Evaluation of a Smartphone App for Forest Sample Plot Measurements

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http://hdl.handle.net/10138/159312

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Vastaranta , M , Latorre , E G , Luoma , V , Saarinen , N , Holopainen , M & Hyyppä , J 2015 , ' Evaluation of a Smartphone App for Forest Sample Plot Measurements ' Forests , vol. 6 , no. 4 , pp. 1179-1194 . DOI: 10.3390/f6041179

Title: Evaluation of a Smartphone App for Forest Sample Plot Measurements
Author: Vastaranta, Mikko; Latorre, Eduardo Gonzalez; Luoma, Ville; Saarinen, Ninni; Holopainen, Markus; Hyyppä, Juha
Contributor: University of Helsinki, Department of Forest Sciences
University of Helsinki, Department of Forest Sciences
University of Helsinki, Department of Forest Sciences
University of Helsinki, Department of Forest Sciences
Date: 2015
Language: eng
Number of pages: 16
Belongs to series: Forests
ISSN: 1999-4907
URI: http://hdl.handle.net/10138/159312
Abstract: We evaluated a smartphone app (TRESTIMA(TM)) 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 (D-gM) and height (H-gM) 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 x 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. D-gM measurement bias varied from -1.4% to 3.1% and RMSE from 5.2% to 11.6% depending on the tree species. Respectively, H-gM 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.
Subject: AREA-BASED APPROACH
SCANNING LIDAR
LASER
PRECISION
ACCURACY
AIRBORNE
4112 Forestry
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