Context

Microclimate (fine-scale temperature variability within metres of Earth’s surface) is highly influential on terrestrial organisms’ ability to survive and function. Understanding how such local climatic conditions vary is challenging to measure at adequate spatio-temporal resolution. Microclimate models provide the means to address this limitation, but require as inputs, measurements, or estimations of multiple environmental variables that describe vegetation and terrain variation.

Objectives

To describe the key components of microclimate models and their associated environmental parameters. To explore the potential of drones to provide scale relevant data to measure such environmental parameters.

Methods

We explain how drone-mounted sensors can provide relevant data in the context of alternative remote sensing products. We provide examples of how direct micro-meteorological measurements can be made with drones. We show how drone-derived data can be incorporated into 3-dimensional radiative transfer models, by providing a realistic representation of the landscape with which to model the interaction of solar energy with vegetation.

Results

We found that for some environmental parameters (i.e. topography and canopy height), data capture and processing techniques are already established, enabling the production of suitable data for microclimate models. For other parameters such as leaf size, techniques are still novel but show promise. For most parameters, combining spatial landscape characterization from drone data and ancillary data from lab and field studies will be a productive way to create inputs at relevant spatio-temporal scales.

Conclusions

Drones provide an exciting opportunity to quantify landscape structure and heterogeneity at fine resolution which are in turn scale-appropriate to deliver new microclimate insights.

中文翻译：

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无人机提供空间和体积数据，为微气候建模提供新见解

语境

小气候（地球表面几米内的小尺度温度变化）对陆地生物的生存和功能有很大的影响。要了解如何以适当的时空分辨率进行测量，要了解这种当地气候条件是如何变化的。小气候模型提供了解决这一局限性的方法，但需要作为描述植被和地形变化的多个环境变量的输入，测量或估计。

目标

描述小气候模型的关键组成部分及其相关的环境参数。探索无人机提供规模相关数据以测量此类环境参数的潜力。

方法

我们将解释安装在无人机上的传感器如何在替代遥感产品的背景下提供相关数据。我们提供了如何使用无人机直接进行微气象测量的示例。我们通过提供对地形的逼真的表示来模拟太阳能与植被之间的相互作用，展示如何将无人机衍生的数据纳入3维辐射传递模型。

结果

我们发现，对于某些环境参数（即地形和树冠高度），已经建立了数据捕获和处理技术，从而能够为微气候模型生成合适的数据。对于其他参数，例如叶片大小，技术仍然很新颖，但显示出希望。对于大多数参数，将无人机数据的空间景观特征与实验室和野外研究的辅助数据相结合，将是在相关时空尺度上创建输入的有效方式。

结论

无人机提供了一个激动人心的机会，可以以高分辨率对景观结构和异质性进行量化，而规模又适合于提供新的微气候见解。