Annual changes in MODIS vegetation indices of Swedish coniferous forests in relation to snow dynamics and tree phenology

Remote sensing provides spatially and temporally continuous measures of forest reflectance, and vegetation indices calculated from satellite data can be useful for monitoring climate change impacts on forest tree phenology. Monitoring of evergreen coniferous forest is more difficult than monitoring of deciduous forest, as the new buds only account for a small proportion of the green biomass, and the shoot elongation process is relatively slow. In this study, we have analyzed data from 186 coniferous monitoring sites in Sweden covering boreal, southern-boreal, and boreo-nemoral conditions. Our objective was to examine the possibility to track seasonal changes in coniferous forests by time-series of MODIS eight-day vegetation indices, testing the coherence between satellite monitored vegetation indices (VI) and temperature dependent phenology. The relationships between two vegetation indices (NDVI and WDRVI) and four phenological indicators (length of snow season, modeled onset of vegetation period, tree cold hardiness level and timing of budburst) were analyzed.The annual curves produced by two curve fitting methods for smoothening of seasonal changes in NDVI and WDRVI were to a large extent characterized by the occurrence of snow, producing stable seasonal oscillations in the northern part and irregular curves with less pronounced annual amplitude in the southern part of the country. Measures based on threshold values of the VI-curves, commonly used for determining the timing of different phenological phases, were not applicable for Swedish coniferous forests. Evergreen vegetation does not have a sharp increase in greenness during spring, and the melting of snow can influence the vegetation indices at the timing of budburst in boreal forests. However, the interannual variation in VI-values for specific eight-day periods was correlated with the phenological indicators. This relation can be used for satellite monitoring of potential climate change impacts on northern coniferous spring phenology.