Spatio-Temporal Reconstruction of MODIS NDVI by Regional Land Surface Phenology and Harmonic Analysis of Time-Series

Satellite-derived Normalized Difference Vegetation Index (NDVI) is frequently obstructed by adverse atmospheric components resulting in data gaps in time series. The harmonic analysis of time series (HANTS) algorithm is a widely used technique to reconstruct missing NDVI time series. However, due to restriction of HANTS to act within temporal dimension, its direct application is bound to endure practical problems in spatiotemporal reconstruction due to large data gaps. This study proposes Moving Offset Method (MOM), a novel prefilling method applied on NDVI time series prior to application of HANTS. MOM restores the missing NDVI time series by assuming that it tends to follow a reference pattern of land surface phenology (NDVIref). The NDVIref is prepared by using a recursive search and fill algorithm (SFA) for data availability without null values. It restores null values in NDVIref at a pixel by using coefficients of linear regression with NDVIref at another pixel having identical conditions. Finally, the prefilling is prior to application of HANTS. The proposed approach is demonstrated by using MODIS 16-daily time series data for Northeast India and Bhutan region which is covered with frequent seasonal clouds. Besides direct application of HANTS, it is also compared with similar approaches which includes prefilling by inverse distance weighted (IDW) and cubic spline, prior to application of HANTS. The fitting indicators, overall reconstruction error (ORE) and normalized noise related error (NNRE) are found to be best for proposed approach in spatiotemporal comparison. Also, restoration of seasonality trait the NDVI time series better in the proposed approach. This approach is concluded to be an enhancement for HANTS that could be helpful in improving quality of NDVI reconstruction for regions with frequent seasonal obstructions around the globe.