Abstract
Combination of near daily 3 m red, green, blue, and near infrared (NIR) Planetscope reflectance with lower temporal resolution 10 m and 20 m red, green, blue, NIR, red-edge, and shortwave infrared (SWIR) Sentinel-2 reflectance provides potential for improved global monitoring. Sharpening the Sentinel-2 reflectance with the Planetscope reflectance may enable near-daily 3 m monitoring in the visible, red-edge, NIR, and SWIR. However, there are two major issues, namely the different and spectrally nonoverlapping bands between the two sensors and surface changes that may occur in the period between the different sensor acquisitions. They are examined in this study that considers Sentinel-2 and Planetscope imagery acquired one day apart over three sites where land surface changes due to biomass burning occurred. Two well-established sharpening methods, high pass modulation (HPM) and Model 3 (M3), were used as they are multiresolution analysis methods that preserve the spectral properties of the low spatial resolution Sentinel-2 imagery (that are better radiometrically calibrated than Planetscope) and are relatively computationally efficient so that they can be applied at large scale. The Sentinel-2 point spread function (PSF) needed for the sharpening was derived analytically from published modulation transfer function (MTF) values. Synthetic Planetscope red-edge and SWIR bands were derived by linear regression of the Planetscope visible and NIR bands with the Sentinel-2 red-edge and SWIR bands. The HPM and M3 sharpening results were evaluated visually and quantitatively using the Q2n metric that quantifies spectral and spatial distortion. The HPM and M3 sharpening methods provided visually coherent and spatially detailed visible and NIR wavelength sharpened results with low distortion (Q2n values > 0.91). The sharpened red-edge and SWIR results were also coherent but had greater distortion (Q2n values > 0.76). Detailed examination at locations where surface changes between the Sentinel-2 and the Planetscope acquisitions occurred revealed that the HPM method, unlike the M3 method, could reliably sharpen the bands affected by the change. This is because HPM sharpening uses a per-pixel reflectance ratio in the spatial detail modulation which is relatively stable to reflectance changes. The paper concludes with a discussion of the implications of this research and the recommendation that the HPM sharpening be used considering its better performance when there are surface changes.
Highlights
The Sentinel-2A and -2B satellites, launched in 2015 and 2017, respectively, acquire global land surface data at 10 m, 20 m, and 60 m in the visible, near infrared (NIR), and shortwave infrared (SWIR) bands [1]
When the data from one sensor are used to sharpen the data from another sensor there are additional challenges, if (i) the sensors have different and spectrally nonoverlapping bands, and (ii) if the images are acquired on different dates when the land surface has changed [8,9]
These two issues are the focus of this study, as Planetscope data have no equivalent Sentinel-2 red-edge and SWIR bands, and Planetscope and Sentinel-2 data are often acquired over the same location on different days
Summary
The Sentinel-2A and -2B satellites, launched in 2015 and 2017, respectively, acquire global land surface data at 10 m, 20 m, and 60 m in the visible, near infrared (NIR), and shortwave infrared (SWIR) bands [1]. When the data from one sensor are used to sharpen the data from another sensor there are additional challenges, if (i) the sensors have different and spectrally nonoverlapping bands, and (ii) if the images are acquired on different dates when the land surface has changed [8,9]. These two issues are the focus of this study, as Planetscope data have no equivalent Sentinel-2 red-edge and SWIR bands, and Planetscope and Sentinel-2 data are often acquired over the same location on different days
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