Regional evaluation of satellite-based methods for identifying end of vegetation growing season

Autumn phenology plays an important role in regulating ecosystem carbon and water cycling, but it has received less attention than spring phenology. Satellite-based methods have been widely applied in monitoring autumn phenology at large spatial scales. However, few studies have evaluated and compared the performance of different satellite-based methods in autumn phenology identification. Here, we compared the spatiotemporal variations of end of vegetation growing season dates (EOS) as determined from eight prevailing satellite-based methods against long-term field observations at 31 sites in China. We found that field-based observations in forest and grassland sites, respectively, had rates of EOS delay of 2.11 and 3.85 days per 1 degrees C increase in mean annual temperature (MAT) during 2001-2014. However, nearly all the eight satellite-based methods underestimated these delay rates compared with the ground observations over all sites. We also found that the eight methods weakly agreed with the field-observed interannual variations of EOS. At the regional scale, the identified average EOS differed up to 38 and 40 days among the investigated satellite-based methods in forest and grassland ecosystems respectively. The delayed rate of identified EOS with the increase of MAT ranged from 0.77 to 3.51 days degrees C-1 for forests and from 0.41 to 2.95 days degrees C-1 for grasslands. The identified EOS by most of the eight methods had delayed temporal trends in forests during 2001-2014 while we found advanced trends in grassland ecosystems. The large discrepancy in EOS identification among the prevailing satellite-based methods highlight the need for more accurate satellite-based methods in data gap-filling and phenometrics detection, and more extensive, multi-species based field observations that can be used to constrain and validate the satellite-based methods.

Automated summary

This study compared the performance of different satellite-based methods in identifying autumn phenology in China. Results showed that satellite-based methods underestimated the delay rates of end of vegetation growing season compared to field observations, and there was a large discrepancy in EOS identification among different methods. The study highlights the need for more accurate satellite-based methods and extensive field observations for data gap-filling and phenometrics detection.