Geostatistical interpolation of SLC-off Landsat ETM+ images

By Matthew Pringle, Michael Schmidt, Jasmine Muir. 2009

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Harmonic regression of Landsat time series for modeling attributes from national forest inventory data (2018, unknown): “…proposed to dealing with them, including compositing of several images (Roy et al., 2010), interpolation using SLC-on imagery (Maxwell et al., 2007; Chen et al., 2011), data fusion with MODIS imagery (Roy et al., 2008), and geostatistical methods (Zhang et al., 2007; Pringle et al., 2009).”
Recovering missing pixels for Landsat ETM + SLC-off imagery using multi-temporal regression analysis and a regularization method (2013, methodology): “Although this study showed that geostatistical methods can be effective, accurate prediction is still difficult at the junction of different land-use types (Pringle et al., 2009).”
A simple and effective method for filling gaps in Landsat ETM+ SLC-off images (2011, unknown): “…approaches, we felt that conducting similar pixelbased comparisons between NSPI and the multi-scale segmentation approach (Maxwell et al., 2007) or the geostatistics based methods (Zhang, et al., 2007; Pringle et al., 2009) was statistically problematic and beyond the scope of the study.”
Missing Information Reconstruction of Remote Sensing Data: A Technical Review (2015, methodology): “, the joint spatio-spectral methods [43] and the joint spatio-temporal methods [92].”