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Predicting stand age in managed forests using National Forest Inventory field data and airborne laser scanning

Forest Ecosystems 2020年第3期7卷 579-589页

作者： Matti Maltamo Hermanni Kinnunen Annika Kangas lauri korhonen University of Eastern Finland School of Forest SciencesP.O.Box 11180101JoensuuFinland Natural Resources Institute Finland Bioeconomy and EnvironmentP.O.Box 6880100JoensuuFinland

Background: The aim of this study was to construct a nationwide stand age model by using National Forest Inventory(NFI) data and nationwide airborne laser scanning(ALS) data. In plantation forestry, age is usually *** this is not the case in boreal managed forests, age is still seldom predicted in forest management *** age accurately in situ is also very laborious. On the other hand, tree age is one of the accurately measured sample tree attributes in NFI field data. Many countries also have a nationwide coverage of airborne laser scanning(ALS) data. In this study, we merged these data sources and constructed a nationwide, area-based model for stand ***: While constructing the model, we omitted old forests from the data, since the correlation between ALS height metrics and stand age diminished at stands with age > 100 years. Additionally, the effect of growth conditions was considerable, so we also utilized different geographical and NFI variables such as site fertility and soil type in the modeling. The resultant nationwide model for the stand age of managed forests yielded a root mean square error(RMSE) of about 14 years. The model could be improved further by additional forest structure variables, but such information may not be available in ***: The results showed that the prediction of stand age by ALS, geographical and NFI information was challenging, but stil possible with moderate success. This study is an example of the joint use of NFI and nationwide ALS data and re-use of NFI data in research.

关键词： Forest stock age LiDAR NFI Nationwide model Growth conditions

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Inventory of aspen trees in spruce dominated stands in conserva-tion area

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Forest Ecosystems 2015年第2期2卷 143-154页

作者： Matti Maltamo Annukka Pesonen lauri korhonen Jari Kouki Mikko Vehmas Kalle Eerik?inen University of Eastern Finland School of Forest Science Blom Kartta Oy City of Joensuu Natural Resources Institute Finland Joensuu Unit

Background： The occurrence of aspen trees increases the conservation value of mature conifer dominated forests. Aspens typically occur as scattered individuals among major tree species, and therefore the inventory of aspens is challenging. Methods： We characterized aspen populations in a boreal nature reserve using diameter distribution, spatial pattern, and forest attributes： volume, number of aspens, number of large aspen stems and basal area median diameter. The data were collected from three separate forest stands in Koli National Park, eastern Finland. At each site, we measured breast height diameter and coordinates of each aspen. The comparison of inventory methods of aspens within the three stands was based on simulations with mapped field data. We mimicked stand level inventory by locating varying numbers of fixed area circular plots both systematically and randomly within the stands. Additionally, we also tested if the use of airborne laser scanning （ALS） data as auxiliary information would improve the accuracy of the stand level inventory by applying the probability proportional to size sampling to assist the selection of field plot locations. Results： The results showed that aspens were always clustered, and the diameter distributions indicated different stand structures in the three investigated forest stands. The reliability of the volume and number of large aspen trees varied from relative root mean square error figures above 50% with fewer sample plots （5-10） to values of 25%-50% with ]0 or more sample plots. Stand level inventory estimates were also able to detect spatial pattern and the shape of the diameter distribution. In addition, ALS-based auxiliary information could be useful in guiding the inventories, but caution should be used when applying the ALS-supported inventory technique. Conclusions： This study characterized European aspen populations for the purposes of monitoring and management of boreal conservation areas. Our results suggest tha

关键词： Diameter distribution Historical continuity Inventory LiDAR Populus tremula L Simulation Spatial arrangement Stand characteristics

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考虑目标光谱差异的机载离散激光雷达叶面积指数反演

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遥感学报 2020年第12期24卷 1450-1463页

作者：田罗屈永华 korhonen lauri Korpela Ilkka Heiskanen Janne 北京师范大学遥感科学国家重点实验室北京100875 北京师范大学地理科学学部遥感与工程研究院北京市陆表遥感数据产品工程技术研究中心北京100875 东芬兰大学森林科学学院东芬兰70210 赫尔辛基大学地理科学学部赫尔辛基00100 赫尔辛基大学大气与地球系统研究所赫尔辛基00100

利用间隙率模型反演LAI(Leaf Area Index),需要同时获取冠层间隙率和消光系数,后者与冠层叶倾角分布有关。基于点云数量构建激光雷达穿透指数LPI(LiDAR Penetration Index),用以代替冠层间隙率GF(Gap Fraction),并利用间隙率模型反演冠... 详细信息

利用间隙率模型反演LAI(Leaf Area Index),需要同时获取冠层间隙率和消光系数,后者与冠层叶倾角分布有关。基于点云数量构建激光雷达穿透指数LPI(LiDAR Penetration Index),用以代替冠层间隙率GF(Gap Fraction),并利用间隙率模型反演冠层LAI是利用LiDAR PCD(LiDAR Point Cloud Data)数据反演冠层LAI主要思路。冠层和背景的光谱差异是影响PCD数据中冠层和背景点云数量的重要因素,因此从LPI到GF的校正需要获取背景和冠层的后向散射系数比(μ=ρg/ρv)。本文基于PCD数据中点云强度进行μ值获取,用以实现LPI到GF的校正;在假设区域内叶倾角满足椭球形叶倾角分布的基础上,利用样地尺度下的多角度GF,采用有约束的非线性最优化方法获取椭球形叶倾角分布参数χ,实现冠层消光系数的获取;最后利用间隙率模型实现基于PCD数据的LAI反演。本文探讨了基于PCD数据进行冠层LAI反演时,样地尺度Rxy_Tile、样方尺度Rxy_Plot以及进行背景和冠层分割的高度阈值Ht对模型的影响。结果显示,由于区域内地衣植被广泛覆盖,基于点云强度的μ值接近1,符合区域特点;经过μ值校正后的GF对冠层间隙率具有较好的反映能力(R2=0.78,RMSE=0.09);对于优势种明显的区域,基于样地尺度内多角度GF的χ值反演受样地内冠间大间隙的影响,选择合适的样地尺度能够减小LAI反演过程中的系统性误差;结合地面参考数据,确定的最优Rxy_Tile、Rxy_Plot和Ht分别为950 m、10 m和2.6 m,在此基础上反演的LAI与地面测量数据具有高度的一致性(R2=0.84,RMSE=0.51);与Rxy_Plot相比,基于间隙率模型的LAI反演对Ht的选择更为敏感。

关键词：遥感叶面积指数 LiDAR 间隙率消光系数目标光谱特性

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