Jürgen & Schwartz, Mark D. & Powell, James A. & Nemani, Ramakrishna R., 2007. "On the use of the advanced very high resolution radiometer for development of prognostic land surface phenology models," Ecological Modelling, Elsevier, vol. 201(2), pages 144-156.
    • Handle: RePEc:eee:ecomod:v:201:y:2007:i:2:p:144-156
    DOI: 10.1016/j.ecolmodel.2006.09.011
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    References listed on IDEAS

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    1. R. B. Myneni & C. D. Keeling & C. J. Tucker & G. Asrar & R. R. Nemani, 1997. "Increased plant growth in the northern high latitudes from 1981 to 1991," Nature, Nature, vol. 386(6626), pages 698-702, April.
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    1. Verma, Manish & Friedl, Mark A. & Finzi, Adrien & Phillips, Nathan, 2016. "Multi-criteria evaluation of the suitability of growth functions for modeling remotely sensed phenology," Ecological Modelling, Elsevier, vol. 323(C), pages 123-132.

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