Remote sensing of vegetation structure and composition
using computer vision
My research focuses on the development and use of a low-cost
remote sensing sytem comprised of off-the-shelf digital cameras,
hobbyist remote controlled aircraft and computer vision
software, Ecosynth,
for measuring tree and forest canopy 3D structure and
composition in fine spatial scale. I am interested in
understanding how forest canopies are meausured by a computer
vision structure from motion system and also in understanding
how we can use this new combination of existing technologies to
improve understanding of forest ecosystems, for example by
improving measurements of canopy leaf/plant area density or by
studying the relationship between canopy reflectance and
structure in 3D and at fine-spatial scale throughout the growing
season. My research is primarily based on the UMBC campus
in Baltimore MD, but I also study the forest at the
Smithsonian Environmental Research Center (SERC) in
Edgewater MD.
Publications
Dandois, J.P. and E.C. Ellis (2010). Remote Sensing of Vegetation Structure and Using Computer Vision.
Remote Sensing, 2(4): 1157-1176.
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