Ecosynth - The Future of Remote Sensing for Forest Ecology

Ecosynth techniques are truly transforming the study of forest ecosystems and the field of remote sensing.  Our most recent Ecosynth publication in the journal Remote Sensing of Environment is available open-access thanks to support from the UMBC CUERE IGERT.

The paper covers a lot of ground, demonstrating the accuracy of Ecosynth canopy height measurements as compared to LIDAR and field based measurements (thanks field team!) at sites on the UMBC campus and SERC forest. Through repeated scans of the same forest at SERC throughout the growing season, Ecosynth revealed distinct changes in canopy color and structure that were closely related to airborne LIDAR, field inventories, and satellite vegetation index time series.

With Ecosynth, individual researchers can collect high resolution, 3D, multi-spectral point cloud datasets at research sites on demand.  When the US Government decided to make MODIS and Landsat data available for free to everyone, there was a huge surge in data use and research productivity.  Our hope is that with Ecosynth, 3D-spectral remote sensing is placed in the hands of individual field scientists, land managers, and citizen scientists, enabling ecological remote sensing research where people are working and not just where the data happens to have been collected. 

Dandois, J.P. and Erle C. Ellis (2013). High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision. Remote Sensing of Environment. 136, 259-276. DOI: 10.1016/j.rse.2013.04.005

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