AgriSen - A Dataset for Crop Classification

Abstract

The large amount of collected data in the field of Earth Observation has created the need for automatization in processing and extraction information from it. Thus, deep learning (DL) techniques have gained popularity among the remote sensing community. Agriculture is one of the domains where DL can improve the current state-of-the-art. In this paper, we focus on the task of crop type classification, a key task in the process of assessing the agricultural market and yield. To this purpose, we introduce a new dataset, based on publicly available data (images from satellite Sentinel-2 and annotations from Land Parcel Identification System), to be used for further research in this field.