{
    "description": "Automatic, accurate crop type maps can provide unprecedented information for understanding food systems, especially in developing countries where ground surveys are infrequent. However, little work has applied existing methods to these data scarce environments, which also have unique challenges of irregularly shaped fields, frequent cloud coverage, small plots, and a severe lack of training data. To address this gap in the literature, we provide the first crop type semantic segmentation dataset ",
    "tags": [
        "sentinel-1",
        "sentinel-2",
        "planetscope",
        "sar",
        "crop type",
        "agriculture",
        "segmentation"
    ]
}