Applied aerial spectroscopy: A case study on remote sensing of an ancient and semi-natural woodland

An area of ancient and semi-natural woodland (ASNW) has been investigated by applied aerial spectroscopy using an unmanned aerial vehicle (UAV) with multispectral image (MSI) camera. A novel normalised difference spectral index (NDSI) algorithm was developed using principal component analysis (PCA)....

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Bibliographic Details
Published in:PloS one 2021-11, Vol.16 (11), p.e0260056-e0260056
Main Authors: Ahmed, Shara, Nicholson, Catherine E, Muto, Paul, Perry, Justin J, Dean, John R
Format: Article
Language:English
Subjects:
Aircraft
Algorithms
Biology and Life Sciences
Birch trees
Cameras
Case reports
Conservation of Natural Resources
Coppice forests
Dead wood
Drone aircraft
Engineering and Technology
England
Environmental aspects
Forests
Ground level
Image segmentation
Indigenous species
Methods
Oak
Observations
Personal computers
Physical Sciences
Plant species
Principal Component Analysis
Principal components analysis
Regeneration
Remote sensing
Remote Sensing Technology - instrumentation
Research and Analysis Methods
Satellites
Spectroscopy
Spectrum analysis
Spectrum Analysis - instrumentation
Trees
Trees - classification
Unmanned Aerial Devices
Unmanned aerial vehicles
Woodlands
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Summary:An area of ancient and semi-natural woodland (ASNW) has been investigated by applied aerial spectroscopy using an unmanned aerial vehicle (UAV) with multispectral image (MSI) camera. A novel normalised difference spectral index (NDSI) algorithm was developed using principal component analysis (PCA). This novel NDSI was then combined with a simple segmentation method of thresholding and applied for the identification of native tree species as well as the overall health of the woodland. Using this new approach allowed the identification of trees at canopy level, across 7.4 hectares (73,934 m2) of ASNW, as oak (53%), silver birch (37%), empty space (9%) and dead trees (1%). This UAV derived data was corroborated, for its accuracy, by a statistically valid ground-level field study that identified oak (47%), silver birch (46%) and dead trees (7.4%). This simple innovative approach, using a low-cost multirotor UAV with MSI camera, is both rapid to deploy, was flown around 100 m above ground level, provides useable high resolution (5.3 cm / pixel) data within 22 mins that can be interrogated using readily available PC-based software to identify tree species. In addition, it provides an overall oversight of woodland health and has the potential to inform a future woodland regeneration strategy.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0260056