行星的田地：超越10米的田地边界测绘
Fields of the Planet: Field Boundary Mapping Beyond 10m
AI总结：
介绍Fields of the Planet（FTP），作为Fields of The World（FTW）的3米分辨率配套产品，通过矢量预测评估田地划分，在匹配架构和训练方法下，3米图像提升了全景质量等指标。
摘要：
田地边界地图支持作物监测、灌溉规划和产量估计，但许多小农户地块仅跨越几个10米的哨兵 - 2像素。我们引入了Fields of the Planet（FTP），它是Fields of The World（FTW）的3米行星观测配套产品，在24个国家对133,168个共同注册的行星观测补丁窗口目标进行相同多边形、季节窗口和训练/测试分割。FTP通过在对全景质量（PQ）、对象F1、大小分层PQ和米级匹配边界误差评分之前对预测进行矢量化，将田地划分评估为地块恢复。在匹配的架构和训练方法下，3米图像将PQ从21.0提高到35.5，将小于0.5公顷田地的PQ从5.8提高到15.7，并将匹配边界误差从18.6米减少到7.4米。
英文摘要：
Field-boundary accuracy depends on the model, sensor resolution, label discretization, and evaluation procedure. Measuring the contribution of sensor resolution therefore requires a controlled comparison across sensors. We present Fields of the Planet (FTP), a 3 m PlanetScope companion to Fields of The World (FTW) containing 133,168 co-registered patch-window targets across 24 countries. FTP preserves FTW's vector polygons, seasonal windows, and dataset splits, enabling direct comparison with 10 m Sentinel-2. We first quantify the resolution ceiling by rasterizing and vectorizing the same ground-truth parcels at each resolution to determine which fields the label grid can represent. We evaluate predicted parcels with polygon-level and boundary metrics. With identical PRUE+ training and post-processing across sensors, plus an upsampled Sentinel-2 control, we isolate gains from image content. PlanetScope raises panoptic quality (PQ) from 21.0 to 35.5, improves PQ on sub-$0.5$ ha fields from 5.8 to 15.7, and reduces matched-boundary error from 18.6 m to 7.4 m. Pixel-level metrics understate this improvement, so field-boundary benchmarks should account for sensor resolution.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
