High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision

Jonathan P. Dandois; Erle C. Ellis

doi:10.1016/j.rse.2013.04.005

Treesearch

High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision

Formally Refereed

Authors:

Jonathan P. Dandois, Erle C. Ellis

Year:

2013

Type:

Scientific Journal

Station:

Northern Research Station

DOI:

https://doi.org/10.1016/j.rse.2013.04.005

Source:

Remote Sensing of Environment. 136: 259-276.

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Abstract

High spatial resolution three-dimensional (3D) measurements of vegetation by remote sensing are advancing ecological research and environmental management. However, substantial economic and logistical costs limit this application, especially for observing phenological dynamics in ecosystem structure and spectral traits. Here we demonstrate a new aerial remote sensing system enabling routine and inexpensive aerial 3D measurements of canopy structure and spectral attributes, with properties similar to those of LIDAR, but with RGB (red-green-blue) spectral attributes for each point, enabling high frequency observations within a single growing season. This "Ecosynth" methodology applies photogrammetric "Structure from Motion" computer vision algorithms to large sets of highly overlapping low altitude (

Keywords

Canopy structure, Canopy phenology, Forest structure, Forestry, Forest ecology, Computer vision, Unmanned aerial systems, UAS, Unmanned aerial vehicle, UAV, Forest biomass, Forest carbon, Phenology, Forest monitoring, Tree height, Canopy height

Citation

Dandois, Jonathan P.; Ellis, Erle C. 2013. High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision. Remote Sensing of Environment. 136: 259-276.