Next Article in Journal
Previous Article in Journal
Sensors 2013, 13(2), 2384-2398; doi:10.3390/s130202384
Article

Rapid Characterization of Vegetation Structure with a Microsoft Kinect Sensor

1,* , 1
 and 2
Received: 14 November 2012; in revised form: 26 December 2012 / Accepted: 31 January 2013 / Published: 11 February 2013
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [6753 KB, uploaded 21 June 2014]   |   Browse Figures
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 terrestrial ecology; field measurements; canopy structure; biomass; LIDAR; Microsoft Kinect; point clouds; depth images; convex hulls; concave hulls
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


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.

AMA Style

Azzari G, Goulden ML, Rusu RB. Rapid Characterization of Vegetation Structure with a Microsoft Kinect Sensor. Sensors. 2013; 13(2):2384-2398.

Chicago/Turabian Style

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.



Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert