Dataset for: Howard Slough Waterfowl Management Area Multispectral Imagery at Various Resolutions and Convolutional Neural Network Training Data

This dataset contains the materials necessary to reproduce the study submitted to Remote Sensing: "Tradeoffs Between UAS Spatial Resolution and Accuracy for Deep Learning Semantic Segmentation Applied to Wetland Vegetation Species Mapping". This includes the raw imagery output from the camera aboard the unoccupied aerial vehicle, the Red-Edge MX, captured over the Howard Slough Waterfowl Management Area, Utah, in August of 2020, resampled images, code to resample the images, a link to ground reference data, and the training and testing data used for the convolutional neural network in the study.