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Rapid Characterization of Vegetation Structure with a Microsoft Kinect Sensor
Department of Earth System Science, University of California Irvine, Irvine, CA 92697, USA
Open Perception, Inc., 68 Willow Road, Menlo Park, CA 94025, USA
* Author to whom correspondence should be addressed.
Received: 14 November 2012; in revised form: 26 December 2012 / Accepted: 31 January 2013 / Published: 11 February 2013
Abstract: The importance of vegetation structure and biomass in controlling land-atmosphere exchange is widely recognized, but measurements of canopy structure are challenging, time consuming, and often rely on destructive methods. The Microsoft Kinect is an infrared sensor designed for video gaming that outputs synchronized color and depth images and that has the potential to allow rapid characterization of vegetation structure. We compared depth images from a Kinect sensor with manual measurements of plant structure and size for two species growing in a California grassland. The depth images agreed well with the horizontal and vertical measurements of plant size made manually. Similarly, the plant volumes calculated with a three-dimensional convex hulls approach was well related to plant biomass. The Kinect showed some limitations for ecological observation associated with a short measurement range and daytime light contamination. Nonetheless, the Kinect’s light weight, fast acquisition time, low power requirement, and cost make it a promising tool for rapid field surveys of canopy structure, especially in small-statured vegetation.
Keywords: terrestrial ecology; field measurements; canopy structure; biomass; LIDAR; Microsoft Kinect; point clouds; depth images; convex hulls; concave hulls
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Cite This Article
MDPI and ACS Style
Azzari, G.; Goulden, M.L.; Rusu, R.B. Rapid Characterization of Vegetation Structure with a Microsoft Kinect Sensor. Sensors 2013, 13, 2384-2398.
Azzari G, Goulden ML, Rusu RB. Rapid Characterization of Vegetation Structure with a Microsoft Kinect Sensor. Sensors. 2013; 13(2):2384-2398.
Azzari, George; Goulden, Michael L.; Rusu, Radu B. 2013. "Rapid Characterization of Vegetation Structure with a Microsoft Kinect Sensor." Sensors 13, no. 2: 2384-2398.