DOI: 10.5061/dryad.2q8m903
title: Data from: Drone‐based structure‐from‐motion photogrammetry captures grassland sward height variability

description: 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
 perenne (perennial ryegrass) and Trifolium pratense (red clover). We
 compared the derived measurements with in situ data captured on the same
 day using traditional agronomic sward height techniques to determine the
 quality of the drone‐derived surface model product for sward
 characterisation. The SfM and Multi‐View Stereo‐based surface model had a
 mean absolute sward height measurement error of between 3.7 and 4.2 cm. To
 produce field observations with equivalent quality would require up to 550
 sward height measurements for the study site (area: 8,059 m2), which is
 not feasible over larger extents required for conservation of key species
 or agronomic purposes. Synthesis and applications. We demonstrate how the
 collection of precise and detailed information on the spatial structure of
 grasslands can be made over management‐relevant extents. Aerial digital
 photographs can be transformed into surface models using an image‐based
 modelling approach: structure‐from‐motion and Multi‐View Stereo
 techniques. Image‐based measurements of sward heights were compared with
 manual sward height data captured on the same day. This novel source of
 vegetation spatial information could improve sward management for
 conservation and agronomy applications. The approach supports frequent
 surveys, at user‐controlled revisit times, and delivers data for spatial
 monitoring of key grassland functions and services.
description: First Image
 DatasetFirst replicate image
 dataset (50 images). Includes also 1) UAV flight log (can be viewed with
 the software MissionPlanner), 2) CSV file detailing image coordinates and
 attitude and 3) xml files containing A) ground control point information,
 B) image coordinates (image number and where in image a given ground
 control point can be seen).FirstImageDatasetJAPPL.zipRadial Extended MICMAC First Image DatasetSfM+MVS point cloud generated from the first replicate image dataset.FirRadExtFgeeSR.plySecond Image DatasetSecond replicate image dataset (50 images). Includes also 1) UAV flight log (can be viewed with the software MissionPlanner), 2) CSV file detailing image coordinates and attitude and 3) xml files containing A) ground control point information, B) image coordinates (image number and where in image a given ground control point can be seen).SecondImageDatasetJAPPL.zipRadial Extended MICMAC Second Image DatasetSfM+MVS point cloud generated from the second replicate image dataset.secRadExtFgee.plyThird Image DatasetThird replicate image dataset (50 images). Includes also 1) UAV flight log (can be viewed with the software MissionPlanner), 2) CSV file detailing image coordinates and attitude and 3) xml files containing A) ground control point information, B) image coordinates (image number and where in image a given ground control point can be seen).ThirdImageDatasetJAPPL.zipRadial Extended MICMAC Third Image DatasetSfM+MVS point cloud generated from the third replicate image dataset.ThiRadExtFgee.plySward height correlation plotsEstimated sward height (SfM+MVS-based pipeline) compared to in-situ measurments of sward height using traditional agronomic techniques. These figures are the basis for the section COMPARISON OF MULTIPLE METHODS.SwHCorrelationZip.zipRelevant CSV filesIncludes e.g. DSM as generated from SfM+MVS-based pipeline, validation DSM, validation DTM.TubbonHillCSV.zip