Tree mapping using airborne, terrestrial and mobile laser scanning - A case study in a heterogeneous urban forest

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• 作者：Markus Holopainen ; Ville Kankare ; Mikko Vastaranta ; Xinlian Liang ; Yi Lin ; Matti Vaaja ; Xiaowei Yu ; Juha Hyypp盲 ; Hannu Hyypp盲 ; Harri Kaartinen ; Antero Kukko ; Topi Tanhuanp盲盲 ; Petteri Alho
• 关键词：Airborne laser scanning ; Mobile laser scanning ; Tree detection ; Terrestrial laser scanning ; Urban forestry
• 刊名：Urban Forestry Urban Greening
• 出版年：2013
• 年：2013
• 卷：12
• 期：4
• 页码：546-553
• 全文大小：1536 K

文摘

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 (ALS_ITDauto or ALS_ITDvisual) and manual or automatic measurements of TLS and MLS (TLS_auto, MLS_auto, MLS_manual, MLS_semi). Our results showed that the best methods for tree detection were TLS_auto and MLS_manual, 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 MLS_semi, TLS_auto, MLS_manual, MLS_auto, ALS_ITDauto and ALS_ITDvisual. We conclude that the accuracies of TLS and ALS were applicable for operational urban tree mapping in heterogeneous park forests. MLS_manual shows high potential but manual measurements are not feasible in operational tree mapping. Challenges that should be solved in further studies include ALS_ITDauto oversegmentation as well as MLS_auto processing methodologies and data collection for tree detection.