Monitoring Myanmar’s Complex Water Networks with an Adaptive Interwoven Deep Learning Framework and Multi-Source Remote Sensing

The dataset contains 2372 samples, each with dimensions of 128×128×8 pixels, corresponding to the same number of labels, with label dimensions of 128×128×1 pixels. The spatial resolution of the samples is 30-meters/pixel, suitable for land surface feature analysis. The labels use binary classification, where 0 represents non-water bodies and 1 represents water bodies. The data comes from Landsat-8 satellite imagery, applicable for water body detection, environmental monitoring, and related research.