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Downscaling of Landsat 8 OLI - Reflective Wavelength Bands using Landsat 15-m Panchromatic-Assisted


I came across this very interesting paper in which Landsat - 8 reflective bands were downscaled to Sentinel - 2 20-m resolution using Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) Method. The method first downscales the Landsat-8 30-m OLI bands to 15-m using the spatial detail provided by the Landsat-8 15-m panchromatic band and then reprojects and resamples the downscaled 15-m data into registration with Sentinel-2A 20-m data. The LPAD method is demonstrated using pairs of contemporaneous Landsat-8 OLI and Sentinel-2A MSI images sensed less than 19 min apart over diverse geographic environments. The LPAD method is shown to introduce less spectral and spatial distortion and to provide visually more coherent data than conventional bilinear and cubic convolution resampled 20-m Landsat OLI data. In addition, results for a pair of Landsat-8 and Sentinel-2A images sensed one day apart suggest that image fusion should be undertaken with caution when the images are acquired under different atmospheric conditions. The LPAD source code is available at GitHub for public use (Li et al, 2017).


(Image Credit: Li et al, 2017 and MDPI Remote Sensing)

Figure - Crop field, California, true color images showing: (a) Sentinel-2A 20-m image (3000 × 3000 20-m pixels) and sub-set (red box); (b) Sentinel-2A 256 × 256 20-m pixel sub-set; (c) Landsat-8 bilinear resampled to 20 m; (d) Landsat-8 bilinear-based LPAD 20-m data; (e) Landsat-8 cubic convolution resampled to 20 m; (f) Landsat-8 cubic convolution-based LPAD 20-m data.

The LPAD method adopted by the author of the research paper works principally using two steps-

(i) Use Panchromatic band of Landsat to downscale Landsat-8 30-m Data to 15 m.

(ii) Perform reprojection and resampling of the Downscaled 15-m data into registration with the Sentinel-2A 20-m Data

Results showcased that

(1) the LPAD method introduced less spectral and spatial distortion and provided visually more coherent data than traditional bilinear and cubic convolution resampling approaches;

(2) the LPAD approach can be effectively applied to downscaling the Landsat-8 30-m OLI bands;

(3) the bilinear-based LPAD approach provided the least spectral and spatial distortion; and

(4) Landsat-8 and Sentinel-2A data fusion should be undertaken with caution when images are acquired at different times under different atmospheric conditions.

The LPAD source code is made available at GitHub for public use and evaluation at https://github.com/jasonleepolyu/Landsat-Panchromatic-Assisted-Downscaling-LPAD-/tree/master

Reference:

Disclaimer: The geoinformers.com does not take any credit of the work depicted above.

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