Publications

Cui, TF; Martz, L; Lamb, EG; Zhao, L; Guo, XL (2019). Comparison of Grassland Phenology Derived from MODIS Satellite and PhenoCam Near-Surface Remote Sensing in North America. CANADIAN JOURNAL OF REMOTE SENSING, 45(5), 707-722.

Abstract
ReSUMe La validation au sol de la phenologie de la vegetation estimee par satellite est difficile parce que les donnees phenologiques in situ sont mal distribuees et surtout observees a partir d'un nombre limite d'especes vegetales a des phenophases discretes. Le reseau PhenoCam recemment developpe mesure en continue la croissance du verdissement de la vegetation. Il peut etre utilise pour valider la phenologie de la vegetation estimee par satellite a travers une variete de types fonctionnels de plantes. Dans cette etude, nous avons utilise les coordonnees chromatiques vertes (GCC) en Amerique du Nord de PhenoCam pour evaluer la phenologie des prairies derivee de trois types d'indice de vegetation MODIS: l'indice de vegetation de difference normalisee (NDVI), l'indice de vegetation ameliore (IVI) et l'indice GCC par pixel (GCCpp) qui a ete calcule pour decrire la couleur moyenne de la vegetation au niveau des pixels. Le debut du verdissement (SOG), la fin du verdissement (EOG) et la longueur de la periode vegetative (LOG) et les dates de la dynamique saisonniere detaillees pour chaque annee ont ete comparees. Nos resultats indiquent que l'indice MODIS IVI peut etre utilise pour predire les mesures phenologiques et la dynamique saisonniere des prairies a partir de PhenoCam GCC. Plus important encore, nous avons quantifie la difference entre les indices SOG, EOG, et LOG et la saisonnalite estimee a partir de donnees satellites et observees pres de la surface Nous avons decouvert que GCCpp peut etre plus approprie que NDVI et EVI pour estimer la dynamique de verdissement des prairies au cours de la senescence. 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.

DOI:
10.1080/07038992.2019.1674643

ISSN:
0703-8992