Weed Species Identification: A Hyperspectral and RGB Dataset with Labeled Data
Description
The data set contains meticulously sampled and labeled data for training and testing. The images represent a time series of the weed's growth along its early growth stages, which is critical for precise herbicide application.
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For full description of the data, please refer to our paper: Ronay, Inbal, Ran Nisim Lati, and Fadi Kizel. 2024. "Weed Species Identification: Acquisition, Feature Analysis, and Evaluation of a Hyperspectral and RGB Dataset with Labeled Data" Remote Sensing 16, no. 15: 2808. https://doi.org/10.3390/rs16152808 Our dataset comprises five scenes. Each scene was created by sowing weed seeds within a 34×54 cm sowing tray divided into cells of 2×2 cm. The weeds were grown in a greenhouse with daily irrigation. We recorded the five scenes over six days within two weeks following weed sowing, using a hyperspectral camera (Specim IQ, Oulu, Finland). We acquired the images at 7,8, 9, and 12,13 14 Days After Sowing (DAS), where the weeds started at stage 12 and reached stages 13 -14 on the BBCH scale. Some weed traits, such as the weed botanical group, are essential for making informed decisions about herbicide selection. Consequently, three distinct weed species were carefully chosen in the dataset: Amaranthus retroflexus (Ar), Solanum nigrum (Sn), and Setaria adhaerens (Sa). These species were selected because they represent different botanical groups and photosynthesis pathways, as detailed in our paper mentioned above. This selection facilitates a comprehensive exploration of the spectral resemblances and disparities among the chosen weed species. The image acquisition process involved maintaining a consistent camera distance of 1.5, with the scene illuminated by two halogen light spots. The hyperspectral images encompass 512×512 pixels with a spatial resolution of 0.1cm and 204 spectral bands within the visible and near-infrared range (400-1000 nm). In addition to the hyperspectral image, the Specim camera concurrently captures an RGB image of the scene with a size of 645×645 pixels.