Hedgementation = Hedgerow Segmentation: A Remote Sensing Benchmark

Nathan Senyard, Salem Hamdani, Astrid Zhang, Derek Wang, Evan Shelhamer, Mathias Lécuyer, Joséphine Gantois

TL;DR: We provide a new remote sensing benchmark for the recognition and localization of hedgerows as important features of agricultural landscapes.

Abstract: We propose Hedgementation: a new benchmark to evaluate machine learning models for hedgerow mapping from remote sensing data at country scale and 10m^2 spatial resolution. We combine and harmonize multiple remote sensing data products and ground truth labels sourced from a hedgerow inventory in France. We measure the ability of three baseline models to generalize across spatial distance, and across climatic zones, a more explicitly challenging task. Our benchmark tests both supervised and self-supervised learning approaches for remote sensing, applied to tracking fine-scale features of high agricultural importance.

Submission Number: 61