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Evaluation of a Smartphone App for Forest Sample Plot Measurements
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 h...
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Published in: | Forests 2015-04, Vol.6 (4), p.1179-1194 |
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creator | Vastaranta, Mikko Latorre, Eduardo Luoma, Ville Saarinen, Ninni Holopainen, Markus Hyyppä, Juha |
description | 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. |
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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.</description><identifier>ISSN: 1999-4907</identifier><identifier>EISSN: 1999-4907</identifier><identifier>DOI: 10.3390/f6041179</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Accuracy ; Digital cameras ; forest inventory ; forest management planning ; forest mensuration ; forest technology ; Forests ; GIS ; Land surveys ; Lasers ; Picea abies ; Pinus sylvestris ; Remote sensing ; Scanners ; Smartphones ; Trees</subject><ispartof>Forests, 2015-04, Vol.6 (4), p.1179-1194</ispartof><rights>Copyright MDPI AG 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c388t-526a99533eb53cf0e265ab014664c60569c0ba87bdbbf0edc44d200bb00bd0323</citedby><cites>FETCH-LOGICAL-c388t-526a99533eb53cf0e265ab014664c60569c0ba87bdbbf0edc44d200bb00bd0323</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1676111168/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1676111168?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,37013,44590,75126</link.rule.ids></links><search><creatorcontrib>Vastaranta, Mikko</creatorcontrib><creatorcontrib>Latorre, Eduardo</creatorcontrib><creatorcontrib>Luoma, Ville</creatorcontrib><creatorcontrib>Saarinen, Ninni</creatorcontrib><creatorcontrib>Holopainen, Markus</creatorcontrib><creatorcontrib>Hyyppä, Juha</creatorcontrib><title>Evaluation of a Smartphone App for Forest Sample Plot Measurements</title><title>Forests</title><description>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.</description><subject>Accuracy</subject><subject>Digital cameras</subject><subject>forest inventory</subject><subject>forest management planning</subject><subject>forest mensuration</subject><subject>forest technology</subject><subject>Forests</subject><subject>GIS</subject><subject>Land surveys</subject><subject>Lasers</subject><subject>Picea abies</subject><subject>Pinus sylvestris</subject><subject>Remote sensing</subject><subject>Scanners</subject><subject>Smartphones</subject><subject>Trees</subject><issn>1999-4907</issn><issn>1999-4907</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdUVFLwzAQLqLg0IE_IeCLL9VLk6bN4xybDiYK0-eQpIl2tE1NWsF_b9x0iAfHHXcf3_cdlyQXGK4J4XBjGVCMC36UTDDnPKUciuM__WkyDWELMfKi5BmdJLeLD9mMcqhdh5xFEm1a6Yf-zXUGzfoeWefR0nkTBrSRbd8Y9NS4AT0YGUZvWtMN4Tw5sbIJZvpTz5KX5eJ5fp-uH-9W89k61aQshzTPmOQ8J8SonGgLJmO5VIApY1QzyBnXoGRZqEqpuK00pVUGoFTMCkhGzpLVnrdycit6X0enn8LJWuwGzr-KaL3WjRGlkRYqUgAtC8pKIglmpQRFrbZY5SZyXe25eu_ex3idaOugTdPIzrgxiAgHygjeyV7-g27d6Lt4aUQVDMeICgdC7V0I3tiDQQzi-zfi9zfkC9SQfhc</recordid><startdate>20150401</startdate><enddate>20150401</enddate><creator>Vastaranta, Mikko</creator><creator>Latorre, Eduardo</creator><creator>Luoma, Ville</creator><creator>Saarinen, Ninni</creator><creator>Holopainen, Markus</creator><creator>Hyyppä, Juha</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SN</scope><scope>7SS</scope><scope>7X2</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>M0K</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>7ST</scope><scope>7U6</scope><scope>DOA</scope></search><sort><creationdate>20150401</creationdate><title>Evaluation of a Smartphone App for Forest Sample Plot Measurements</title><author>Vastaranta, Mikko ; Latorre, Eduardo ; Luoma, Ville ; Saarinen, Ninni ; Holopainen, Markus ; Hyyppä, Juha</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c388t-526a99533eb53cf0e265ab014664c60569c0ba87bdbbf0edc44d200bb00bd0323</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Accuracy</topic><topic>Digital cameras</topic><topic>forest inventory</topic><topic>forest management planning</topic><topic>forest mensuration</topic><topic>forest technology</topic><topic>Forests</topic><topic>GIS</topic><topic>Land surveys</topic><topic>Lasers</topic><topic>Picea abies</topic><topic>Pinus sylvestris</topic><topic>Remote sensing</topic><topic>Scanners</topic><topic>Smartphones</topic><topic>Trees</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vastaranta, Mikko</creatorcontrib><creatorcontrib>Latorre, Eduardo</creatorcontrib><creatorcontrib>Luoma, Ville</creatorcontrib><creatorcontrib>Saarinen, Ninni</creatorcontrib><creatorcontrib>Holopainen, Markus</creatorcontrib><creatorcontrib>Hyyppä, Juha</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Agriculture Science Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Environmental Science Collection</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Directory of Open Access Journals</collection><jtitle>Forests</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vastaranta, Mikko</au><au>Latorre, Eduardo</au><au>Luoma, Ville</au><au>Saarinen, Ninni</au><au>Holopainen, Markus</au><au>Hyyppä, Juha</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of a Smartphone App for Forest Sample Plot Measurements</atitle><jtitle>Forests</jtitle><date>2015-04-01</date><risdate>2015</risdate><volume>6</volume><issue>4</issue><spage>1179</spage><epage>1194</epage><pages>1179-1194</pages><issn>1999-4907</issn><eissn>1999-4907</eissn><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.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/f6041179</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Digital cameras forest inventory forest management planning forest mensuration forest technology Forests GIS Land surveys Lasers Picea abies Pinus sylvestris Remote sensing Scanners Smartphones Trees |
title | Evaluation of a Smartphone App for Forest Sample Plot Measurements |
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