基于移动GIS的作物种植环境数据采集技术
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国家自然科学基金资助项目(31471762)


Mobile GIS Based Approach for Collection of Crop Planting Environment Data
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    摘要:

    野外数据采集具有灵活性强、采集内容多样、准确度高等优势,已成为补充完善农业数据的主要手段之一。作物种植环境数据采集工作存在指标多并随调查区域、作物类型与作物生育期不同而发生变化等特点,采用传统方式设计调查界面与录入模式难以满足数据采集的普适性需求。为此,在分析作物种植环境数据采集工作实际需求的基础上设计并实现了作物种植环境数据采集系统(CPEDCS)原型。一方面,系统针对作物种植环境指标的不确定性特征提出基于结构表的用户可定制种植环境数据录入模式,支持用户自定义录入界面;另一方面,系统集成移动GIS为野外采集工作提供空间信息支持,并可以动态适应空间数据类型、数量、范围的变化。研究的数据组织模型在陕西省杨凌区小麦种植环境野外调查的实际应用中,表现出良好的实用性与稳定性,一定程度上提高了采集工作效率,减少了数据录入出错率并能为调查人员提供空间信息辅助功能。

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    Field data collection, comparing with other data acquisition methods such as remote sensing or wireless sensor network, has advantages of high flexibility, high accuracy and gradually becoming one of the main methods for complementing agricultural data.We analyzed the actual demands of crop planting environment data collection work, and on that basis, presented an Android based crop planting environment data collecting system prototype (CPEDCS). Firstly, in consideration of uncertainty characteristics of crop planting environment indicators, we designed a customizable data input mode based on structural data table, which supports users to set indicators by editing XML file, defines visibility and arrangement of indicators, and configures default value of each indicator; secondly, mobile GIS module was integrated in CPEDCS client to provide spatial information, and the module can automatically adapt to variation of data type, file quantity and spatial range; thirdly, we realized efficient image data management and application by image data acquisition, compression, coding and transmission, and users can query image data in different sample points realtime through browser. At last, we applied our system on crop planting environment data collection work in Yangling District, Shanxi Province in April, 2013 and April, 2014. The experimental results show that the CPEDCS has high practicability and stability, and to some extent could increase data collecting efficiency, reduce error rate on data input, and provide spatial information for investigators.

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叶思菁,朱德海,姚晓闯,岳彦利,黄健熙,李 林.基于移动GIS的作物种植环境数据采集技术[J].农业机械学报,2015,46(9):325-334.

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  • 收稿日期:2015-01-26
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  • 在线发布日期: 2015-09-10
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