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森林前进:可视化和访问过去50年全球森林综合数据
E L Tejada-Gutiérrez1, J Mateo Fornés2, F Solsona2
1Department Ciències Mèdiques Bàsiques, Universitat de Lleida, Lleida 25198, Spain.
概括
森林管理需要综合生物多样性数据. 一个新的协议创建了一个全球数据仓库,使ForestForward平台能够进行生态系统分析和监测.
科学领域:
- 生态生态学 生态生态学
- 环境科学 环境科学
- 数据科学数据科学数据科学
背景情况:
- 可持续森林管理需要全面的生物多样性数据,但现有的数据集是分散的,缺乏标准化.
- 分析长期生态变化需要整合历史数据和采用大数据技术.
- 挑战包括统一多样化的数据集和管理大量的信息,以监测时间生态系统.
研究的目的:
- 为全球林业数据集开发和实施一个强大的数据集成协议.
- 为历史和当前的植物生物多样性信息创建一个集中式数据仓库.
- 构建一个用户友好的平台,用于访问,可视化和分析时间生态系统数据.
主要方法:
- 一个提取,转换和加载 (ETL) 协议被设计用于策划和整合4482个全球林业数据集.
- 使用Python脚本和NoSQL MongoDB数据库来自动化数据集成过程.
- 使用来自全球生物多样性信息设施的数据建立了一个包含超过1.72亿条记录的100GB数据仓库.
主要成果:
- 成功将4482个从18世纪开始的林业数据集集集成到一个统一的数据仓库中.
- 开发了ForestForward网络平台,这是一个使用Django框架构建的免费,用户友好的应用程序.
- 该平台允许用户探索,下载和可视化精选的生物多样性数据,观察时间生态系统的变化.
结论:
- 开发的ETL协议和数据仓库有效地解决了整合分散的生物多样性数据的挑战.
- 森林前进平台为研究人员和管理人员提供了一种有价值的工具,用于分析长期森林生态系统动态.
- 这种综合数据方法提高了可持续森林管理和生态系统弹性评估的能力.
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