利用航拍照片匹配和机载激光扫描数据得出的树冠高度模型来确定Bory tucholsky国家公园的树木数量

P. Wężyk, P. Hawryło, Marta Szostak
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引用次数: 7

摘要

近年来,“精确林业”一词越来越常用,指的是现代和可持续的森林管理模式。这种木材生物量资源管理的运作除其他外,是根据现代地理信息技术,包括机载激光扫描和数字摄影测量,精确确定和长期监测单棵树和整个林分的选定森林税收参数。本研究的目的是分析基于图像的点云或ALS技术生成的CHM (Canopy Height Model)在使用单个苏格兰松(Pinus sylvestris L.)树冠分割方法定义树木数量方面的有效性。这项研究是在位于波兰Bory tucholsky国家公园的苏格兰松林中进行的。由于故意缺乏某些造林处理,近几十年来,与管理森林相比,这些林分的特点是树木密度相对较高。CHM是由数字航空照片(CIR构图;GSD 0.15 m)和ALS点云(4点/m;ISOK项目)。应用PhotoScan Professional (Agisoft)软件对航空照片进行立体匹配生成点云。基于图像的点云(CHM_IPC;GSD: 0.30 m)和ALS数据(CHM_ALS;GSD: 0.75 m)使用FUSION (USDA Forest Service)软件生成。在eCognition Developer (TRIMBLE GeoSpatial)软件中进行树冠分割。除了高度模型外,还使用了光谱信息(所谓的真实CIR正射影图;GSD: 0.3和0.75 m)。为了评估所得结果的准确性,使用了248个参考区域的地面真值数据。结果表明,在年龄较低(< 120年)的林分中,采用图像匹配方法(CHM_IPC)取得了较好的结果,而在年龄较大(bb0 120年)的林分中,采用CHM_ALS模型对树冠的检测准确率最高。基于248个地面真值区域计算的平均百分比误差(以单株松冠为基础,以树木数定义)为0.89%,显示了数字摄影测量(IPC)和GEOBIA的巨大潜力。在波兰几乎覆盖全国的情况下,机载数字图像(目前的IPC模型)和ALS点云
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determination of the number of trees in the Bory Tucholskie National Park using crown delineation of the canopy height models derived from aerial photos matching and airborne laser scanning data
In recent years the term "precise forestry" has been used more and more often, referring to a modern and sustainable model of forest management. Functioning of such management of wood biomass resources is based, among others, on precisely defined and log-term monitored selected forest taxation parameters of single trees and whole forest stands based on modern geoinformation technologies, including Airborne Laser Scanning (ALS) and digital photogrammetry. The purpose of the work was the analysis of the usefulness of the CHM (Canopy Height Model) generated from the image-based point cloud or ALS technology to define the number of trees using the method of the segmentation of single Scots pine (Pinus sylvestris L.) crowns. The study was carried out in the Scots pine stands located in the Bory Tucholskie National Park (Poland). Due to the intentional lack of certain silviculture treatments, over the recent decades, these forest stands have been characterized by relatively high tree density, compared to managed forests. The CHM was generated from digital airborne photos (CIR composition; GSD 0.15 m) and on the other hand from the ALS point clouds (4 points/m; ISOK project). To generate point clouds from airborne photos using stereomatching method, the PhotoScan Professional (Agisoft) software was applied. The CHM coming from the Image-Based Point Cloud (CHM_IPC; GSD: 0.30 m) and ALS data (CHM_ALS; GSD: 0.75 m) were generated using FUSION (USDA Forest Service) software. The segmentation of tree crowns was carried out in eCognition Developer (TRIMBLE GeoSpatial) software. Apart from height models, also spectral information was used (so-called true CIR orthophotomaps; GSD: 0.3 and 0.75 m). To assess the accuracy of the obtained results, the ground truth data from 248 reference areas were used. The carried out analyses showed that in forest stands of younger age classes (< 120 years) better results were achieved applying the method of image matching (CHM_IPC), while in the case of older stands (> 120 years) the accuracy of the detection rate of tree crowns was the highest when CHM_ALS model was applied. The mean percentage error (defined by the number of trees, based on the detection of single pine crowns), calculated based on 248 ground truth areas was 0.89%, which shows a great potential of digital photogrammetry (IPC) and GEOBIA. In case of almost full nationwide cover in Poland of airborne digital images (present IPC models) and ALS point clouds
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