Regression based polynomial chaos expansion for crop phenology estimation coupled with polsar imagery

Abstract

Crop phenology monitoring using Synthetic Aperture Radar (SAR) data is gaining popularity within the remote sensing community due to SAR's all weather and large coverage imaging capability. This paper introduces a polynomial chaos expansion (PCE) based regression algorithm to retrieve BBCH scale of crops, which identifies the phenology of crops in a standardized system. The impact and applicability of the proposed methodology is successfully illustrated using the TerraSAR-X dual-pol imagery that was acquired over the cultivation period of paddy-rice fields located in Turkey. To assess the applicability of the methodology, root mean square and correlation analysis were performed under different amount of training data and number of inputs.