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论文推荐 | 面向气候智能农业的近地表相机信息农业土地监测

北京城市实验室BCL  · 公众号  ·  · 2024-08-12 10:30

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本期为大家推荐的内容为论文《 Near surface camera informed agricultural land monitoring for climate smart agriculture 》( 面向气候智能农业的近地表相机信息农业土地监测 ),发表在 Climate Smart Agriculture 期刊,欢迎大家学习与交流。


连续而准确地监测农业景观对于理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限于卫星的重访周期和天气条件,导致农业监测中出现空白。为了解决这些局限性,我们在中国部署了近地表摄像机(NSCam)网络,并探索其在农业土地监测和实现气候智能型农业(CSA)中的应用。通过分析NSCam网络捕获的图像数据,我们可以准确评估长期或突发的农业土地变化。根据初步监测结果,将NSCam数据与遥感影像相结合大大提高了农业监测的时间细节和准确性,帮助农业管理者做出明智的决策。通过整合我们的NSCam网络,可以弥补遥感影像未捕捉到的异常天气条件和人类活动对农业土地的影响。这种方法的成功实施凸显了其在更广泛的CSA应用中的潜力,促进了农业的韧性和可持续性实践。




论文相关

题目: Near surface camera informed agricultural land monitoring for climate smart agriculture

面向气候智能农业的近地表相机信息农业土地监测

作者: 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, Tingting Li, Zhentao Sun, Yonggan Zhao, Mengyang Fang, Dailiang Peng, Chaoyang Wu, Sheng Li, Xiaoli Shen, Keping Ma, Guanghui Lin, Yong Luo

发表刊物:

Climate Smart Agriculture

DOI:

https://doi.org/10.1016/j.csag.2024.100008



摘要 ABSTRACT

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.



论文展示(部分)


更多相关的研究工作详见BCL的 Active Urban Sensing 】单元链接:

https://www.beijingcitylab.com/projects-1/58-active-urban-sensing/

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