Accuracy of tree mapping based on hand-held laser scanning comparing leaf-on and leaf-off conditions in mixed forests

IF 3.4 2区 农林科学 Q1 FORESTRY
Frederico Tupinambá-Simões, Adrián Pascual, Juan Guerra-Hernández, Cristóbal Ordóñez, Tiago de Conto, Felipe Bravo
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Abstract

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.

Abstract Image

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
使用移动激光扫描勘测森林生态系统是一项前景广阔的可扩展技术,能够以高分辨率描述森林的三维结构。为了确认使用手持激光扫描(HLS)检索森林结构参数的一致性,在该方法投入使用之前,确认数据至关重要。我们在西班牙西部的一片混交林中分析了不同物候条件下基于 HLS 的树级绘图性能,该混交林由 Pinus pinaster 和两种落叶树种 Alnus glutinosa 和 Quercus pyrenaica 组成。在生长季节(2022 年 7 月)和落叶季节(2022 年 2 月)分别对该地区进行了两次和一次扫描。地面参考数据(418 棵树、15 个树桩)用于校准 HLS 数据,并评估将三维数据转换为树级属性(DBH、高度和体积)时物候的影响。尽管物候发生了变化,但基于 HLS 的工作流程在隔离树木位置和识别茎干方面非常稳健。在 65 厘米以下的树对中,96% 的树对是匹配的。对于 DBH,物候几乎不会改变估计值。在比较基于 HLS 的树高分布时,我们观察到了很强的一致性。在比较高度测量值时,数值超过了 2 米,这证明在基于遥感的调查中应谨慎使用高度数据作为参考,尤其是落叶树种。与落叶树种(r = 0.91 -0.96,相对均方根误差 = 27.3-30.5%)相比,松树的树木体积更为精确(r = 0.95,相对均方根误差 = 21.3 -23.8%)。HLS 数据和森林结构复杂性工具表现出色,尤其是在考虑混交林和混合物候条件的树木定位方面。
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来源期刊
CiteScore
7.30
自引率
3.30%
发文量
2538
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.
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