Ecological consideration for several methodologies to diagnose vegetation phenology

• Published in: Ecological research Vol. 33; no. 2; pp. 363 - 377
• Main Authors: Lim, Chi Hong, An, Ji Hong, Jung, Song Hie, Nam, Gyung Bae, Cho, Yong Chan, Kim, Nam Shin, Lee, Chang Seok
• Format: Journal Article
• Language: English
• Published: Tokyo Springer Japan 01.03.2018; Blackwell Publishing Ltd
• Subjects: Behavioral Sciences; Biomedical and Life Sciences; Climate change; Curvature; Curvature K index; Digital camera; Digital cameras; Digital imaging; Ecology; Evolutionary Biology; Forestry; HMV; Life Sciences; MODIS; Phenology; Plant Sciences; Remote monitoring; Remote sensing; Sap flow; Satellite image; Senescence; Special Feature; Time series; Vegetation; Visual observation; Zoology; HMV; Satellite image; Climate change; Curvature K index; Sap flow; Digital camera
• ISSN: 0912-3814; 1440-1703
• DOI: 10.1007/s11284-017-1551-3

A challenge of phenological research is to integrate remotely sensed observations obtained at different spatial and temporal scales to provide information that contains both a high temporal density and fine spatial scale observations. This study aims to improve the level of spatial detail and the temporal density required for efficient monitoring of vegetation phenology by applying two remote sensing techniques, MODIS and digital camera images. Based on the vegetation indices extracted from each measurement, we analyzed phenological changes of vegetation and deduced phenophases transition dates, such as start dates of green-up and senescence by applying different two methods, the rate of change of curvature, K and HMV. The start and end of the growing season of Mongolian oak expressed in ExG–DC, which were extracted from digital camera image, were agreed well with that of visual assessment. EVI among three vegetation indices (EVI, NDVI and ExG–MI) showed the high correlation with ExG–DC and visual assessment. Based on RMSE, the transition dates assessed by visual observation were agreed better with the dates, which were estimated based on curvature K than with the dates estimated from HMV in all vegetation indices. Sap flow time-series estimates for the phenological transition dates were closely accorded with the estimates derived from near-surface time-series, and coincided better with the dates estimated based on curvature K than that based on HMV. In conclusion, based on the result of this study, we suggest that it is effective to use EXG–DC obtained from digital camera and EVI from MODIS when these two instrument are integrated as the vegetation indices and that curvature K is an effective method for extracting the phenological event dates of vegetation.