Data
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/808c370&rft.title=2024 Scott Teaching Trial&rft.identifier=RDM ID: a7ce28c9-329c-47d8-a503-ebe6707fabe6&rft.publisher=The University of Queensland&rft.description=This dataset contains multispectral imagery and derived geospatial products collected during a teaching trial conducted at The University of Queensland. The trial aimed to demonstrate UAV-based remote sensing techniques and data processing workflows for students in agricultural and environmental science courses. A DJI 3 Multispectral UAV was used to capture high-resolution imagery across multiple spectral bands, including blue, green, red, red-edge, and near-infrared. Data were collected under clear-sky conditions following a standard reflectance calibration procedure using field calibration panels. Post-processing was performed using Agisoft Metashape to generate orthomosaics and digital elevation models (DEMs). The dataset provides both the raw multispectral images and the derived geospatial products for educational and research use. This dataset serves as a resource for learning about UAV data acquisition, image calibration, orthomosaic generation, and vegetation index analysis.&rft.creator=Mr Chris James&rft.creator=Mr Chris James&rft.creator=Mr Daniel Smith&rft.creator=Mr Daniel Smith&rft.creator=Mr Edward MUGAMBA&rft.creator=Ms Carla Gho Brito&rft.creator=Professor Scott Chapman&rft.creator=Professor Scott Chapman&rft.date=2025&rft_rights= https://guides.library.uq.edu.au/deposit-your-data/license-reuse-data-agreement&rft_subject=eng&rft_subject=Agricultural biotechnology diagnostics (incl. biosensors)&rft_subject=Agricultural biotechnology&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=Non-genetically modified uses of biotechnology&rft_subject=Agricultural management of nutrients&rft_subject=Agriculture, land and farm management&rft_subject=Agricultural production systems simulation&rft_subject=Agricultural spatial analysis and modelling&rft_subject=Agro-ecosystem function and prediction&rft_subject=Crop and pasture production&rft_subject=Modelling and simulation&rft_subject=Artificial intelligence&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft.type=dataset&rft.language=English Access the data

Contact Information

[email protected]
School of Agriculture and Food Sustainability

Full description

This dataset contains multispectral imagery and derived geospatial products collected during a teaching trial conducted at The University of Queensland. The trial aimed to demonstrate UAV-based remote sensing techniques and data processing workflows for students in agricultural and environmental science courses. A DJI 3 Multispectral UAV was used to capture high-resolution imagery across multiple spectral bands, including blue, green, red, red-edge, and near-infrared. Data were collected under clear-sky conditions following a standard reflectance calibration procedure using field calibration panels. Post-processing was performed using Agisoft Metashape to generate orthomosaics and digital elevation models (DEMs). The dataset provides both the raw multispectral images and the derived geospatial products for educational and research use. This dataset serves as a resource for learning about UAV data acquisition, image calibration, orthomosaic generation, and vegetation index analysis.

Issued: 2025

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Other Information
Research Data Collections

local : UQ:289097

ror : https://ror.org/02zj7b759

Identifiers