利用近地相机对农田进行监测,促进气候智能型农业的发展

Le Yu , Zhenrong Du , Xiyu Li , Qiang Zhao , Hui Wu , Duoji weise , Xinqun Yuan , Yuanzheng Yang , Wenhua Cai , Weimin Song , Pei Wang , Zhicong Zhao , Ying Long , Yongguang Zhang , Jinbang Peng , Xiaoping Xin , Fei Xu , Miaogen Shen , Hui Wang , Yuanmei Jiao , Yong Luo
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引用次数: 0

摘要

对农业景观进行连续、准确的监测对于了解作物物候以及应对气候和人为变化至关重要。然而,广泛使用的光学卫星遥感受到重访周期和天气条件的限制,导致农业监测出现空白。针对这些局限性,我们设计并在中国各地部署了近地面相机(NSCam)网络,探索其在农田监测和实现气候智能农业(CSA)中的应用。通过分析近地相机网络获取的图像数据,我们可以准确评估农田的长期或突然变化。根据初步监测结果,将 NSCam 数据与遥感图像相结合,可大大提高农业监测的时间细节和准确性,帮助农业管理者做出明智决策。对于遥感图像无法捕捉到的异常天气条件和人类活动对农田的影响,可以通过结合我们的 NSCam 网络进行补充。这种方法的成功实施突出表明,它有可能在全面农业研究中得到更广泛的应用,从而促进弹性和可持续的农业实践。
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Near surface camera informed agricultural land monitoring for climate smart agriculture

Continuous and accurate monitoring of agricultural landscapes is crucial for understanding crop phenology and responding to climatic and anthropogenic changes. However, the widely used optical satellite remote sensing is limited by revisit cycles and weather conditions, leading to gaps in agricultural monitoring. To address these limitations, we designed and deployed a Near Surface Camera (NSCam) Network across China, and explored its application in agricultural land monitoring and achieving climate-smart agriculture (CSA). By analyzing the image data captured by the NSCam Network, we can accurately assess long-term or abrupt agricultural land changes. According to the preliminary monitoring results, integrating NSCam data with remote sensing imagery greatly enhances the temporal details and accuracy of agricultural monitoring, aiding agricultural managers in making informed decisions. The impacts of abnormal weather conditions and human activities on agricultural land, which are not captured by remote sensing imagery, can be complemented by incorporating our NSCam Network. The successful implementation of this method underscores its potential for broader application in CSA, promoting resilient and sustainable agricultural practices.

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