RESUMO
As satellite launching increases worldwide, uncertainty quantification for satellite data becomes essential. Misunderstanding satellite data uncertainties can lead to misinterpretations of natural phenomena, emphasizing the importance of validation. In this study, we established a tower-based network equipped with multispectral sensors, SD-500 and SD-600, to validate the satellite-derived NDVI product. Multispectral sensors were installed at eight long-term ecological monitoring sites managed by NIFoS. High correlations were observed between both multispectral sensors and a hyperspectral sensor, with correlations of 0.76 and 0.92, respectively, indicating that the calibration between SD-500 and SD-600 was unnecessary. High correlations, 0.8 to 0.96, between the tower-based NDVI with Sentinel-2 NDVI, were observed at most sites, while lower correlations at Anmyeon-do, Jeju, and Wando highlighting challenges in evergreen forests, likely due to shadows in complex canopy structures. In future research, we aim to analyze the uncertainties of surface reflectance in evergreen forests and develop a biome-specific validation protocol starting from site selection. Especially, the integration of tower, drone, and satellite data is expected to provide insights into the effect of complex forest structures on different spatial scales. This study could offer insights for CAS500-4 and other satellite validations, thereby enhancing our understanding of diverse ecological conditions.
RESUMO
Owing to climate change and frequent extreme weather events, changes in spring flowering phenology have been observed in temperate forests. The flowering time response to climate change is divergent among species and is difficult to predict due to the complexity of flowering mechanisms. To compare the effects of spring warming, winter chilling, and day length on spring flowering time, we evaluated eight process-based models (two types of forcing models, two types of chilling-forcing models, and four models with the effect of day length added to the aforementioned four models). We used flowering data of seven temperate species (Cornus officinalis, Rhododendron mucronulatum, Forsythia koreana, Prunus yedoensis, Rhododendron yedoense f. poukhanense, Rhododendron schlippenbachii, and Robinia pseudoacacia) observed in nine different arboretums in South Korea over 9 years. Generally, the forcing model performed better than the sequential chilling-forcing model, regardless of the species. The performance gap between the models was reduced when day length term was included in model, but the chilling-forcing model did not outperform the forcing model. The effect of day length on flowering time differed depending on the species. Prunus yedoensis, which had a particularly low warming sensitivity compared to other species, was more dependent on day length than other species. On the other hand, day length had little effect on the flowering time of Robinia pseudoacacia and Cornus officinalis, mostly found in the early successional stage. These findings imply that the effect of chilling on flowering time would be minor for the seven species inhabiting the warm-temperate forest, and the effect of day length on flowering time was species-specific and dependent on species' temperature (warming) sensitivity and life strategy. In the future warm climate, the flowering time of day length sensitive species would not advance significantly, which may result in a phenological mismatch and endanger their life.
