Integration of field measurements with unmanned aerial vehicle to predict forest inventory metrics at tree and stand scales in natural pure Crimean pine forests

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dc.authoridAksoy, Hasan/0000-0003-1980-3834
dc.contributor.authorBulut, Sinan
dc.contributor.authorGunlu, Alkan
dc.contributor.authorAksoy, Hasan
dc.contributor.authorBolat, Ferhat
dc.contributor.authorSoenmez, Muecahit Yilmaz
dc.date.accessioned2025-03-23T19:35:22Z
dc.date.available2025-03-23T19:35:22Z
dc.date.issued2024
dc.departmentSinop Üniversitesi
dc.description.abstractInventorying forest ecosystems is an essential part of forest management planning. However, it is quite costly and time-consuming, particularly for larger areas. Recently, significant developments have been made in unmanned aerial vehicle (UAV) technology to improve the cost and time efficiency in forest inventory. Therefore, UAV images have become one of the inventory tools that produces data with high spatial resolution in determining forest resources. This study aims to investigate the contribution of UAV data to forest inventory in a case study area with a total of 30 sample plots located in pure and natural Crimean pine (Pinus nigra J.F. Arnold ssp. pallasiana (Lamb.) Holmboe) stands in the Black Sea backward region of T & uuml;rkiye. Total tree height (h) and stem volume (v) were recorded at individual tree level (n = 367), and the number of trees (N), mean height (h(mean)), top height (h(top)), stand basal area (BA) and stand volume (V) were calculated at sample plot level (n = 30) from both the field and UAV-based data. Pearson's correlation coefficients (r) for h and v were 0.96 and 0.72, respectively, the highest correlation at the sample plot level was observed for the h(mean) - h(top) (r = 0.96), while the lowest correlation was found for BA (r = 0.54). The suitability of the observation and prediction values was assessed using a t-test at both individual tree and sample plot levels. According to the t-test results, the observation and prediction values for h, v, h(mean), h(top), BA and V metrics were found to be compatible (p > 0.05), but not for N (p < 0.05). Overall results indicated that UAV technology has a potential to be used in forest inventory and can contribute to the determination of individual tree and stand metrics. Thereby, it saves cost and time in forest inventory studies and helps monitoring the dynamic structure of the forest ecosystem with an effective approach in forest inventory.
dc.description.sponsorshipCankiri Karatekin University Project Department [OF080120B04]
dc.description.sponsorshipThis work was supported by the Cankiri Karatekin University Project Department, [Project No: OF080120B04].
dc.identifier.doi10.1080/01431161.2024.2357837
dc.identifier.endpage3896
dc.identifier.issn0143-1161
dc.identifier.issn1366-5901
dc.identifier.issue12
dc.identifier.scopus2-s2.0-85195521148
dc.identifier.scopusqualityQ1
dc.identifier.startpage3872
dc.identifier.urihttps://doi.org/10.1080/01431161.2024.2357837
dc.identifier.urihttps://hdl.handle.net/11486/5853
dc.identifier.volume45
dc.identifier.wosWOS:001238832800001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor & Francis Ltd
dc.relation.ispartofInternational Journal of Remote Sensing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250323
dc.subjectRemote sensing
dc.subjectpoint cloud
dc.subjectconiferous forest
dc.subjectforest inventory
dc.subjectUAV
dc.titleIntegration of field measurements with unmanned aerial vehicle to predict forest inventory metrics at tree and stand scales in natural pure Crimean pine forests
dc.typeArticle

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