想测试遥感模型对细节的抓取能力？这个基准用了法国全国树篱数据，10米分辨率，还能跨气候区泛化。
Hedgementation 是一个面向国家尺度、10m² 空间分辨率的树篱映射遥感基准。它整合了多个遥感数据产品与法国树篱清单的标注，用于评估机器学习模型。基准测试了三个基线模型在空间距离和气候区域上的泛化能力，并涵盖监督和自监督学习方法。代码已开源在 GitHub。
Hedgementation = Hedgerow Segmentation: A Remote Sensing Benchmark
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. The code to reproduce the benchmark and baselines results is available at https://github.com/hedgementation/hedgementation.