美国多部门的土地利用和土地覆盖基础地图,以支持人类和地球系统模型
Jay Oliver1, Ryan A McManamay2
1Department of Environmental Science, Baylor University, Waco, TX, 76798, USA.
Scientific data
|March 20, 2025
概括
我们为美国开发了一个新的土地利用和土地覆盖系统,以改善地球系统模型. 这种一致的系统可以减少结合不同土地数据产品 (如LUH2和CLM) 的错误.
科学领域:
- 地球系统科学 地球系统科学
- 土地使用和土地覆盖变化 (LULC) 分析分析.
- 地理空间数据协调协调工作
背景情况:
- 地球系统模型 (ESM) 依赖于准确的土地利用和土地覆盖变化 (LULC) 预测,以模拟土地-大气相互作用和生物地球化学循环.
- 现有的LULC产品,如社区土地模型 (CLM) 和土地利用协调 2 (LUH2) 被广泛使用,但当与多部门动态 (MSD) 模型,如全球变化分析模型 (GCAM) 整合时,由于主题和解决方案不一致,会带来挑战.
- 协调不同的LULC数据引入不确定性和错误传播,特别是在需要更细微的空间尺度的区域研究中.
研究的目的:
- 为相邻的美国开发一个主题上一致的LULC系统.
- 创建一个灵活的系统,适应多个MSD框架,包括LUH2,CLM和GCAM.
- 通过减少LULC数据集成的不确定性来支持区域一级的研究.
主要方法:
- 开发了一个新的,主题上一致的LULC系统,使用经验上衍生出的空间产品用于相对边界的美国.
- 创建了一系列高分辨率 (30米) 的基底地图,用于多个当代年.
- 确保了LUH2,CLM和GCAM分类系统之间的灵活性和可互换性.
主要成果:
- 已经建立了一个主题一致的LULC系统,用于与美国相邻的美国.
- 现在可以使用多年的高分辨率 (30米) 基底地图.
- 该系统促进了无集成,并在不同模型 (LUH2,CLM,GCAM) 中使用LULC数据时减少了不确定性.
结论:
- 开发的LULC系统有效地解决了主题不一致性,并改善了区域研究的数据集成.
- 这一进步通过提供协调和灵活的LULC数据基础,支持在地球系统模型中进行更准确的模拟.
- 该系统通过在各种建模框架中灵活使用LULC数据来增强研究能力.
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