Detecting the presence of natural forests using airborne laser scanning data

作     者：Marie-Claude Jutras-Perreault Terje Gobakken Erik Næsset Hans OleØrka Marie-Claude Jutras-Perreault;Terje Gobakken;Erik Naesset;Hans Ole Ørka

作者机构：Faculty of Environmental Sciences and Natural Resource ManagementNorwegian University of Life SciencesNMBUP.O.BoxNO-1432ÅsNorway 

出 版 物：《Forest Ecosystems》 (森林生态系统（英文版）)

年 卷 期：2023年第10卷第6期

页      面：668-680页

核心收录：

学科分类：0907[农学-林学] 09[农学] 0903[农学-农业资源与环境] 

基　　金：funding under the umbrella of ERA-NET Cofund ForestValue project NOBEL,“Novel business models and mechanisms for the sustainable supply of and payment for forest ecosystem services” ForestValue was funded by the European Union's Horizon 2020 research and innovation program(grant number 773324) Furthermore,the Norwegian Environment Agency funded the collection of the additional plots as a part of the project“Remote sensing-based mapping and monitoring of the forest ecosystem”(grant number 18087221) supported by the Norwegian Research Council(project number 297883) 

主　　题：Natural forest ALS Naturalness Vertical variables Horizontal variables Biodiversity Forest condition Ecosystem services 

摘      要：Centuries of forest exploitation have caused significant loss of natural forests in Europe,leading to a decline in populations for many *** prevent further loss in biodiversity,the Norwegian government has set a target of protecting 10%of the forested ***,recent data from the National Forest Inventory(NFI)reveals that less than 2%of Norway s forested area consists of natural *** identify forests with high conservation value,we used vertical and horizontal variables derived from airborne laser scanning(ALS)data,along with NFI plot *** study aimed to predict the presence of natural forests across three counties in southeastern Norway,using three different definitions:pristine,near-natural,and semi-natural *** forests are scarce,and their underrepresentation in field reference data can compromise the accuracy of the *** address this,we assessed the potential gain of including additional field data specifically targeting natural forests to achieve a better balance in the ***,we examined the impact of stratifying the data by dominant tree species on the performance of the *** results revealed that semi-natural forests were the most accurately predicted,followed by near-natural and pristine forests,with Matthews correlation coefficient values of 0.32,0.24,and 0.17,*** additional field data did not improve the ***,stratification by species improved the accuracy of predictions for near-natural and semi-natural forests,while reducing accuracy for pristine *** use of horizontal variables did not improve the *** study demonstrates the potential of ALS data in identifying forests with high conservation *** provides a basis for further research on the use of ALS data for the detection and conservation of natural forests,offering valuable insights to guide future forest preservation efforts.