| 基于仿真大光斑激光雷达和多层感知器的森林地上生物量估算模型构建 |
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| 引用本文： | 许昌建,刘迎春,左丽君,李建更,张婷,韩路萌,方宇,张尹,王天.基于仿真大光斑激光雷达和多层感知器的森林地上生物量估算模型构建[J].林业资源管理,2021(1):50-60. |
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| 作者姓名： | 许昌建 刘迎春 左丽君 李建更 张婷 韩路萌 方宇 张尹 王天 |
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| 作者单位： | 国家林业和草原局调查规划设计院,北京 100714;北京工业大学 信息学部,北京 100124;国家林业和草原局调查规划设计院,北京 100714;中国科学院空天信息研究院,北京 100094;北京工业大学 信息学部,北京 100124 |
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| 基金项目： | 国家自然科学基金项目(31400426);国家水体污染控制与治理科技重大专项(2017ZX07101001)。 |
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| 摘 要： | 森林是全球重要的陆地生态系统,各国普遍采用地面样地调查的方法评估其资源量和生物量。随着激光雷达技术的发展,采用星载大光斑激光雷达估算大区域森林地上生物量将成为另一种选择。为探索利用大光斑激光雷达估算森林地上生物量的方法,提出了一种基于仿真大光斑激光雷达和多层感知器的森林地上生物量估算模型。比较仿真大光斑激光雷达波形参数13种组合拟合森林地上生物量的效果后,认为多层感知器的估测精度高于多元线性回归。与样地实测地上生物量相比,多元线性回归估测结果的偏差范围为-34.96~23.28t/hm2,多层感知器估测结果的偏差范围更小,为-19.09~20.19t/hm2。因此,多层感知器估测森林地上生物量的效果优于多元线性回归。
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| 关 键 词： | 地上生物量 激光雷达 仿真波形 多层感知器 |
Estimation on Forest Above-Ground Biomass Based on Simulated Large-Footprint LiDAR and Multi-Layer Perceptron |
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| XV Changjian,LIU Yingchun,ZUO Lijun,LI Jiangeng,ZHANG Ting,HAN Lumeng,FANG Yu,ZHANG Yin,WANG Tian.Estimation on Forest Above-Ground Biomass Based on Simulated Large-Footprint LiDAR and Multi-Layer Perceptron[J].Forest Resources Management,2021(1):50-60. |
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| Authors: | XV Changjian LIU Yingchun ZUO Lijun LI Jiangeng ZHANG Ting HAN Lumeng FANG Yu ZHANG Yin WANG Tian |
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| Institution: | (Academy of Inventory and Planning,National Forestry and Grassland Administration,Beijing 100714,China;Faculty of Information Technology,Beijing University of Technology,Beijing 100124,China;Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China) |
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| Abstract: | Forests are important global terrestrial ecosystems.Sample survey is a commonly used method by countries to assess their forest resources and biomass.With the development of LiDAR technology,spaceborne large-footprint ladar become an option to estimate forest above-ground biomass(AGB)in large areas.In order to develop the method to estimate forest AGB with large-footprint LiDAR,the study proposes an AGB estimation model based on simulated large-footprint LiDAR and multi-layer perceptron.Based on 13 groups of LiDAR waveform parameters,the multi-layer perceptron achieves higher accuracy than multiple linear regression to estimate AGB.Compared with the field measured AGB,the deviation range of the estimated AGB from the multiple linear regression is between-34.96 to 23.28 t/hm2 and the estimated deviation of the multi-layer perceptron is between-19.09 to 20.19 t/hm2.Therefore,multi-layer perceptron is better than multiple linear regression in estimating forest AGB. |
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| Keywords: | above-ground biomass LiDAR simulated waveform multi-layer perceptron |
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