Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
5
datasets available to search
ShareScore release 0.9.0
Dataset results
5 results for “Structure from Motion Photogrammetry”
Monitoring creep along the Hayward Fault using structure-from-motion photogrammetry of offset curbs"
<p>Point clouds for each observed offset curbs along the Hayward Fault in Fremont, California between 2016 to 2018. </p>
Data from: Structure from motion photogrammetry: does the choice of software matter for Ecology?
Structure-from-Motion (SfM) and Multiview-Stereo (MVS) is emerging as a flexible, self-service, remote sensing tool for generating fine-grained digital surface models (DSMs) in the Earth sciences and ecology. However, drone-based SfM+MVS applications have developed at a rapid pace over the past decade and there are now many software options available for data processing. Consequently, understanding of reproducibility issues caused by variations in software choice and their influence on data quality is relatively poorly understood. This understanding is crucial for the development of SfM+MVS if it is to fulfil a role as a new quantitative remote sensing tool to inform management frameworks and species conservation schemes. To address this knowledge gap, a lightweight multirotor drone carrying a Ricoh GR II consumer-grade camera was used to capture replicate, centimetre-resolution image datasets of a temperate, intensively managed grassland ecosystem. These data allowed the exploration of method reproducibility and the impact of SfM+MVS software choice on derived vegetation canopy height measurement accuracy. The quality of DSM height measurements derived from four different, yet widely used SfM-MVS software – Photoscan, Pix4D, 3DFlow Zephyr and MICMAC, were compared with in-situ sward height data captured on the same day as image capture. Using the same replicate image dataset (n=3) as input we demonstrate that there are 1.7, 2.0 and 2.5 cm differences in RMSE (excluding one outlier) between the outputs from different SfM+MVS software using "High", "Medium" and "Low" quality settings, respectively. Furthermore, we show that there can be a significant difference, although of small overall magnitude between replicate image datasets (n=3) processed using the same SfM+MVS software, following the same workflow, with a variance in RMSE of up to 1.3, 1.5 and 2.7 cm (excluding one outlier) for "High", "Medium" and "Low" quality settings, respectively. We conclude that SfM+MVS software choice does matter.
Data from: 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 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.
Data from: Drone‐based structure‐from‐motion photogrammetry captures grassland sward height variability
Open the record for dataset details and reuse information.
Data from: Structure from motion photogrammetry: does the choice of software matter for Ecology?
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.