Abstract
Remote sensing of high-latitude forests phenology is essential for understanding the global carbon cycle and the response of vegetation to climate change. The normalized difference vegetation index (NDVI) has long been used to study boreal evergreen needleleaf forests (ENF) and deciduous broadleaf forests. However, the NDVI-based growing season is generally reported to be longer than that based on gross primary production (GPP), which can be attributed to the difference between greenness and photosynthesis. Instead of introducing environmental factors such as land surface or air temperature like previous studies, this study attempts to make VI-based phenology more consistent with photosynthesis dynamics through applying a light use efficiency model. NDVI (MOD13C2) was used as a proxy for both fractional of absorbed photosynthetically active radiation (APAR) and light use efficiency at seasonal time scale. Results show that VI-based phenology is improved towards tracking seasonal GPP changes more precisely after applying the light use efficiency model compared to raw NDVI or APAR, especially over ENF.
Highlights
Phenology is the study of the timing of vegetation growing/senescence events based on vegetation seasonal dynamics [1]
We investigate the feasibility of using the vegetation indices (VIs)-based light use efficiency (LUE) model to track seasonal dynamics of gross primary production (GPP) over high-latitude forests
Our results showed that VI-based phenology of evergreen needleleaf forests (ENF)
Summary
Phenology is the study of the timing of vegetation growing/senescence events based on vegetation seasonal dynamics [1]. Satellite observations of land surface provides spatially-continuous time-resolved reflectance data of terrestrial vegetation. Extracting phenological timing from time-series remote sensing data is an effective tool for monitoring large-scale vegetation dynamics, especially where in-situ observations are lacking (e.g., [2]). Remote sensing of vegetation phenology is based on the seasonal cycle of reflectance-based vegetation indices (VIs). VIs have been regarded as proxies of the green biomass of vegetation canopy, carrying information of leaf greenness and canopy structure [3]. Because VIs often show clear seasonal cycles over mid-high latitude forests, due to seasonal changes of temperature and precipitation [4,5], numerous researches have utilized VI time-series curves to study the phenology of such vegetation
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
