Annual global land cover maps (GLC) are being provided by several operational monitoring efforts. However, map validation is lagging, in the sense that the annual land cover maps are often not validated. Concurrently, users such as the climate and land management community require information on the temporal consistency of multi-date GLC maps and stability in their accuracy. In this study, we propose a framework for operational validation of annual global land cover maps using efficient means for updating validation datasets that allow timely map validation according to recommendations in the CEOS Stage-4 validation guidelines. The framework includes a regular update of a validation dataset and continuous map validation. For the regular update of a validation dataset, a partial revision of the validation dataset based on random and targeted rechecking (areas with a high probability of change) is proposed followed by additional validation data collection. For continuous map validation, an accuracy assessment of each map release is proposed including an assessment of stability in map accuracy addressing the user needs on the temporal consistency information of GLC map and map quality. This validation approach was applied to the validation of the Copernicus Global Land Service GLC product (CGLS-LC100). The CGLS-LC100 global validation dataset was updated from 2015 to 2019. The update was done through a partial revision of the validation dataset and an additional collection of sample validation sites. From the global validation dataset, a total of 40% (10% for each update year) was revisited, supplemented by a targeted revision focusing on validation sample locations that were identified as possibly changed using the BFAST time series algorithm. Additionally, 6720 sample sites were collected to represent possible land cover change areas within 2015 and 2019. Through this updating mechanism, we increased the sampling intensity of validation sample sites in possible land cover change areas within the period. Next, the dataset was used to validate the annual GLC maps of the CGLS-LC100 product for 2015–2019. The results showed that the CGLS-LC100 annual GLC maps have about 80% overall accuracy showing high temporal consistency in general. In terms of stability in class accuracy, herbaceous wetland class showed to be the least stable over the period. As more operational land cover monitoring efforts are upcoming, we emphasize the importance of updated map validation and recommend improving the current validation practices and guidelines towards operational map validation so that long-term land cover maps and their uncertainty information are well understood and properly used.

一些业务监测工作正在提供年度全球土地覆盖图 (GLC)。然而，地图验证滞后，因为年度土地覆盖图通常未经验证。同时，气候和土地管理社区等用户需要有关多日期 GLC 地图时间一致性及其准确性稳定性的信息。在这项研究中，我们提出了一个框架，用于使用有效的方法更新验证数据集，以便根据 CEOS 第 4 阶段验证指南中的建议及时验证地图，从而对年度全球土地覆盖图进行操作验证。该框架包括定期更新验证数据集和连续地图验证。对于验证数据集的定期更新，建议根据随机和有针对性的重新检查（变化概率高的区域）对验证数据集进行部分修订，然后收集额外的验证数据。对于连续地图验证，建议对每个地图发布进行精度评估，包括地图精度稳定性评估，以满足用户对 GLC 地图时间一致性信息和地图质量的需求。该验证方法应用于哥白尼全球土地服务 GLC 产品 (CGLS-LC100) 的验证。CGLS-LC100 全球验证数据集从 2015 年更新到 2019 年。更新是通过验证数据集的部分修订和样本验证站点的额外集合完成的。从全局验证数据集中，总共重新访问了 40%（每个更新年 10%），辅以有针对性的修订，重点是使用 BFAST 时间序列算法确定为可能发生更改的验证样本位置。此外，还收集了 6720 个样本点，以代表 2015 年和 2019 年可能发生的土地覆盖变化区域。通过这种更新机制，我们增加了该时期内可能的土地覆盖变化区域的验证样本点的抽样强度。接下来，该数据集用于验证 CGLS-LC100 产品 2015-2019 年的年度 GLC 地图。结果表明，CGLS-LC100 年度 GLC 地图的整体准确度约为 80%，总体上显示出较高的时间一致性。在类精度的稳定性方面，草本湿地类在此期间表现出最不稳定。随着更多可操作的土地覆盖监测工作即将展开，