Gross primary production (GPP) is a fundamental measure of the terrestrial carbon cycle critical to our understanding of ecosystem function under the changing climate and land use. Remote sensing enables access to continuous spatial coverage, but remains challenged in heterogeneous croplands. Coarse resolution products, like MOD17A (500 m), may aggregate fragmented land cover types commonly found in heavily managed landscapes and misrepresent their respective contribution to carbon production. Consequently, this study demonstrates the capability of fine-resolution imagery (20-30 m) and available red-edge vegetation indices to characterize GPP across seven Midwest cropping systems. Four sites were established on a 22-year-old USDA Conservation Reserve Program (CRP); and the other three on land conventionally farmed with corn-soybean-wheat rotation (AGR). We compare in situ GPP estimates from eddy-covariance towers with ten satellite models: eight variants of the vegetation photosynthesis models (VPM), of which five include a red-edge vegetation index, as well as conventional products Landsat CONUS GPP (30 m) and MOD17AH V6 (500 m). Daily and cumulative fine-resolution imagery integrated within VPM generally agreed with tower-based GPP in heterogeneous landscapes more than those from MODIS 500 m VPM or conventional GPP products from MOD17AH V6 or Landsat 8 CONUS. Replacing EVI2 with red-edge indices NDRE2, NDRE1, and MTCI in Sentinel 2 VPMs notably improved explanation of variance and estimation of cumulative GPP. While existing methods using MODIS- and Landsat-derived GPP are important baselines for regional and global studies, future research may benefit from the higher spatial, temporal, and radiometric resolution.

初级生产总值 (GPP) 是陆地碳循环的基本衡量标准，对于我们了解气候变化和土地利用变化下的生态系统功能至关重要。遥感能够获得连续的空间覆盖，但在异质农田中仍然面临挑战。粗分辨率产品，如 MOD17A (500 m)，可能会聚合在管理严密的景观中常见的碎片化土地覆盖类型，并歪曲它们各自对碳生产的贡献。因此，本研究展示了高分辨率图像 (20-30 m) 和可用红边植被指数在中西部七个种植系统中表征 GPP 的能力。在一个 22 年历史的美国农业部自然保护区计划 (CRP) 上建立了四个地点；其他三个在传统上以玉米-大豆-小麦轮作（AGR）方式耕作的土地上。我们比较原位来自涡协方差塔的 GPP 估计值有 10 个卫星模型：植被光合作用模型 (VPM) 的 8 个变体，其中 5 个包括红边植被指数，以及常规产品 Landsat CONUS GPP (30 m) 和 MOD17AH V6 ( 500 米）。与来自 MODIS 500 m VPM 或来自 MOD17AH V6 或 Landsat 8 CONUS 的传统 GPP 产品相比，集成在 VPM 中的每日和累积高分辨率图像通常与异质景观中的基于塔的 GPP 一致。在 Sentinel 2 VPM 中用红边指数 NDRE2、NDRE1 和 MTCI 替换 EVI2 显着改善了对方差的解释和累积 GPP 的估计。虽然使用 MODIS 和 Landsat 衍生 GPP 的现有方法是区域和全球研究的重要基线，但未来的研究可能会受益于更高的空间、时间、