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Information extraction and system construction of digital forest system based on multisource remote sensing data

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing Normal University, Beijing 100875, China

  • Email：xiedonghui@bnu.edu.cn
  • Introduction：谢东辉， 研究方向为定量遥感机理和遥感应用。E-mail：xiedonghui@bnu.edu.cn
XIE Donghui1,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing Normal University, Beijing 100875, China

  • Email：yili@mail.bnu.edu.cn
  • Introduction：李益， 研究方向为植被定量遥感。E-mail： yili@mail.bnu.edu.cn
LI Yi1*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing Normal University, Beijing 100875, China

ZHOU Kun1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing Normal University, Beijing 100875, China

ZHANG Zhixiang1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing Normal University, Beijing 100875, China

JIN Lin1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing Normal University, Beijing 100875, China

YAN Guangjian1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing Normal University, Beijing 100875, China

MU Xihan1,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

LI Wenhang2,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

FENG Gongyao2

Resümee

Digital forestry is the foundation of forestry informationization and modernization, which can help management with scientific programming, scientific management, and scientific decision. With the development of 3S (GIS, RS, and GNSS) technology, improving the level of digital forestry becomes feasible, especially for the monitoring scale from forest-compartment level to single-tree level by using high spatial- and spectral-resolution remote sensing data and Light Detection And Ranging (LiDAR). This paper aims to develop a forestry digital system by combining the advantages of remote sensing and GIS technology, which can improve the precision management ability of forest farm.Saihanba Mechanical Forest Farm in Hebei Province, China is taken as the research area, and airborne data, including LiDAR, CCD image, and hyperspectral image, are used to study single tree segmentation and classification methods. First, an algorithm combined water shed and Connection Center Evolution methods is applied to segment each single tree based on the airborne LiDAR scanner (ALS). Then, the random forest algorithm is applied to classify the tree species of each single tree based on the combination of the 50 characteristics from ALS, CCD, and hyperspectral image. The 3D model reconstruction is also examined by using terrestrial laser scanning data, with the procedure of branch reconstruction and leaf addition. Forest scenarios are reconstructed based on each single tree model. Finally, WebGIS technology is used to develop a forestry digital system with the functions of data storage, management, query, analysis, and visualization.More than 9706 thousand single trees within the airborne flight area of 270 km2 are segmented and classified. Combined with the survey data of ground quadrats, the single tree segmentation accuracy can reach over 0.6 matching rate, and the single tree classification accuracy of four typical tree species in the study area can reach more than 97%.The information of single tree, including location, tree height, crown breadth, and the structures of branches and leaves, are extracted based on airborne and field data, which can help analyze the multiscale forest characteristics from organs (branches and leaves)-single tree-region scales. On this basis, this paper explores the forestry digitization method based on single tree information and develops a digital forestry system using WebGIS technology. The system preliminarily completes the functions of storage, management, query, analysis, and visualization of relevant data in the study area, providing reliable basic data for forest management and decision-making planning.

Schlüsselwort

remote sensing;digital forestry;lidar;hyperspectral image;tree segmentation;classification;3D reconstruction

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