草原植被盖度与物候智能监测系统研制  

Development of an intelligent monitoring system for vegetation coverage and phenology in grassland

作　　者：郑一力[1,2,3] 田真 关鹏 石红蕾 ZHENG Yili;TIAN Zhen;GUAN Peng;SHI Honglei(School of Technology,Beijing Forestry University,Beijing 100083,China;Key Laboratory of National Forestry and Grassland Administration on Forestry Equipment and Automation,Beijing 100083,China;State Key Laboratory of Efficient Production of Forest Resources,Beijing 100083,China)

机构地区：[1]北京林业大学工学院,北京100083 [2]林业装备与自动化国家林业和草原局重点实验室,北京100083 [3]林木资源高效生产全国重点实验室,北京100083

出　　处：《农业工程学报》2023年第18期162-171,共10页Transactions of the Chinese Society of Agricultural Engineering

基　　金：中央高校基本科研业务费专项资金资助(2021ZY74);江西省林业科技创新项目,创新专项([2022]38)。

摘　　要：针对目前草原植被盖度和物候期监测中存在的连续工作能力差、自动监测能力弱和精确度较低问题,将固定监测、移动监测和云平台结合,研制了一种草原植被盖度与物候智能监测系统。该系统主要由固定监测子系统、移动监测子系统以及草原物候智能监测云平台组成。固定监测子系统主要由物候相机、供电模块、通信模块、边缘计算控制器和支撑立杆等组成,移动监测子系统主要包括手持机和应用程序。草原物候智能监测云平台基于浏览器/服务器模式架构设计,具有信息查询、数据分析、数据显示和数据共享等功能。固定监测子系统和移动监测子系统可实现草原植被图像数据的采集和上传,然后通过云服务器部署的图像处理程序自动提取草原植被指数和植被盖度并存入数据库。在此基础上,通过拟合植被指数的时间序列获得植被生长曲线,并利用TIMESAT软件提取物候参数。经测试,提出的利用过绿指数(excess green index,EXG)结合最大类间方差法分割草原植被图像进而实现草原植被盖度识别的方法获得了90%的精确度,满足草原植被盖度自动化和批量化提取需求。并且,该研究在提取相对绿度指数(green chromatic coordinate,GCC)、EXG与归一化红绿差分指数(normalized green red difference index,NGRDI)植被指数的基础上,采用Double Logistic函数拟合的植被生长曲线可以准确反映植被生长周期。该系统为草原植被数智化监测和管理提供了可靠的技术和数据支撑。An intelligent monitoring system was developed to continuously,rapidly and accurately identify the grassland vegetation cover and the key phenological periods.The fixed monitoring,mobile monitoring and cloud platforms were also combined to provide a solution.The innovative system consisted of three main components:the fixed and mobile monitoring subsystem,as well as the cloud platform of grassland phenology intelligent monitoring.The fixed monitoring subsystem included various components,such as phenology cameras,power modules,communication modules,edge computing controllers,and supporting poles.The mobile monitoring subsystem consisted of handheld devices with capabilities,such as dustproof,waterproof,and shockproof,along with the necessary applications.The survey plot frames of the grassland field were required for the on-site image collection.The cloud-based grassland phenology intelligent monitoring platform was designed with a browser/server architecture,and then deployed on the Alibaba Cloud’s lightweight application server.As such,the platform was connected seamlessly to a MySQL database,with a user-friendly front-end built on the LayUI framework and a robust back-end using the Spring Boot framework.The efficient storage of collected images and periodic processing was obtained from the comprehensive data,such as the grassland vegetation index,vegetation cover,and phenological parameters.The cloud platform offered a wide range of functionalities,including data querying,processing,displaying,and sharing.Both the fixed and mobile monitoring subsystem were utilized to capture the grassland vegetation images.The fixed and mobile monitoring subsystem were operated and uploaded independently to the cloud platform using a cloud server.A series of processing steps were used to extract the regions of interest,and automatically calculate the grassland vegetation index using advanced techniques of image processing.The vegetation index was then converted into a grayscale space for the singlechannel grayscale image.Bi

关 键 词：图像处理 识别 植被盖度 物候期 植被指数 自动监测 草原 

分 类 号：S812.1[农业科学—草业科学]