Frederico Tupinambá-Simões, Adrián Pascual, Juan Guerra-Hernández, Cristóbal Ordóñez, Tiago de Conto, Felipe Bravo
{"title":"比较混交林落叶和落叶情况下基于手持激光扫描的树木测绘精度","authors":"Frederico Tupinambá-Simões, Adrián Pascual, Juan Guerra-Hernández, Cristóbal Ordóñez, Tiago de Conto, Felipe Bravo","doi":"10.1007/s11676-024-01747-1","DOIUrl":null,"url":null,"abstract":"<p>The use of mobile laser scanning to survey forest ecosystems is a promising, scalable technology to describe forest 3D structures at high resolution. To confirm the consistency in the retrieval of forest structural parameters using hand-held laser scanning (HLS), before operationalizing the method, confirming the data is crucial. We analyzed the performance of tree-level mapping based on HLS under different phenology conditions on a mixed forest in western Spain comprising <i>Pinus pinaster</i> and two deciduous species, <i>Alnus glutinosa</i> and <i>Quercus pyrenaica</i>. The area was surveyed twice during the growing season (July 2022) and once in the deciduous season (February 2022) using several scanning paths. Ground reference data (418 trees, 15 snags) was used to calibrate the HLS data and to assess the influence of phenology when converting 3D data into tree-level attributes (DBH, height and volume). The HLS-based workflow was robust at isolating tree positions and recognizing stems despite changes in phenology. Ninety-six percent of all pairs matched below 65 cm. For DBH, phenology barely altered estimates. We observed a strong agreement when comparing HLS-based tree height distributions. The values exceeded 2 m when comparing height measurements, confirming height data should be carefully used as reference in remote sensing-based inventories, especially for deciduous species. Tree volume was more precise for pines (<i>r</i> = 0.95, and relative RMSE = 21.3 –23.8%) compared to deciduous species (<i>r</i> = 0.91 –0.96, and relative RMSE = 27.3–30.5%). HLS data and the forest structural complexity tool performed remarkably, especially in tree positioning considering mixed forests and mixed phenology conditions.</p>","PeriodicalId":15830,"journal":{"name":"Journal of Forestry Research","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accuracy of tree mapping based on hand-held laser scanning comparing leaf-on and leaf-off conditions in mixed forests\",\"authors\":\"Frederico Tupinambá-Simões, Adrián Pascual, Juan Guerra-Hernández, Cristóbal Ordóñez, Tiago de Conto, Felipe Bravo\",\"doi\":\"10.1007/s11676-024-01747-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The use of mobile laser scanning to survey forest ecosystems is a promising, scalable technology to describe forest 3D structures at high resolution. To confirm the consistency in the retrieval of forest structural parameters using hand-held laser scanning (HLS), before operationalizing the method, confirming the data is crucial. We analyzed the performance of tree-level mapping based on HLS under different phenology conditions on a mixed forest in western Spain comprising <i>Pinus pinaster</i> and two deciduous species, <i>Alnus glutinosa</i> and <i>Quercus pyrenaica</i>. The area was surveyed twice during the growing season (July 2022) and once in the deciduous season (February 2022) using several scanning paths. Ground reference data (418 trees, 15 snags) was used to calibrate the HLS data and to assess the influence of phenology when converting 3D data into tree-level attributes (DBH, height and volume). The HLS-based workflow was robust at isolating tree positions and recognizing stems despite changes in phenology. Ninety-six percent of all pairs matched below 65 cm. For DBH, phenology barely altered estimates. We observed a strong agreement when comparing HLS-based tree height distributions. The values exceeded 2 m when comparing height measurements, confirming height data should be carefully used as reference in remote sensing-based inventories, especially for deciduous species. Tree volume was more precise for pines (<i>r</i> = 0.95, and relative RMSE = 21.3 –23.8%) compared to deciduous species (<i>r</i> = 0.91 –0.96, and relative RMSE = 27.3–30.5%). HLS data and the forest structural complexity tool performed remarkably, especially in tree positioning considering mixed forests and mixed phenology conditions.</p>\",\"PeriodicalId\":15830,\"journal\":{\"name\":\"Journal of Forestry Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Forestry Research\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1007/s11676-024-01747-1\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forestry Research","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1007/s11676-024-01747-1","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FORESTRY","Score":null,"Total":0}
Accuracy of tree mapping based on hand-held laser scanning comparing leaf-on and leaf-off conditions in mixed forests
The use of mobile laser scanning to survey forest ecosystems is a promising, scalable technology to describe forest 3D structures at high resolution. To confirm the consistency in the retrieval of forest structural parameters using hand-held laser scanning (HLS), before operationalizing the method, confirming the data is crucial. We analyzed the performance of tree-level mapping based on HLS under different phenology conditions on a mixed forest in western Spain comprising Pinus pinaster and two deciduous species, Alnus glutinosa and Quercus pyrenaica. The area was surveyed twice during the growing season (July 2022) and once in the deciduous season (February 2022) using several scanning paths. Ground reference data (418 trees, 15 snags) was used to calibrate the HLS data and to assess the influence of phenology when converting 3D data into tree-level attributes (DBH, height and volume). The HLS-based workflow was robust at isolating tree positions and recognizing stems despite changes in phenology. Ninety-six percent of all pairs matched below 65 cm. For DBH, phenology barely altered estimates. We observed a strong agreement when comparing HLS-based tree height distributions. The values exceeded 2 m when comparing height measurements, confirming height data should be carefully used as reference in remote sensing-based inventories, especially for deciduous species. Tree volume was more precise for pines (r = 0.95, and relative RMSE = 21.3 –23.8%) compared to deciduous species (r = 0.91 –0.96, and relative RMSE = 27.3–30.5%). HLS data and the forest structural complexity tool performed remarkably, especially in tree positioning considering mixed forests and mixed phenology conditions.
期刊介绍:
The Journal of Forestry Research (JFR), founded in 1990, is a peer-reviewed quarterly journal in English. JFR has rapidly emerged as an international journal published by Northeast Forestry University and Ecological Society of China in collaboration with Springer Verlag. The journal publishes scientific articles related to forestry for a broad range of international scientists, forest managers and practitioners.The scope of the journal covers the following five thematic categories and 20 subjects:
Basic Science of Forestry,
Forest biometrics,
Forest soils,
Forest hydrology,
Tree physiology,
Forest biomass, carbon, and bioenergy,
Forest biotechnology and molecular biology,
Forest Ecology,
Forest ecology,
Forest ecological services,
Restoration ecology,
Forest adaptation to climate change,
Wildlife ecology and management,
Silviculture and Forest Management,
Forest genetics and tree breeding,
Silviculture,
Forest RS, GIS, and modeling,
Forest management,
Forest Protection,
Forest entomology and pathology,
Forest fire,
Forest resources conservation,
Forest health monitoring and assessment,
Wood Science and Technology,
Wood Science and Technology.