Drone‐based structure‐from‐motion photogrammetry captures grassland sward height variability

Grasslands deliver a range of ecosystem services, including the provision of food and biodiversity, and regulation of soil carbon storage and hydrology. Monitoring schemes are needed to quantify spatial changes in these multiple functions alongside ecosystem degradation. Sward height is widely recognised as a key spatial variable in the provision of these services. Current manual monitoring approaches are labour intensive, and often fail to capture spatial patterns of important features, including sward height.
Proximal sensing from small aerial drones carrying lightweight cameras can be transformed into surface height models using image‐based structure‐from‐motion and Multi‐View Stereo‐based approaches; this presents a new opportunity for monitoring the spatial structure of grassland sward height. We combined aerial photographs with field survey data and an open‐source image‐based modelling‐processing workflow to generate sward height measurements for a field comprising mainly Lolium ...

草地生态系统可提供诸多生态系统服务功能，包括食物供给与生物多样性维持，以及土壤碳储量调控与水文调节。亟需建立监测方案，以量化这些多重生态功能随生态系统退化发生的空间变化。草层高度（sward height）被广泛认为是影响这些服务功能提供的关键空间变量。当前的人工监测方法不仅劳动强度大，且往往无法捕捉包括草层高度在内的重要特征的空间分布格局。搭载轻型相机的小型航拍无人机所获取的近距遥感数据，可通过基于图像的运动恢复结构（Structure from Motion, SfM）与多视图立体（Multi-View Stereo, MVS）方法转换为地表高度模型；这为监测草地草层高度的空间结构提供了全新机遇。本研究将航拍影像与野外调查数据、开源的基于图像的建模处理工作流相结合，针对一片以黑麦草属（Lolium）为主的地块生成了草层高度测量数据……