基于景感生态学的生态环境物联网框架构建
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中国科学院战略性先导科技专项(XDA23030103);国家自然科学基金(41571148)


Construction on the framework of ecological environment internet of things based on landsenses ecology
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The Strategic Priority Research Program (A) of the Chinese Academy of Sciences (XDA23030103); The National Natural Science Foundation of China ( 41571148)

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    摘要:

    更高的城市化率造成新的城市生态环境问题和变化趋势,新理论与新技术也为生态环境监测与管理提供了新方法。景感生态学是以可持续发展为目标,基于生态学的基本原理,从自然要素、物理感知、心理感知、社会经济、过程与风险等相关方面,研究土地利用规划、建设与管理的科学。基于景感生态学理论,开展生态环境物联网的监测网络设计与监测平台构建。首先,从自然要素中的光、热、水、土壤、综合气象等,以及物理感知的视觉、嗅觉、听觉、触觉等作为监测要素并进行特征分析;其次,结合多目标约束和聚类分析约束条件,提出非规则网格最优法进行生态环境监测网络的布设。再其次,重点探讨了联合地面固定监测站、无人船与无人机构建的"陆海空一体化"的生态环境数据采集与监测;其中,在地面构建综合气象与土壤传感器,可监测自然要素的光照、热量、雨量、气压,以及物理感知要素的风速、风向温度、湿度及噪声等;在海洋中,基于无人船搭载的水环境与水质传感器,可监测水体温度、水浑浊度与水污染状况,以及水体总磷与水体质量等;在空中,基于无人机搭载的气体监测仪、多/高光谱传感器与数码相机,可获取不同区域与不同高度的CO2、SO2、PM1.5、PM2.5、NO、O3等大气环境状况及粒子溶度与污染物扩散状况。最后,从全方位、多要素的数据获取、有线网络与无线网络相结合的数据传输、数据分类处理、数据智能控制,以及包含实时监测、预报预警、综合分析和平台管理的远程监控平台等五个模块来构建物联网监测平台。构建的生态环境物联网框架可实现生态环境全方位、全天候、多维度的远程实时监测与智能预警预报,为提升城市生态环境监测与管理提供支撑平台,增强了生态环境安全,满足人民日益增长的优美生态环境需要,提高了城市生态环境动态监测和智能管理的效益。

    Abstract:

    The higher urbanization rate causes new urban ecological environment problems and changing trends. The new ideas and technologies also provide new methods for ecological environment monitoring and management. Landscape ecology aims at sustainable development based on the basic principles of ecology. It researched the science of land use planning, construction and management from the aspects of natural elements, physical perception, psychological perception, social economy, process and risk, etc. Based on the concept of landscape ecology, this paper developed a monitoring network design and monitoring platform for the ecological environment Internet of things. Firstly, the characteristics of natural elements such as light, heat, water, soil, comprehensive meteorology and so on, as well as physical perception of vision, smell, hearing, touch and so on as the monitoring elements, we perform the feature analysis. Secondly, combined with the multi-objective constraints and clustering analysis constraints, an irregular grid optimal method is proposed to set up the ecological environment monitoring network. Then, the paper focuses on the collection and monitor of the ecological environment data of "land, sea and air integration" built by the combined ground fixed monitoring station, unmanned ship and unmanned organization. Among them, a comprehensively meteorological and soil sensor is built on the ground, which can monitor the light, heat, rainfall and air pressure of natural elements, as well as the wind speed, wind direction, temperature, humidity and noise of physical sensing elements. In the ocean, based on the water environment and water quality sensors carried by unmanned ships, water temperature, water turbidity and water pollution, as well as water environment and water quality can be monitored. In the air, the gas monitor, multispectral sensor and digital phase are based on Unmanned Aircraft Vehicle (UAV). The atmospheric environment conditions of CO2, SO2, PM1.5, PM2.5, NO, O3, particle solubility and pollutant diffusion in different regions and at different heights can be obtained. Finally, the Internet of things (IOT) monitoring platform is constructed from five modules, such as all-round and multi-factor data acquisition, data transmission combined with wired network and wireless network, data classification processing, intelligent control of data, and remote monitoring platform including real-time monitoring, forecast and early warning, integrated analysis and platform management. In this paper, the framework of the Internet of things can realize all-round, all-weather and multi-dimensional remote real-time monitoring and intelligent early warning and forecast of ecological environment, which provides the support to improve the urban ecological environmental monitoring and management platform, so as to enhance the ecological environment security, and meet the needs of the people's increasing beautiful ecological environment, as well as improve the urban ecological environment dynamic monitoring and intelligent management of benefits.

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郑渊茂,王业宁,周强,王豪伟.基于景感生态学的生态环境物联网框架构建.生态学报,2020,40(22):8093~8102

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