Temporal NDVI Reconstruction Method Based on UBiaSTF Spatiotemporal Fusion Model

Abstract:

High spatial and temporal resolution NDVI data is of great significance in the application of agricultural remote sensing. Spatiotemporal fusion (STF) models can serve as an effective approach to enhance the spatiotemporal resolution of NDVI data. An STF model, UBiaSTF, was proposed which integrated the Unet framework into BiaSTF, and applied it to the spatiotemporal NDVI fusion of Landsat 8 and Sentinel-2 with MODIS imagery in the Jiefangzha Irrigation District. The model was compared with ESTARFM and BiaSTF models to analyze its effectiveness in the reconstruction of remote sensing time series NDVI. The results indicated that the UBiaSTF model performed excellently in the reconstruction of NDVI time series, with the coefficient of determination R2 significantly improved compared with that of other models, reaching a maximum of 0.930. Additionally, the UBiaSTF model demonstrated strong stability in long time series data fusion tasks, effectively overcoming the impact of reference image temporal interval changes on prediction accuracy. Furthermore, the UBiaSTF model showed the lowest fusion error in the reconstruction of time series NDVI across different vegetation coverage categories compared with ESTARFM and BiaSTF, closely matching the actual changes. This model can serve as an effective tool for the reconstruction of time series NDVI in areas with vegetation coverage.