We have moved! Please visit us at ANTHROECOLOGY.ORG. This website is for archival purposes only.

We have moved! Please visit us at ANTHROECOLOGY.ORG. This website is for archival purposes only.


Ecosynth: 3D Tools for Ecology

3D point cloud of a forest on the UMBC campus (Dandois & Ellis 2010)
The Ecosynth Project develops low-cost user-deployed open-source tools for scanning ecosystems in 3D from sets of digital photographs acquired using light-weight aerial platforms or from the ground.

For more information:

Join the Ecosynth Community

Visit the Ecosynth Wiki

Meet the Ecosynth Team @UMBC

More about the UMBC Forest Research Plots

The Ecosynth project is supported by a grant from NSF's Advances in Bioinformatics Program (2012).  The project began in Spring 2009 with support from the USFS and the UMBC CUERE IGERT.


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]

Zahawi, R., J.P. Dandois, K.D. Holl, D. Nadwodny, L.J. Reid, and E.C. Ellis. 2015. Using lightweight unmanned aerial vehicles to monitor tropical forest recovery. Biological Conservation 186:287–295. [download]

Dandois, J.P., D. Nadwodny, E. Anderson, A. Bofto, M. Baker, and E.C. Ellis. 2015. Forest census and map data for two temperate deciduous forest edge woodlot patches in Baltimore, Maryland, USA. Ecology 96:1734-1734. [download] [download dataset]

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(10): 13895-13920. [download]

Dandois, J. P., M. Baker, M. Olano, G. G. Parker, and E. C. Ellis. 2017. What is the point? Evaluating the structure, color, and semantic traits of computer vision point clouds of vegetation. Remote Sensing 9:355. [download]


Funders & Support
This material is based upon work supported by the National Science Foundation under Grant DBI 1147089 awarded March 1, 2012. Initial and continuing support provided by the USDA Forest Service joint venture agreement 06-JV-11242300-135. Graduate student support by NSF IGERT 054969 to UMBC CUERE, undergraduate student support from the Baltimore Ecosystem Study DEB-0423476. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Please contact Erle Ellis for more information.