Comparison of Grassland Phenology Derived from MODIS Satellite and PhenoCam Near-Surface Remote Sensing in North America. Issue 5 (3rd September 2019)

• Record Type: Journal Article
• Authors: Cui, Tengfei; Martz, Lawrence; Lamb, Eric G.; Zhao, Liang; Guo, Xulin
• Is Part Of: Canadian journal of remote sensing. Volume 45:Issue 5(2019)
• Page Start: 707
• Page End: 722
• Publication Date: 2019-09-03
• Subjects: Remote sensing -- Periodicals; 621.367805
• DOI: 10.1080/07038992.2019.1674643
• Languages: English
• ISSNs: 0703-8992

Abstract

Abstract: Ground validation of satellite-based vegetation phenology has been challenging because ground phenology data are sparsely distributed and mostly observed from limited numbers of plant species at discrete phenophases. The recently developed PhenoCam network has measured continuous growth of vegetation canopy greenness that can be used to validate satellite-based vegetation phenology across a variety of plant functional types. In this study, we used PhenoCam green chromatic coordinate (GCC) in North America to evaluate grassland phenology derived from three types of MODIS vegetation indices: the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and a per-pixel GCC (GCCpp) which was computed to describe the average vegetation color at the pixel level. The start of greenness (SOG), end of greenness (EOG), and length of greenness (LOG), and the dates for detailed seasonal dynamics for each site-year were compared. Our results indicate that MODIS VIs can be used to predict phenological metrics and seasonal dynamics in grassland greenness measured from PhenoCam GCC. More importantly, we quantified the difference between SOG, EOG, and LOG and seasonality estimated from satellite and near-surface remote sensing and discovered that GCCpp may be more suitable than NDVI and EVI at estimating dynamics in grassland greenness during senescence.