An optimal method for validating satellite-derived land surface phenology using in-situ observations from national phenology networks

Yongchang Ye, Xiaoyang Zhang, Yu Shen, Jianmin Wang, Theresa Crimmins, Helfried Scheifinger

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Satellite-based land surface phenology (LSP) products play an important role in understanding atmosphere-vegetation carbon and energy exchanges. These products have been widely calculated from various satellite observations from local to global scales. However, the quality and accuracy of LSP products are often poorly quantified due to spatial mismatch between satellite observed pixels and in-situ observations. In the present study, we demonstrate an optimal algorithm leveraging the scalability, consistency, and representativeness of rich in-situ observations from national phenology networks to validate LSP products. Specifically, we demonstrate two approaches for validating the phenological timing of greenup onset in the operational Visible Infrared Imaging Radiometer Suite (VIIRS) LSP product developed at NASA using in-situ observations collected from the Pan European Phenological database (PEP725, 9664 site-years) and the USA National Phenology Network (USA-NPN, 3144 site-years) spanning 2013–2020. The first approach assumes that in-situ data contain observations of phenological transitions (e.g., leaf-out) that are directly comparable with satellite detections. Accordingly, in-situ data were aggregated using four upscaling methods (mean, median, 30th percentile, and minimum bias) to directly compare with VIIRS LSP. The second approach assumes that species-specific phenological timing in in-situ data is basically impossible to spatially reconcile VIIRS LSP, but phenological events in a local area are driven by the same or very similar weather conditions. Therefore, interannual variations and long-term trends were applied to compare VIIRS LSP with in-situ data. The result shows first that the 30th percentile method is more promising in aggregating in-situ observations than the commonly used mean method. Second, direct comparison indicates that VIIRS greenup onset has a mean absolute difference of 13.9 ± 9.8 days with PEP725 in-situ observations and 12.3 ± 10.9 days with USA-NPN observations in well-selected deciduous forest sites. Third, the interannual comparison reveals that VIIRS greenup onset exhibits the same directions of multi-year anomalies and long-term trends as those of both PEP725 and USA-NPN observations in over 70% of sample sites. These findings improve our understanding of the scale mismatch and sample representativeness of species-specific phenology and the uncertainties of long-term LSP detections from remote sensing data.

Original languageEnglish (US)
Pages (from-to)74-90
Number of pages17
JournalISPRS Journal of Photogrammetry and Remote Sensing
Volume194
DOIs
StatePublished - Dec 2022

Keywords

  • In-situ observations
  • LSP validation
  • PEP725
  • Phenology
  • USA-NPN
  • VIIRS

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Computer Science Applications
  • Computers in Earth Sciences

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