Monitoring of plant reproductive phenology at large spatial scale is important to detect effects of climate change on various ecosystems. Remote sensing data has a great potential to improve phenological observation of plants as it provides spatially large and temporally frequent data. However, spectral mixtures of elements in a pixel and weak spectral signals of plant reproductive organs are two major issues to estimate phenological condition of plant reproductive status using remotely sensed data. To explore the possibility of monitoring flowering status of plants using remotely sensed data, we evaluate the accuracy of cherry blossom (Somei Yoshino) geographical distribution estimates by MODIS (1km spatial resolution) with IKONOS (4m spatial resolution, as a control data). Mixture Tuned Matched Filtering (MTMF), a specialized type of mixture analysis was applied to both MODIS and IKONOS data. MODIS showed higher estimation accuracy at the areas with high cherry blossom density (for example park), but low at the areas with low cherry blossom density. Therefore, we conclude that the accuracy of cherry blossom estimates by using MODIS was relying on the density of cherry blossom.