What information is important? A spatiotemporal inference for classification of satellite image time series

Satellite image time series has been broadly used to map land covers due to the repetitive measurements ability and rich spatiotemporal information it contained. However, existing studies in SITS tended to only express and employ one or two aspects of spectral, spatial, and temporal features without fully utilizing all the three information, leading to the unsatisfactory results of SITS classification. Accordingly, this study aim at obtaining land cover information base on classification of SITS with integratively expressing and employing spectral, spatial and temporal features. Moreover, results of different combinations of the three kinds of features are evaluated and compared to infer the effect and importance of features, and find the optimal features for SITS classification. Experiments carried out with this methodology show the effectiveness of this approach, potentially contributing to the feature extracted and classification patterns in SITS.