Hyperspectral signatures of crops under different management type, crop classification models, Heracleum detection

This dataset consists of a total of four individual outputs described in the certified methodology "Monitoring agricultural crops using innovative remote sensing methods". These are:1) a dataset of hyperspectral signatures extracted from the CASI aerial hyperspectral data time series for the Polkovice experimental agricultural site in the Czech Republic. The dataset captures the time series of spectral signatures of selected agricultural crops under different types of management (tillage/no-tillage, with and without added biochar) - a total of 1,140,304 individual crop spectra. Furthermore, this dataset contains scripts in the Matlab programming language for processing and interpreting these signatures - visualization, spectral separability testing, training classification models2) a dataset of crop spectral signatures extracted from two simultaneously acquired satellite data, Sentinel-2 (multispectral dataset) and Prisma (hyperspectral dataset). In addition, the dataset contains trained models for crop classification from these two datasets as a Matlab function3) a dataset of spectral signatures of agricultural crops according to the SAMAS classification scheme extracted from the EnMap hyperspectral sensor time series and a Matlab script for their preprocessing4) a JavaScript script for Google Earth Engine to detect the presence of greater sagebrush (Heracleum mantegazzianum)