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Forests 2015, 6(4), 1179-1194; doi:10.3390/f6041179

Evaluation of a Smartphone App for Forest Sample Plot Measurements

1
Department of Forest Sciences, University of Helsinki, P.O. Box 27, Helsinki FI-00014, Finland
2
Centre of Excellence in Laser Scanning Research, National Land Survey of Finland/Finnish Geospatial Research Institute FGI, P.O. Box 84, Helsinki FI-00521, Finland
3
Finnish Geospatial Research Institute FGI, National Land Survey of Finland, P.O. Box 84, Helsinki FI-00521, Finland
*
Author to whom correspondence should be addressed.
Academic Editor: Eric J. Jokela
Received: 19 February 2015 / Revised: 7 April 2015 / Accepted: 9 April 2015 / Published: 15 April 2015
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Abstract

We evaluated a smartphone app (TRESTIMATM) for forest sample plot measurements. The app interprets imagery collected from the sample plots using the camera in the smartphone and then estimates forest inventory attributes, including species-specific basal areas (G) as well as the diameter (DgM) and height (HgM) of basal area median trees. The estimates from the smartphone app were compared to forest inventory attributes derived from tree-wise measurements using calipers and a Vertex height measurement device. The data consist of 2169 measured trees from 25 sample plots (32 m × 32 m), dominated by Scots pine and Norway spruce from southern Finland. The root-mean-square errors (RMSEs) in the basal area varied from 19.7% to 29.3% and the biases from 11.4% to 18.4% depending on the number of images per sample plot and image shooting location. DgM measurement bias varied from −1.4% to 3.1% and RMSE from 5.2% to 11.6% depending on the tree species. Respectively, HgM bias varied from 5.0% to 8.3% and RMSE 10.0% to 13.6%. In general, four images captured toward the center of the plot provided more accurate results than four images captured away from the plot center. Increasing the number of captured images per plot to the analyses yielded only marginal improvement to the results. View Full-Text
Keywords: forest mensuration; forest technology; GIS; forest inventory; remote sensing; forest management planning forest mensuration; forest technology; GIS; forest inventory; remote sensing; forest management planning
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. (CC BY 4.0).

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MDPI and ACS Style

Vastaranta, M.; Latorre, E.G.; Luoma, V.; Saarinen, N.; Holopainen, M.; Hyyppä, J. Evaluation of a Smartphone App for Forest Sample Plot Measurements. Forests 2015, 6, 1179-1194.

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