Spatio-temporal fusion of NDVI data for simulating soil water content in heterogeneous Mediterranean areas

• Main Authors: Marta Chiesi, Piero Battista, Luca Fibbi, Lorenzo Gardin, Maurizio Pieri, Bernardo Rapi, Maurizio Romani, Francesco Sabatini, Fabio Maselli
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2019-01-01
• Series: European Journal of Remote Sensing
• Subjects: modis; tm/etm+; ndvi; image fusion
• Online Access: http://dx.doi.org/10.1080/22797254.2018.1557501

Recent studies have demonstrated that the soil water content (SWC) of Mediterranean ecosystems can be simulated by combining ground data and remote sensing observations of Normalized Difference Vegetation Index (NDVI). The application of this approach in heterogeneous and fragmented areas, however, requires the use of spatio-temporal fusion (STF) methods to properly account for the actual NDVI variability of the examined ecosystems. One of these methods, which was specifically developed to produce annual NDVI data series in Mediterranean regions, is currently applied to MODIS and TM/ETM+ images taken over a highly fragmented green urban area in Florence (Central Italy). The performances of this STF method, called SEVIS, are indirectly evaluated by comparing local SWC measurements to simulations driven by the original (MODIS) and fused (MODIS+TM/ETM+) NDVI datasets. The results obtained confirm the critical dependence of the applied SWC simulation strategy on the efficient accounting for the actual NDVI evolution of the observed ecosystem. In particular, the use of the fused NDVI dataset corrects almost completely for the strong SWC underestimation produced by the original MODIS images during the summer dry period, significantly improving all accuracy statistics (r2 from 0.564 to 0.855, RMSE from 0.101 to 0.044 cm3 cm−3 and MBE from −0.046 to 0.000 cm3 cm−3).