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FastMapping: Software to create field maps and identify management zones in precision agriculture

机译:快速映射:软件在精密农业中创建现场地图和身份管理区

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Diverse on-farm agronomic data, gathered via precision agriculture (PA), require depuration and joint analysis of multiple georeferenced field characteristics such as crop yields, and soil and topographic aspects. Multivariate analysis of spatial variability has been recommended to understand variation of data within fields and classify sites into zones of broad similarity to support crop management. However, most of the statistical techniques available for spatial data require advanced skills. Cleaning and statistical analysis of big spatial data can only be effectively implemented if there are easy-to-use computer programs integrating the analytical steps. This paper explains the development and implementation of FastMapping, an interactive web application to automatically clean PA raw data, generate spatial variability field maps, and delineate multivariate management zones. The application uses an interface developed in R language that automatically depurates datafiles; in addition, through automatic spatial interpolation of each variable, it allows us to merge data layers on the same spatial grid in such a way that each site within the agricultural field has values of all the measured variables. On this grid, FastMapping identifies homogeneous zones, in a multivariate and spatial way, and provides data reports including validation of the delineated zones. FastMapping outputs for zone delineation were compared with results from Management Zone Analyst (MZA) software in several fields. The new software yielded a similar zoning to that of MZA and added graphs and statistical results that are lacking in most PA software tools. The flexibility of FastMapping to import, clean and visualize PA data in a single computer environment is highly encouraging. FastMapping can be used by the PA community to support site-specific agricultural management.
机译:通过精密农业(PA)聚集的各种农场农艺数据需要剩余和联合分析多种地理导场特征,例如作物产量和土壤和地形方面。建议对空间变异性进行多变量分析,以了解字段内数据的变化,并将网站分类为广泛相似之处,以支持作物管理。但是,用于空间数据的大多数统计技术都需要高级技能。如果有易于使用的计算机程序集成分析步骤,则只能有效地实现对大空间数据的清洁和统计分析。本文介绍了快速绘制的开发和实现,交互式Web应用程序,以自动清洁PA原始数据,生成空间变异性字段映射和描绘多变量管理区域。该应用程序使用以R语言开发的接口,自动停止数据文件;另外,通过每个变量的自动空间插值,它允许我们在相同的空间网格上合并数据层,使得农业领域内的每个站点具有所有测量变量的值。在此网格上,FastMapping以多变量和空间方式识别均匀区域,并提供数据报告,包括验证划定区域。将区域描绘的快谱输出与几个字段中管理区分析师(MZA)软件的结果进行了比较。新软件产生了类似的分区,并在MZA的那种中添加了缺乏大多数PA软件工具的图表和统计结果。在单个计算机环境中,快速移动,清洁和可视化PA数据的灵活性很高。 PA社区可以使用FastMapping来支持特定于地的农业管理。

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