Time series interpolation

A consistent data acquisition interval among multi-temporal images is necessary to accurate landscape change detection and temporal-series signatures. Orbital images are difficult to maintain a temporal precision due to the different interferences that generate missing data. The correct handling of missing data is a difficult problem in data analysis and often depends on your specific situation. This missing information can be replaced using an interpolation method. In this paper is proposed a new algorithm that interpolates multitemporal images. This new computation method uses the cubic-spline interpolation technique to trace the reflectance and NDVI behaviors along time. The performance of the cubic-spline interpolation technique in the determination of NDVI temporal series is verified in terms of accuracy.