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Hyperspectral Imaging and Precision Agriculture

Resonon's hyperspectral imaging systems are non-destructive remote sensing tools that deliver detailed reflectance data at each pixel in an image.

Because hyperspectral data contains much more information than traditional images, objects which appear very similar to the human eye can be distinguished with hyperspectral data analysis tools.

Resonon provides three hyperspectral imaging systems available for research in precision agriculture:

Seed viability study

corymbia reflectance hyperspectral imaging Nansen

Viable and nonviable seeds that appear identical to the human eye can be clearly distinguished using hyperspectral data.

This study is published in: C. Nansen, G. Zhao, N. Dakin, C Zhao, and S.R. Turner, J. Photochem. and Photobio. B 145 19 (2015).

Datacubes from this research are available for free download at Resonon's downloads page.

Click here for more details on Professor Nansen's seed viability study.

Ladybird precision agriculture robot

Resonon hyperspectral imaging camera precision agriculture robot

University of Sydney robotics expert Professor Salah Sukkarieh has been awarded Researcher of the Year for his work on the "Ladybird" robot.

The Ladybird robot employs many sensors, including a Resonon hyperspectral imaging camera.

Click here for more information on the Ladybird precision agriculture robot.

Hyperspectral vegetation indices: beyond NDVI

Calculating Hyperspectral Vegetation Indices with Spectronon
Screenshot of Spectronon

Hyperspectral vegetation indices (HVI's) are a common tool for analyzing hyperspectral data of agricultural crops.

HVI's have been correlated with Leaf Area Index, pigment concentration, canopy cover, leaf nitrogen, light use efficiency, growth rates, and other biochemical characteristics.

Resonon's Spectronon software makes it easy to create HVI maps from hyperspectral data.

Click here for more information on Hyperspectral Vegetation Indices.

Invasive weed mapping

Leafy spurge hyperspectral imaging

Using a Resonon airborne hyperspectral imaging system, an invasive weed infestation was identified and located.

This study is published in:S.C. Jay, R.L. Lawrence, K.S. Repasky, and L.J. Rew, Geoscience and Remote Sensing Symposium (IGARSS) 4374 (2010).

Click here for more details on hyperspectral weed mapping.