Logan Gall, Tom Glancy, Michael Kantar, Bryan C. Runck
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引用次数: 0
摘要
农业气象数据对于利用数字农业技术了解生产情况至关重要。然而,整合多个来源的农业气象观测数据仍是一项挑战。数字农业科学家通常要多次下载和清理相同的数据集。我们提出了一个原型系统,通过提供简化的用户界面、数据库和应用程序接口,简化了从气象数据源收集、清理、整合和汇总数据的过程。原型系统提供了查询多种地理空间格式(栅格和矢量)的标准接口,并整合了观测网络,包括美国国家海洋和大气管理局全球历史气候学网络(NOAA GHCN)、NOAA NClim-Grid(NOAA 的网格气候标准)和 Ameriflux BASE。该系统可自动检查和更新数据,节省存储空间和处理时间,并允许用户对数据进行空间和时间汇总。该应用和集成系统以开放源代码和基于浏览器的用户界面提供,可在 Windows、Linux 和 Mac 环境中运行,支持更广泛地使用多源农业气象数据。
A tool for integrating agrometeorological observation data for digital agriculture: A Minnesota case study
Agrometeorological data are essential for understanding production using digital agriculture techniques. However, integrating agrometerological observations from multiple sources remains a challenge. Often, digital agriculture scientists download and clean the same datasets many times. We present a prototype system that simplifies the process of collecting, cleaning, integrating, and aggregating data from meteorological data sources by providing a simplified user interface, database, and application programming interface. The prototype provides a standard interface for querying multiple geospatial formats (raster and vector) and integrates observation networks including the National Oceanic and Atmospheric Administration Global Historical Climatology Network (NOAA GHCN), NOAA NClim-Grid (NOAA's Gridded Climate Normals), and Ameriflux BASE. The system automatically checks and updates data, saving storage space and processing time, and allows users to summarize data spatially and temporally. Provided as open source code and browser-based user interface, the application and integration system can be run across Windows, Linux, and Mac environments to support broader use of multi-source agrometeorology data.