Wu Bingfang, Zhang Miao, Zeng Hongwei, Tian Fuyou, Potgieter Andries B, Qin Xingli, Yan Nana, Chang Sheng, Zhao Yan, Dong Qinghan, Boken Vijendra, Plotnikov Dmitry, Guo Huadong, Wu Fangming, Zhao Hang, Deronde Bart, Tits Laurent, Loupian Evgeny
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China.
School of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
Natl Sci Rev. 2022 Dec 19;10(4):nwac290. doi: 10.1093/nsr/nwac290. eCollection 2023 Apr.
Building a more resilient food system for sustainable development and reducing uncertainty in global food markets both require concurrent and near-real-time and reliable crop information for decision making. Satellite-driven crop monitoring has become a main method to derive crop information at local, regional, and global scales by revealing the spatial and temporal dimensions of crop growth status and production. However, there is a lack of quantitative, objective, and robust methods to ensure the reliability of crop information, which reduces the applicability of crop monitoring and leads to uncertain and undesirable consequences. In this paper, we review recent progress in crop monitoring and identify the challenges and opportunities in future efforts. We find that satellite-derived metrics do not fully capture determinants of crop production and do not quantitatively interpret crop growth status; the latter can be advanced by integrating effective satellite-derived metrics and new onboard sensors. We have identified that ground data accessibility and the negative effects of knowledge-based analyses are two essential issues in crop monitoring that reduce the applicability of crop monitoring for decisions on food security. Crowdsourcing is one solution to overcome the restrictions of ground-truth data accessibility. We argue that user participation in the complete process of crop monitoring could improve the reliability of crop information. Encouraging users to obtain crop information from multiple sources could prevent unconscious biases. Finally, there is a need to avoid conflicts of interest in publishing publicly available crop information.
建立一个更具韧性的粮食系统以实现可持续发展，以及减少全球粮食市场的不确定性，都需要同时具备近乎实时且可靠的作物信息来进行决策。卫星驱动的作物监测已成为在地方、区域和全球尺度获取作物信息的主要方法，它能揭示作物生长状况和产量的时空维度。然而，目前缺乏定量、客观且可靠的方法来确保作物信息的可靠性，这降低了作物监测的适用性，并导致不确定且不良的后果。在本文中，我们回顾了作物监测的最新进展，并确定了未来工作中的挑战与机遇。我们发现，卫星衍生指标并未完全捕捉到作物产量的决定因素，也未对作物生长状况进行定量解读；通过整合有效的卫星衍生指标和新型机载传感器，后者可以得到改进。我们已经确定，地面数据的可获取性以及基于知识分析的负面影响是作物监测中的两个关键问题，它们降低了作物监测在粮食安全决策中的适用性。众包是克服地面真值数据可获取性限制的一种解决方案。我们认为，用户参与作物监测的全过程可以提高作物信息的可靠性。鼓励用户从多个来源获取作物信息可以避免无意识的偏差。最后，在发布公开可用的作物信息时需要避免利益冲突。
