Ecosynth research focuses on improving understanding of terrestrial ecosystems based on 3D-multispectral remote sensing.   To date, research has been focused on tool and method development, but now Ecosynth techniques can begin to be applied to answer research questions by others at their own field sites.  Information for applying Ecosynth techniques in your research can be found throughout the site, including code( and wiki-based instructions (  You can also access several Ecosynth datasets ( for your own testing.  Our papers are available open-access and all of our content is licensed under a Creative Commons Attribution 4.0 International License.


Dandois, J., M. Olano, and E. C. Ellis. 2015. Optimal Altitude, Overlap, and Weather Conditions for Computer Vision UAV Estimates of Forest Structure. Remote Sensing 7:13895-13920. [download]

Dandois, J.P., Boswell, D., Anderson, E., Bofto, A., Baker, M., & Ellis, E.C. (2015). Forest census and map data for two Temperate Deciduous forest edge woodlot patches in Baltimore MD, USA. Ecology, 96:6, 1734. [download] [blog post]

Zahawi, R.A., Dandois, J.P., Holl, K.D., Nadwodny, D., Reid, J.L., & Ellis, E.C. (2015). Using lightweight unmanned aerial vehicles to monitor tropical forest recovery. Biological Conservation, 186, 287-295. [download] [blog post]

Dandois, J. P. and E. C. Ellis. 2013. High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision. Remote Sensing of Environment 136:259-276. [download] [blog post]

Dandois, J. P. and E. C. Ellis. 2010. Remote sensing of vegetation structure using computer vision. Remote Sensing 2(4):1157-1176. [download]


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