New Method for Forest Resource Data Collection Based on Smartphone Fusion with Multiple Sensors
Tree parameter measurement is an important part of forest resource monitoring. Smartphones play an important role in forest resource surveys. Although sensors inside smartphones, such as gyroscopes and angle sensors, can meet the needs of the public for entertainment or games, the measurement accura...
Gespeichert in:
Veröffentlicht in: | Mobile information systems 2020, Vol.2020 (2020), p.1-11 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 11 |
---|---|
container_issue | 2020 |
container_start_page | 1 |
container_title | Mobile information systems |
container_volume | 2020 |
creator | Chen, Feixiang Chen, Danyu Dong, Yanqi Fan, Guangpeng |
description | Tree parameter measurement is an important part of forest resource monitoring. Smartphones play an important role in forest resource surveys. Although sensors inside smartphones, such as gyroscopes and angle sensors, can meet the needs of the public for entertainment or games, the measurement accuracy in professional forest resource monitoring is slightly insufficient. In this paper, a method of collecting tree measurement factors based on personal smart space fusion with a variety of high-precision sensors is proposed. First of all, a high-precision attitude sensor measurement module and a laser ranging module are organically integrated and packaged in a black box. The smartphone is then connected to the sensor box using a magnet sheet, and the working personnel can determine key parameters in the forest stand by holding it. Finally, in order to verify the accuracy of the method, the measured values in this paper are compared with the reference values. The root mean square error (RMSE) of the tree position in the X and Y directions was 0.114 m and 0.147 m, the relative deviations (rBias) were 0.95% and 0.39%, and the average RMSE was 0.186 m. The RMSEs measured by tree height and diameter at breast height (DBH) were 0.98 m and 2.24 cm, the relative root mean square error (rRMSE) was 5.87% and 13.46%, and the relative deviations (rBias) were −1.40% and −1.06%, respectively. Therefore, the method of forest stand parameter measurement based on personal smart space fusion multitype sensors proposed in this paper can be effectively applied to forest resource data collection. |
doi_str_mv | 10.1155/2020/5736978 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2407982325</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2407982325</sourcerecordid><originalsourceid>FETCH-LOGICAL-c360t-97853fcf2af2a8571bc3215afa19d3bc8f159c1ecfe48a92349a15ce6997fc813</originalsourceid><addsrcrecordid>eNqFkN9LwzAQx4soOKdvPkvAR63mR9M0jzqdCpuCU9hbyNIL7ahNTVqG_70ZG_goHNwX7sPdfb9Jck7wDSGc31JM8S0XLJeiOEhGpBA8lZgvD6PmIksxEcvj5CSENcY5ZlyMEvUKGzSHvnIlss6jqfMQevQOwQ3eAHrQvUYT1zRg-tq16F4HKFEUiy_t-65yLaDpELajTd1XaD40fd01gBbQBufDaXJkdRPgbN_Hyef08WPynM7enl4md7PUsBz3aXyYM2ss1bEKLsjKMEq4tprIkq1MYQmXhoCxkBVaUpZJTbiBXEphTUHYOLnc7e28-x6iBbWOBtp4UtEMC1lQRnmkrneU8S4ED1Z1vo5GfhTBahuh2kao9hFG_GqHV3Vb6k39H32xoyEyYPUfTSTNiGS_01x63w</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2407982325</pqid></control><display><type>article</type><title>New Method for Forest Resource Data Collection Based on Smartphone Fusion with Multiple Sensors</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Wiley-Blackwell Open Access Titles</source><source>Alma/SFX Local Collection</source><creator>Chen, Feixiang ; Chen, Danyu ; Dong, Yanqi ; Fan, Guangpeng</creator><contributor>Lee, Sungchang ; Sungchang Lee</contributor><creatorcontrib>Chen, Feixiang ; Chen, Danyu ; Dong, Yanqi ; Fan, Guangpeng ; Lee, Sungchang ; Sungchang Lee</creatorcontrib><description>Tree parameter measurement is an important part of forest resource monitoring. Smartphones play an important role in forest resource surveys. Although sensors inside smartphones, such as gyroscopes and angle sensors, can meet the needs of the public for entertainment or games, the measurement accuracy in professional forest resource monitoring is slightly insufficient. In this paper, a method of collecting tree measurement factors based on personal smart space fusion with a variety of high-precision sensors is proposed. First of all, a high-precision attitude sensor measurement module and a laser ranging module are organically integrated and packaged in a black box. The smartphone is then connected to the sensor box using a magnet sheet, and the working personnel can determine key parameters in the forest stand by holding it. Finally, in order to verify the accuracy of the method, the measured values in this paper are compared with the reference values. The root mean square error (RMSE) of the tree position in the X and Y directions was 0.114 m and 0.147 m, the relative deviations (rBias) were 0.95% and 0.39%, and the average RMSE was 0.186 m. The RMSEs measured by tree height and diameter at breast height (DBH) were 0.98 m and 2.24 cm, the relative root mean square error (rRMSE) was 5.87% and 13.46%, and the relative deviations (rBias) were −1.40% and −1.06%, respectively. Therefore, the method of forest stand parameter measurement based on personal smart space fusion multitype sensors proposed in this paper can be effectively applied to forest resource data collection.</description><identifier>ISSN: 1574-017X</identifier><identifier>EISSN: 1875-905X</identifier><identifier>DOI: 10.1155/2020/5736978</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Accuracy ; Climate change ; Data collection ; Diameters ; Forests ; Gyroscopes ; Java ; Lasers ; Magnetic fields ; Methods ; Modules ; Monitoring ; Operating systems ; Parameters ; Photogrammetry ; Researchers ; Root-mean-square errors ; Sensors ; Smart sensors ; Smartphones ; Software ; Trees</subject><ispartof>Mobile information systems, 2020, Vol.2020 (2020), p.1-11</ispartof><rights>Copyright © 2020 Guangpeng Fan et al.</rights><rights>Copyright © 2020 Guangpeng Fan et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c360t-97853fcf2af2a8571bc3215afa19d3bc8f159c1ecfe48a92349a15ce6997fc813</citedby><cites>FETCH-LOGICAL-c360t-97853fcf2af2a8571bc3215afa19d3bc8f159c1ecfe48a92349a15ce6997fc813</cites><orcidid>0000-0003-1000-8455</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,4014,27914,27915,27916</link.rule.ids></links><search><contributor>Lee, Sungchang</contributor><contributor>Sungchang Lee</contributor><creatorcontrib>Chen, Feixiang</creatorcontrib><creatorcontrib>Chen, Danyu</creatorcontrib><creatorcontrib>Dong, Yanqi</creatorcontrib><creatorcontrib>Fan, Guangpeng</creatorcontrib><title>New Method for Forest Resource Data Collection Based on Smartphone Fusion with Multiple Sensors</title><title>Mobile information systems</title><description>Tree parameter measurement is an important part of forest resource monitoring. Smartphones play an important role in forest resource surveys. Although sensors inside smartphones, such as gyroscopes and angle sensors, can meet the needs of the public for entertainment or games, the measurement accuracy in professional forest resource monitoring is slightly insufficient. In this paper, a method of collecting tree measurement factors based on personal smart space fusion with a variety of high-precision sensors is proposed. First of all, a high-precision attitude sensor measurement module and a laser ranging module are organically integrated and packaged in a black box. The smartphone is then connected to the sensor box using a magnet sheet, and the working personnel can determine key parameters in the forest stand by holding it. Finally, in order to verify the accuracy of the method, the measured values in this paper are compared with the reference values. The root mean square error (RMSE) of the tree position in the X and Y directions was 0.114 m and 0.147 m, the relative deviations (rBias) were 0.95% and 0.39%, and the average RMSE was 0.186 m. The RMSEs measured by tree height and diameter at breast height (DBH) were 0.98 m and 2.24 cm, the relative root mean square error (rRMSE) was 5.87% and 13.46%, and the relative deviations (rBias) were −1.40% and −1.06%, respectively. Therefore, the method of forest stand parameter measurement based on personal smart space fusion multitype sensors proposed in this paper can be effectively applied to forest resource data collection.</description><subject>Accuracy</subject><subject>Climate change</subject><subject>Data collection</subject><subject>Diameters</subject><subject>Forests</subject><subject>Gyroscopes</subject><subject>Java</subject><subject>Lasers</subject><subject>Magnetic fields</subject><subject>Methods</subject><subject>Modules</subject><subject>Monitoring</subject><subject>Operating systems</subject><subject>Parameters</subject><subject>Photogrammetry</subject><subject>Researchers</subject><subject>Root-mean-square errors</subject><subject>Sensors</subject><subject>Smart sensors</subject><subject>Smartphones</subject><subject>Software</subject><subject>Trees</subject><issn>1574-017X</issn><issn>1875-905X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><recordid>eNqFkN9LwzAQx4soOKdvPkvAR63mR9M0jzqdCpuCU9hbyNIL7ahNTVqG_70ZG_goHNwX7sPdfb9Jck7wDSGc31JM8S0XLJeiOEhGpBA8lZgvD6PmIksxEcvj5CSENcY5ZlyMEvUKGzSHvnIlss6jqfMQevQOwQ3eAHrQvUYT1zRg-tq16F4HKFEUiy_t-65yLaDpELajTd1XaD40fd01gBbQBufDaXJkdRPgbN_Hyef08WPynM7enl4md7PUsBz3aXyYM2ss1bEKLsjKMEq4tprIkq1MYQmXhoCxkBVaUpZJTbiBXEphTUHYOLnc7e28-x6iBbWOBtp4UtEMC1lQRnmkrneU8S4ED1Z1vo5GfhTBahuh2kao9hFG_GqHV3Vb6k39H32xoyEyYPUfTSTNiGS_01x63w</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Chen, Feixiang</creator><creator>Chen, Danyu</creator><creator>Dong, Yanqi</creator><creator>Fan, Guangpeng</creator><general>Hindawi Publishing Corporation</general><general>Hindawi</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-1000-8455</orcidid></search><sort><creationdate>2020</creationdate><title>New Method for Forest Resource Data Collection Based on Smartphone Fusion with Multiple Sensors</title><author>Chen, Feixiang ; Chen, Danyu ; Dong, Yanqi ; Fan, Guangpeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c360t-97853fcf2af2a8571bc3215afa19d3bc8f159c1ecfe48a92349a15ce6997fc813</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Accuracy</topic><topic>Climate change</topic><topic>Data collection</topic><topic>Diameters</topic><topic>Forests</topic><topic>Gyroscopes</topic><topic>Java</topic><topic>Lasers</topic><topic>Magnetic fields</topic><topic>Methods</topic><topic>Modules</topic><topic>Monitoring</topic><topic>Operating systems</topic><topic>Parameters</topic><topic>Photogrammetry</topic><topic>Researchers</topic><topic>Root-mean-square errors</topic><topic>Sensors</topic><topic>Smart sensors</topic><topic>Smartphones</topic><topic>Software</topic><topic>Trees</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Feixiang</creatorcontrib><creatorcontrib>Chen, Danyu</creatorcontrib><creatorcontrib>Dong, Yanqi</creatorcontrib><creatorcontrib>Fan, Guangpeng</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Mobile information systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Feixiang</au><au>Chen, Danyu</au><au>Dong, Yanqi</au><au>Fan, Guangpeng</au><au>Lee, Sungchang</au><au>Sungchang Lee</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New Method for Forest Resource Data Collection Based on Smartphone Fusion with Multiple Sensors</atitle><jtitle>Mobile information systems</jtitle><date>2020</date><risdate>2020</risdate><volume>2020</volume><issue>2020</issue><spage>1</spage><epage>11</epage><pages>1-11</pages><issn>1574-017X</issn><eissn>1875-905X</eissn><abstract>Tree parameter measurement is an important part of forest resource monitoring. Smartphones play an important role in forest resource surveys. Although sensors inside smartphones, such as gyroscopes and angle sensors, can meet the needs of the public for entertainment or games, the measurement accuracy in professional forest resource monitoring is slightly insufficient. In this paper, a method of collecting tree measurement factors based on personal smart space fusion with a variety of high-precision sensors is proposed. First of all, a high-precision attitude sensor measurement module and a laser ranging module are organically integrated and packaged in a black box. The smartphone is then connected to the sensor box using a magnet sheet, and the working personnel can determine key parameters in the forest stand by holding it. Finally, in order to verify the accuracy of the method, the measured values in this paper are compared with the reference values. The root mean square error (RMSE) of the tree position in the X and Y directions was 0.114 m and 0.147 m, the relative deviations (rBias) were 0.95% and 0.39%, and the average RMSE was 0.186 m. The RMSEs measured by tree height and diameter at breast height (DBH) were 0.98 m and 2.24 cm, the relative root mean square error (rRMSE) was 5.87% and 13.46%, and the relative deviations (rBias) were −1.40% and −1.06%, respectively. Therefore, the method of forest stand parameter measurement based on personal smart space fusion multitype sensors proposed in this paper can be effectively applied to forest resource data collection.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><doi>10.1155/2020/5736978</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-1000-8455</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1574-017X |
ispartof | Mobile information systems, 2020, Vol.2020 (2020), p.1-11 |
issn | 1574-017X 1875-905X |
language | eng |
recordid | cdi_proquest_journals_2407982325 |
source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Wiley-Blackwell Open Access Titles; Alma/SFX Local Collection |
subjects | Accuracy Climate change Data collection Diameters Forests Gyroscopes Java Lasers Magnetic fields Methods Modules Monitoring Operating systems Parameters Photogrammetry Researchers Root-mean-square errors Sensors Smart sensors Smartphones Software Trees |
title | New Method for Forest Resource Data Collection Based on Smartphone Fusion with Multiple Sensors |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T05%3A18%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=New%20Method%20for%20Forest%20Resource%20Data%20Collection%20Based%20on%20Smartphone%20Fusion%20with%20Multiple%20Sensors&rft.jtitle=Mobile%20information%20systems&rft.au=Chen,%20Feixiang&rft.date=2020&rft.volume=2020&rft.issue=2020&rft.spage=1&rft.epage=11&rft.pages=1-11&rft.issn=1574-017X&rft.eissn=1875-905X&rft_id=info:doi/10.1155/2020/5736978&rft_dat=%3Cproquest_cross%3E2407982325%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2407982325&rft_id=info:pmid/&rfr_iscdi=true |