星-地协同多源遥感作物参量感知与长势农学辨识机理研究

Crop growth includes both group size and physiological activity information. Currently, when accessing the dynamic information of crop growth in wide range, either terrestrial wireless sensing technology or remote sensing technology has its own advantages and limitations. Furthermore, crop monitoring results could not always provide the specific status information that including the crop group size and physiological activity etc., which limited the recognition accuracy and practical value of crop monitoring. In this project, based on a large-scale comprehensive scientific experiments, winter wheat was chosen to study: (1) the high-tech wireless sensing mechanism and method of crop biochemical parameters, and then to conduct a multi-sensor integrated ground system for crop information collection; (2) to establish a spatial distribution optimization method based on the synergy observation of the ground wireless sensor and multi-source remote sensing; (3) to explore a theory and method that could effectively collaborate the multi-source remote sensing data and ground-sensing information and then to carry out collaborative analysis on the crop parameters; (4) to establish a new crop monitoring method that could be able to clarify both the information of crop population size and physiological activity. The results will benefit to improve the recognition ability of crop growth ststus in complex farmlands, and provide a scientific basis for the development of appropriate field management protocols and guide for precision implementation. Therefore, it is meaningful to improve the utilization efficiency of agricultural resources in a wide range, to enhance the agricultural informatization level in China, to protect agriculture ecological safety and to improve crop quality.

作物长势包括群体大小和生理活性两方面信息。目前，地面无线传感与遥感技术在获取大范围作物长势动态时均具有自身的优势和局限性。通常作物长势监测结果不能提供作物群体大小和生理活性等具体状况信息，限制了其辨识精度和实际应用价值。本项目以冬小麦为研究对象，基于大型综合科学实验，拟研究：(1) 作物生化参数高新无线传感机理与方法，构建作物信息多元传感器集成地面观测系统；（2）建立地面无线传感与多源遥感协同观测的空间布局优化方法；（3）探索有效协同多源遥感数据与地面传感信息的理论和方法，开展作物长势相关参量的协同解析方法研究；（4）建立能够同时明确作物群体大小和生理活性高低信息的新型作物长势监测方法。研究结果将有助于提高复杂农田作物长势的解析和辨识能力，为制订田间适宜管理措施与指导精准作业实施提供科学依据，对大范围提高我国农业资源利用效率、提升农业信息化水平、保障农业生态安全及改善作物品质具有重要意义。

作物长势包括群体大小和生理活性两方面信息。目前，地面无线传感与遥感技术在获取大范围作物长势动态时均具有自身的优势和局限性。通常作物长势监测结果不能提供作物群体大小和生理活性等具体状况信息，限制了其辨识精度和实际应用价值。本项目根据研究计划，基于冬小麦综合观测实验，主要开展了以下研究：(1)开展了小区控制实验和大田区域实验，采集了一套本项目研究所需要的地面-无人机-卫星实验数据；（2）研发了一种作物长势多元参量集成观测地面传感装置，针对该装置开发了移动终端数据采集和管理app软件和服务器端综合性的数据获取、管理及分析平台；（3）分析确定了协同遥感观测的地面空间采样优化布局方法；（4）构建了地面-无人机-卫星多源作物长势参量解析模型；（5）构建了综合作物群体和生理活性信息的作物长势辨识模型。在本项目的资助下，目前已发表学术论文27篇，其中17篇SCI，5篇EI，5篇CSCD；授权发明专利2项；授权软件著作权2项；北京市新技术新产品（服务）证书1项；培养博士后1名，培养研究生3名，完成了项目研究内容和目标，取得了预期研究成果。