GSWF: Global Surface Water gap-Filled dataset

We created a large training dataset using the JRC GSW dataset with simulated gap areas to teach the model how to fill in the gaps.Each GeoTIFF file in the dataset has two bands:1. Water/Non-Water (Binary): Indicates whether the pixel is water (1) or non-water (0).2. Good Quality/Bad Quality (Binary): Indicates whether the pixel is of good quality (1) or bad quality (0).The dataset uses a single-bit storage format to save memory.Quality Score CalculationThe quality score in our dataset is a binary score assigned to each 256x256 gap-filled block.

It is calculated based on the proportion of valid observations within the block. A quality score of 1 indicates a high-quality block, while a score of 0 represents a low-quality block. The quality score calculation process is as follows:1.

For each 256x256 block, count the number of valid observations (pixels with a "good quality" value of 1 in the Good Quality/Bad Quality band). Calculate the percentage of valid observations in the block by dividing the number of valid observations by the total number of pixels in the block (256x256 = 65,536).2. Assign a binary quality score to the block:If the percentage of valid observations is equal to or greater than 2%, assign a quality score of 1 (high quality).If the percentage of valid observations is less than 2%, assign a quality score of 0 (low quality).V2: Some data descriptions have been improved.