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首页> 外文期刊>Urban Forestry & Urban Greening >Tree mapping using airborne, terrestrial and mobile laser scanning - a case study in a heterogeneous urban forest.
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Tree mapping using airborne, terrestrial and mobile laser scanning - a case study in a heterogeneous urban forest.

机译:使用机载,陆地和移动激光扫描进行树图绘制-以异质城市森林为例。

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We evaluated the accuracy and efficiency of airborne (ALS), terrestrial (TLS) and mobile laser-scanning (MLS) methods that can be utilized in urban tree mapping and monitoring. In the field, 438 urban trees located in park and forested environments were measured and mapped from our study area located in Seurasaari, Helsinki, Finland. A field reference was collected, using a tree map created manually from TLS data. The tree detection rate and location accuracy were evaluated, using automatic or semiautomatic ALS individual tree detection (ALSITDauto or ALSITDvisual) and manual or automatic measurements of TLS and MLS (TLSauto, MLSauto, MLSmanual, MLSsemi). Our results showed that the best methods for tree detection were TLSauto and MLSmanual, which detected 73.29% and 79.22% of the reference trees, respectively. The location accuracies (RMSE) varied between 0.44 m and 1.57 m; the methods listed from the most accurate to most inaccurate were MLSsemi, TLSauto, MLSmanual, MLSauto, ALSITDauto and ALSITDvisual. We conclude that the accuracies of TLS and ALS were applicable for operational urban tree mapping in heterogeneous park forests. MLSmanual shows high potential but manual measurements are not feasible in operational tree mapping. Challenges that should be solved in further studies include ALSITDauto oversegmentation as well as MLSauto processing methodologies and data collection for tree detection.
机译:我们评估了可用于城市树木测绘和监测的机载(ALS),地面(TLS)和移动激光扫描(MLS)方法的准确性和效率。在实地,从我们位于芬兰赫尔辛基Seurasaari的研究区域测量并绘制了位于公园和森林环境中的438棵城市树木。使用从TLS数据手动创建的树图收集了字段引用。使用自动或半自动ALS单个树检测(ALS ITDauto 或ALS ITDvisual )以及TLS和MLS的手动或自动测量(TLS)来评估树的检测率和位置准确性 auto ,MLS auto ,MLS manual ,MLS semi )。我们的结果表明,最好的树检测方法是TLS auto 和MLS manual ,分别检测参考树的73.29%和79.22%。位置精度(RMSE)在0.44 m至1.57 m之间变化;从最准确到最不准确列出的方法是MLS semi ,TLS auto ,MLS manual ,MLS auto ,ALS ITDauto 和ALSITDvisual。我们得出结论,TLS和ALS的准确性适用于异种公园森林中的可操作城市树木测绘。 MLS manual 具有很高的潜力,但在操作树映射中进行手动测量是不可行的。在进一步的研究中应解决的挑战包括ALS ITDauto 的细分,以及MLS auto 的处理方法和用于树检测的数据收集。

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