Trunk volume estimation of irregular shaped Populus euphratica riparian forest using TLS point cloud data and multivariate prediction models
Background: Trunk volume (Vt) is an essential parameter for estimating forest stand volume, biomass, and carbon sequestration potential. As the dominant tree species in desert riparian forests, Euphrates poplar (Populus euphratica) has a high proportion of irregularly shaped tree trunks along the Ta...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2023-01-01
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| Series: | Forest Ecosystems |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2197562022000823 |
| _version_ | 1797382907068678144 |
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| author | Asadilla Yusup Ümüt Halik Maierdang Keyimu Tayierjiang Aishan Abdulla Abliz Babierjiang Dilixiati Jianxin Wei |
| author_facet | Asadilla Yusup Ümüt Halik Maierdang Keyimu Tayierjiang Aishan Abdulla Abliz Babierjiang Dilixiati Jianxin Wei |
| author_sort | Asadilla Yusup |
| collection | DOAJ |
| description | Background: Trunk volume (Vt) is an essential parameter for estimating forest stand volume, biomass, and carbon sequestration potential. As the dominant tree species in desert riparian forests, Euphrates poplar (Populus euphratica) has a high proportion of irregularly shaped tree trunks along the Tarim River, NW China, where the habitat is very fragile owing to long-term water stress. This causes uncertainty in estimation accuracy as well as technical challenges for forest surveys. Our study aimed to acquire P. euphratica Vt using terrestrial laser scanning (TLS) and to establish a species-specific Vt prediction model. Methods: A total of 240 individual trees were measured by TLS multiple-station in 12 sampling plots in three sections along the lower reaches of the Tarim River. Vt was calculated by a definite integration method using trunk diameters (Di) at every 0.1-m tree height obtained from TLS, and all data were split randomly into two sets: 70% of data were used to estimate the model parameter calibration, and the remaining 30% were used for model validation. Sixteen widely used candidate tree Vt estimation models were fitted to the TLS-measured Vt and tree structural parameter data, including tree height (H), diameter at breast height (DBH), and basal diameter (BD). All model performances were evaluated and compared by the statistical parameters of determination coefficient (R2), root mean square error (RMSE), Bayesian information criterion (BIC), mean prediction error (ME), mean absolute error (MAE), and modeling efficiency (EF), and accordingly the best model was selected. Results: TLS point cloud reflection intensity (RI) has advantageous in the extraction of data from irregular tree trunk structures. The P. euphratica tree Vt values showed obvious differences at the same tree height (H). There was no significant correlation between Vt and H (R2 = 0.11, P < 0.01), which reflected the irregularity of P. euphratica trunk shape in the study area. Among all the models, model (14): Vt=0.909DBH1.184H0.487BD0.836 (R2 = 0.97, RMSE = 0.14) had the best prediction capability for irregularly shaped Vt with the highest R2, BIC (−37.96), and EF (0.96), and produced a smaller ME (0.006) and MAE (1.177) compared to other models. The prediction accuracy was 93.18%. Conclusions: TLS point cloud RI has a potential for nondestructively measuring irregularly shaped trunk structures of P. euphratica and developed Vt prediction models. The multivariate models more effectively predicted Vt for irregularly shaped trees compared to one-way and general volume models. |
| first_indexed | 2024-03-08T21:12:20Z |
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| id | doaj.art-62437ac7e0e84a6b98715e2999f6395e |
| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-03-08T21:12:20Z |
| publishDate | 2023-01-01 |
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| series | Forest Ecosystems |
| spelling | doaj.art-62437ac7e0e84a6b98715e2999f6395e2023-12-22T05:32:25ZengKeAi Communications Co., Ltd.Forest Ecosystems2197-56202023-01-0110100082Trunk volume estimation of irregular shaped Populus euphratica riparian forest using TLS point cloud data and multivariate prediction modelsAsadilla Yusup0Ümüt Halik1Maierdang Keyimu2Tayierjiang Aishan3Abdulla Abliz4Babierjiang Dilixiati5Jianxin Wei6College of Ecology and Environment, Ministry of Education Key Laboratory of Oasis Ecology, Xinjiang University, Ürümqi, 830046, ChinaCollege of Ecology and Environment, Ministry of Education Key Laboratory of Oasis Ecology, Xinjiang University, Ürümqi, 830046, China; Corresponding author.State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Science, Ürümqi, 830011, China; Cele National Station of Observation and Research for Desert-Grassland Ecosystems, Cele, 848300, ChinaCollege of Ecology and Environment, Ministry of Education Key Laboratory of Oasis Ecology, Xinjiang University, Ürümqi, 830046, ChinaCollege of Tourism, Key Laboratory of Sustainable Development of Xinjiang′s Historical and Cultural Tourism, Xinjiang University, Ürümqi, 830046, ChinaXinjiang Laser Radar Engineering Technology Center, Ürümqi, 830002, ChinaXinjiang Laser Radar Engineering Technology Center, Ürümqi, 830002, ChinaBackground: Trunk volume (Vt) is an essential parameter for estimating forest stand volume, biomass, and carbon sequestration potential. As the dominant tree species in desert riparian forests, Euphrates poplar (Populus euphratica) has a high proportion of irregularly shaped tree trunks along the Tarim River, NW China, where the habitat is very fragile owing to long-term water stress. This causes uncertainty in estimation accuracy as well as technical challenges for forest surveys. Our study aimed to acquire P. euphratica Vt using terrestrial laser scanning (TLS) and to establish a species-specific Vt prediction model. Methods: A total of 240 individual trees were measured by TLS multiple-station in 12 sampling plots in three sections along the lower reaches of the Tarim River. Vt was calculated by a definite integration method using trunk diameters (Di) at every 0.1-m tree height obtained from TLS, and all data were split randomly into two sets: 70% of data were used to estimate the model parameter calibration, and the remaining 30% were used for model validation. Sixteen widely used candidate tree Vt estimation models were fitted to the TLS-measured Vt and tree structural parameter data, including tree height (H), diameter at breast height (DBH), and basal diameter (BD). All model performances were evaluated and compared by the statistical parameters of determination coefficient (R2), root mean square error (RMSE), Bayesian information criterion (BIC), mean prediction error (ME), mean absolute error (MAE), and modeling efficiency (EF), and accordingly the best model was selected. Results: TLS point cloud reflection intensity (RI) has advantageous in the extraction of data from irregular tree trunk structures. The P. euphratica tree Vt values showed obvious differences at the same tree height (H). There was no significant correlation between Vt and H (R2 = 0.11, P < 0.01), which reflected the irregularity of P. euphratica trunk shape in the study area. Among all the models, model (14): Vt=0.909DBH1.184H0.487BD0.836 (R2 = 0.97, RMSE = 0.14) had the best prediction capability for irregularly shaped Vt with the highest R2, BIC (−37.96), and EF (0.96), and produced a smaller ME (0.006) and MAE (1.177) compared to other models. The prediction accuracy was 93.18%. Conclusions: TLS point cloud RI has a potential for nondestructively measuring irregularly shaped trunk structures of P. euphratica and developed Vt prediction models. The multivariate models more effectively predicted Vt for irregularly shaped trees compared to one-way and general volume models.http://www.sciencedirect.com/science/article/pii/S2197562022000823Populus euphraticaTrunk volumeTerrestrial laser scanning (TLS)Reflection intensityTarim river |
| spellingShingle | Asadilla Yusup Ümüt Halik Maierdang Keyimu Tayierjiang Aishan Abdulla Abliz Babierjiang Dilixiati Jianxin Wei Trunk volume estimation of irregular shaped Populus euphratica riparian forest using TLS point cloud data and multivariate prediction models Forest Ecosystems Populus euphratica Trunk volume Terrestrial laser scanning (TLS) Reflection intensity Tarim river |
| title | Trunk volume estimation of irregular shaped Populus euphratica riparian forest using TLS point cloud data and multivariate prediction models |
| title_full | Trunk volume estimation of irregular shaped Populus euphratica riparian forest using TLS point cloud data and multivariate prediction models |
| title_fullStr | Trunk volume estimation of irregular shaped Populus euphratica riparian forest using TLS point cloud data and multivariate prediction models |
| title_full_unstemmed | Trunk volume estimation of irregular shaped Populus euphratica riparian forest using TLS point cloud data and multivariate prediction models |
| title_short | Trunk volume estimation of irregular shaped Populus euphratica riparian forest using TLS point cloud data and multivariate prediction models |
| title_sort | trunk volume estimation of irregular shaped populus euphratica riparian forest using tls point cloud data and multivariate prediction models |
| topic | Populus euphratica Trunk volume Terrestrial laser scanning (TLS) Reflection intensity Tarim river |
| url | http://www.sciencedirect.com/science/article/pii/S2197562022000823 |
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