Published June 11, 2021
| Version 1
Dataset
Open
Application of a Partial Convolutional Neural Network for Estimating Geostationary Aerosol Optical Depth Data (sample data and model outputs)
Authors/Creators
Description
We implemented a partial convolutional neural network for the imputation of missing remote sensing data.
The data set is saved as comma-separated values (CSV) format and comprise of:
1. 54 sample cases of GOCI input data (with NaN regions) for 2018
2. Output of Kriging, Partial CNN, and Inverse Distance Weighting imputation of the respective GOCI input samples
3. Topology (used as input for the Partial CNN model), Latitude, and Longitude of the respective GOCI data.
Files
GOCI_Input.zip
Files
(216.8 MB)
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