The Ecosynth project was completed September 30, 2018.

The Ecosynth Project developed low-cost user-deployed open-source tools for scanning ecosystems in 3D from sets of digital photographs acquired using light-weight aerial platforms and from the ground.

Open source software was developed and released for both aerial and ground-based 3D reconstructions using computer vision.

The Ecosynth community website on Ning was a hub for collaborations for more than 350 early drone and computer vision ecologists from 2012 to 2018. The site closed in August 2019.

Ecosynth developed the first high temporal resolution multispectral imaging of forest canopies in 3D.

An interactive online 3D forestry viewer and inventory system was developed

An international forest research plot was developed on the UMBC Campus

Ecosynth 3D datasets are shared online

Related Publications

Dandois, Jonathan P.; Baker, Matthew; Olano, Marc; Parker, Geoffrey G.; Ellis, Erle C.. 2017. What is the point? Evaluating the structure, color, and semantic traits of computer vision point clouds of vegetation. Remote Sensing 9(4): 355. [Download PDF]
Dandois, Jonathan; Olano, Marc; Ellis, Erle C.. 2015. Optimal Altitude, Overlap, and Weather Conditions for Computer Vision UAV Estimates of Forest Structure. Remote Sensing 7(10): 13895-13920. [Download PDF]
Dandois, Jonathan P.; Nadwodny, Dana; Anderson, Erik; Bofto, Andrew; Baker, Matthew; Ellis, Erle C.. 2015. Forest census and map data for two temperate deciduous forest edge woodlot patches in Baltimore, Maryland, USA. Ecology 96(6): 1734-1734. [Download PDF]
Zahawi, Rakan; Dandois, Jonathan P.; Holl, Karen D.; Nadwodny, Dana; Reid, Leighton J.; Ellis, Erle C.. 2015. Using lightweight unmanned aerial vehicles to monitor tropical forest recovery. Biological Conservation 186: 287–295. [Download PDF]
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. [Download PDF]
Dandois, Jonathan P.; Ellis, Erle C.. 2010. Remote sensing of vegetation structure using computer vision. Remote Sensing 2: 1157-1176. [Download PDF]
Goddard, M. A.; Z. G. Davies; S. Guenat; M. J. Ferguson; J. C. Fisher; A. Akanni; T. Ahjokoski; P. M. L. Anderson; F. Angeoletto; C. Antoniou; A. J. Bates; A. Barkwith; A. Berland; C. J. Bouch; C. C. Rega-Brodsky; L. B. Byrne; D. Cameron; R. Canavan; T. Chapman; S. Connop; S. Crossland; M. C. Dade; D. A. Dawson; C. Dobbs; C. T. Downs; E. C. Ellis; F. J. Escobedo; P. Gobster; N. M. Gulsrud; B. Guneralp; A. K. Hahs; J. D. Hale; C. Hassall; M. Hedblom; D. F. Hochuli; T. Inkinen; I.-C. Ioja; D. Kendal; T. Knowland; I. Kowarik; S. J. Langdale; S. B. Lerman; I. MacGregor-Fors; P. Manning; P. Massini; S. McLean; D. D. Mkwambisi; A. Ossola; G. P. Luque; L. Pérez-Urrestarazu; K. Perini; G. Perry; T. J. Pett; K. E. Plummer; R. A. Radji; U. Roll; S. G. Potts; H. Rumble; J. P. Sadler; S. de Saille; S. Sautter; C. E. Scott; A. Shwartz; T. Smith; R. P. H. Snep; C. D. Soulsbury; M. C. Stanley; T. Van de Voorde; S. J. Venn; P. H. Warren; C.-L. Washbourne; M. Whitling; N. S. G. Williams; J. Yang; K. Yeshitela; K. P. Yocom; Dallimer, M.. 2021. A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems. Nature Ecology & Evolution 5: 219-230. [Download PDF]
Davies, S. J.; I. Abiem; K. Abu Salim; S. Aguilar; D. Allen; A. Alonso; K. Anderson-Teixeira; A. Andrade; G. Arellano; P. S. Ashton; P. J. Baker; M. E. Baker; J. L. Baltzer; Y. Basset; P. Bissiengou; S. Bohlman; N. A. Bourg; W. Y. Brockelman; S. Bunyavejchewin; D. F. R. P. Burslem; M. Cao; D. Cárdenas; L.-W. Chang; C.-H. Chang-Yang; K.-J. Chao; W.-C. Chao; H. Chapman; Y.-Y. Chen; R. A. Chisholm; C. Chu; G. Chuyong; K. Clay; L. S. Comita; R. Condit; S. Cordell; H. S. Dattaraja; A. A. de Oliveira; J. den Ouden; M. Detto; C. Dick; X. Du; Á. Duque; S. Ediriweera; E. C. Ellis; N. L. E. Obiang; S. Esufali; C. E. N. Ewango; E. S. Fernando; J. Filip; G. A. Fischer; R. Foster; T. Giambelluca; C. Giardina; G. S. Gilbert; E. Gonzalez-Akre; I. A. U. N. Gunatilleke; C. V. S. Gunatilleke; Z. Hao; B. C. H. Hau; F. He; H. Ni; R. W. Howe; S. P. Hubbell; A. Huth; F. Inman-Narahari; A. Itoh; D. Janík; P. A. Jansen; M. Jiang; D. J. Johnson; F. A. Jones; M. Kanzaki; D. Kenfack; S. Kiratiprayoon; K. Král; L. Krizel; S. Lao; A. J. Larson; Y. Li; X. Li; C. M. Litton; Y. Liu; S. Liu; S. K. Y. Lum; M. S. Luskin; J. A. Lutz; H. T. Luu; K. Ma; J.-R. Makana; Y. Malhi; A. Martin; C. McCarthy; S. M. McMahon; W. J. McShea; H. Memiaghe; X. Mi; D. Mitre; M. Mohamad; L. Monks; H. C. Muller-Landau; P. M. Musili; J. A. Myers; A. Nathalang; K. M. Ngo; N. Norden; V. Novotny; M. J. O'Brien; D. Orwig; R. Ostertag; K. Papathanassiou; G. G. Parker; R. Pérez; I. Perfecto; R. P. Phillips; N. Pongpattananurak; H. Pretzsch; H. Ren; G. Reynolds; L. J. Rodriguez; S. E. Russo; L. Sack; W. Sang; J. Shue; A. Singh; G.-Z. M. Song; R. Sukumar; I. F. Sun; H. S. Suresh; N. G. Swenson; S. Tan; S. C. Thomas; D. Thomas; J. Thompson; B. L. Turner; A. Uowolo; M. Uriarte; R. Valencia; J. Vandermeer; A. Vicentini; M. Visser; T. Vrska; X. Wang; X. Wang; G. D. Weiblen; T. J. S. Whitfeld; A. Wolf; S. J. Wright; H. Xu; T. L. Yao; S. L. Yap; W. Ye; M. Yu; M. Zhang; D. Zhu; L. Zhu; J. K. Zimmerman; D. Zuleta. . 2021. ForestGEO: Understanding forest diversity and dynamics through a global observatory network. Biological Conservation 253: 108907. [Download PDF]

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Erle C. Ellis

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