3D-imaging technologies provide measurements of terrestrial and aquatic ecosystems’ structure, key for biodiversity studies. However, the practical use of these observations globally faces practical challenges. First, available 3D data are geographically biased, with significant gaps in the tropics. Second, no data source provides, by itself, global coverage at a suitable temporal recurrence. Thus, global monitoring initiatives, such as assessment of essential biodiversity variables (EBVs), will necessarily have to involve the combination of disparate data sets. We propose a standardized framework of ecosystem morphological traits – height, cover, and structural complexity – that could enable monitoring of globally consistent EBVs at regional scales, by flexibly integrating different information sources – satellites, aircrafts, drones, or ground data – allowing global biodiversity targets relating to ecosystem structure to be monitored and regularly reported.

3D成像技术可以测量陆地和水生生态系统的结构，这是生物多样性研究的关键。但是，在全球范围内实际使用这些意见面临着实际挑战。首先，可用的3D数据在地理上存在偏见，在热带地区存在明显差距。其次，没有任何数据源以适当的时间递归本身提供全局覆盖。因此，诸如基本生物多样性变量（EBV）评估之类的全球监测计划必定必须包含不同数据集的组合。我们提出了一个生态系统形态特征（高度，覆盖度和结构复杂性）的标准化框架，该框架可以通过灵活集成不同的信息源（卫星，飞机，无人机，