UAV Remote Sensing Imagery of Miscanthus — 2020

Themes: Feedstock Production

Keywords: Biomass Analytics, Remote Sensing


Varela Quintela, S.Leakey, A.D.B., Sacks, E. October 10, 2022. “UAV remote sensing imagery — Miscanthus trials 2020 — Energy Farm — UIUC.” University of Illinois Urbana-Champaign. DOI: 10.13012/B2IDB-5689586_V1.


(a) Aerial overview of Miscanthus sacchariflorus (top) and Miscanthus sinensis (bottom) trials and plots analyzed in this study (in yellow) located at the University of Illinois Energy Farm. (b) Close-up images of plots and individual plants under intensive growth during the summer of 2020 (top, M. sacchariflorus; bottom, M. sinensis).

Aerial imagery utilized as input in the manuscript “Deep Convolutional Neural Networks Exploit High-Spatial- and -Temporal-Resolution Aerial Imagery to Predict Key Traits in Miscanthus.” Data was collected over Miscanthus sacchariflorus (Msa) and Miscanthus sinensis (Msi) breeding trials at the University of Illinois Energy Farm in 2020. Flights were performed using a DJI M600 mounted with a Micasense Rededge multispectral sensor at 20 m altitude around solar noon. Imagery is available as tif file by field trial and date (10). The post-processing of raw images into orthophoto was performed in Agisoft Metashape software. Each crop surface model and multispectral orthophoto was stacked into a unique raster stack by date and uploaded here. Each raster stack includes 6 layers in the following order: Layer 1 = crop surface model, Layer 2 = Blue, Layer 3 = Green, Layer 4 = Red, Layer 5 = Rededge, and Layer 6 = NIR multispectral bands. Msa raster stacks were resampled to 1.67 cm spatial resolution and Msi raster stacks were resampled to 1.41 cm spatial resolution to ease their integration into further analysis. ‘MMDDYYYY’ is the date of data collection, ‘MSA’ is M. Sacchariflorus trial, ‘MSI’ is Miscanthus Sinensis trial, ‘CSM’ is crop surface model layer, and ‘MULTSP’ are the five multispectral bands.


Aerial Imagery

Data Download (3.5 KB) includes:

  • Data collection timing
  • Approach description
  • CNN model description

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