RGB-to-NDVI-conversion dataset

Dataset for the article: Evaluating Generalization of Methods for Artificially Generating NDVI from UAV RGB Imagery in Vineyards A full description of the article can be found at MDPI Remote Sensing: https://www.mdpi.com/2072-4292/17/3/512 As well as the base data for training Pix2Pix architectures presented on GitHub. This data repository contains: p2p_data.rar which are the preprocessed chips which were used to train and evaluate the Pix2Pix models on. In this folder: 256x256 and 512x512 chips each in individual folders per sensor: ms_512 ms_256 rgb_512 ms_256 256x256: ms contains only training useful chips, rgb_256 contains all the test chips from can2023 and btg2021 as well A=RGB B=NDVI AB aligned A+B 512x512: Each folder contains the structure that Pix2Pix expects: A for 3band imgs, B for NDVI train_A/test_A/val_A -> RGB or msRGB chips from BTG2022 train_B/test_B/val_B -> NDVI chips from BTG2022 test_2021_A -> msRGB chips from BTG2021 test_2023_A -> RGB chips from CAN2023 *_B -> NDVI chips orthos.rar, used in the earliest stages to create chips, and used for evaluation again later. canyelles: RGB, ndvi, chm, dem, dsm btg2021, ms, ndvi, chm, dem, dsm btg2022, ms, RGB, ndvi, chm, dem, dsm preprocessed.rar: Input files for the evaluation code, after aligning rasters, reconstructing chips to orthos