Stand delineation based on laser scanning data and simulated annealing

被引:0
|
作者
Yusen Sun
Weifang Wang
Timo Pukkala
Xingji Jin
机构
[1] Northeast Forestry University,Key Laboratory of Sustainable Forest Ecosystem Management, Ministry of Education, School of Forestry
[2] University of Eastern Finland,undefined
来源
关键词
Segmentation; Airborne laser scanning; Combinatorial optimization; Metaheuristics;
D O I
暂无
中图分类号
学科分类号
摘要
The use of airborne laser scanning (LS) is increasing in forestry. Scanning can be conducted from manned aircrafts or unmanned aerial vehicles (UAV). The scanning data are often used to calculate various attributes for small raster cells. These attributes can be used to segment the forest into homogeneous areas, called segments, micro-stands, or, like in this study, stands. Delineation of stands from raster data is equal to finding the most suitable stand number for each raster cell, which is a combinatorial optimization problem. This study tested the performance of the simulated annealing (SA) metaheuristic in the delineation of stands from grids of UAV-LS attributes. The objective function included three criteria: within-stand variation of the LS attributes, stand area, and stand shape. The purpose was to create delineations that consisted of homogeneous stands with a low number of small stands and a regular and roundish stand shape. The results showed that SA is capable of producing stand delineations that meet these criteria. However, the method tended to produce delineations where the stands often consisted of disconnected parts and the stand borders were jagged. These problems were mitigated by using a mode filter on the grid of stand numbers and giving unique numbers for all disconnected parts of a stand. Three LS attributes were used in the delineation. These attributes described the canopy height, the height of the bottom of the canopy and the variation of echo intensity within 1-m2 raster cells. Besides, a texture variable that described the spatial variation of canopy height in the proximity of a 1-m2 raster cell was found to be a useful variable. Stand delineations where the average stand area was about one hectare explained more than 80% of the variation in canopy height.
引用
收藏
页码:1065 / 1080
页数:15
相关论文
共 50 条
  • [1] Stand delineation based on laser scanning data and simulated annealing
    Sun, Yusen
    Wang, Weifang
    Pukkala, Timo
    Jin, Xingji
    [J]. EUROPEAN JOURNAL OF FOREST RESEARCH, 2021, 140 (05) : 1065 - 1080
  • [2] Forest Stand Delineation Using a Hybrid Segmentation Approach Based on Airborne Laser Scanning Data
    Wu, Zhengzhe
    Heikkinen, Ville
    Hauta-Kasari, Markku
    Parkkinen, Jussi
    Tokola, Timo
    [J]. IMAGE ANALYSIS, SCIA 2013: 18TH SCANDINAVIAN CONFERENCE, 2013, 7944 : 95 - 106
  • [3] Airborne laser data for stand delineation and information extraction
    Koch, B.
    Straub, C.
    Dees, M.
    Wang, Y.
    Weinacker, H.
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2009, 30 (04) : 935 - 963
  • [4] Development of Forest Stand Volume Models Based on Airborne Laser Scanning Data
    Zeng, Weisheng
    Sun, Xiangnan
    Wang, Liuru
    Wang, Wei
    Pu, Ying
    [J]. Linye Kexue/Scientia Silvae Sinicae, 2021, 57 (02): : 31 - 38
  • [5] Delineation of Individual Tree Crowns for Mobile Laser Scanning Data
    Wu, Rosen
    Chen, Yiping
    Wen, Chenglu
    Wang, Cheng
    Li, Jonathan
    [J]. 2ND ISPRS INTERNATIONAL CONFERENCE ON COMPUTER VISION IN REMOTE SENSING (CVRS 2015), 2016, 9901
  • [6] Determination of stand density using data from airborne laser scanning
    Sterenczak, Krzysztof
    [J]. SYLWAN, 2013, 157 (08): : 607 - 617
  • [7] Comparison of stand volume predictions based on airborne laser scanning data versus aerial stereo images
    Schoneberg, Sebastian
    Nothdurft, Arne
    Nuske, Robert S.
    Ackermann, Joerg
    Saborowski, Joachim
    [J]. ALLGEMEINE FORST UND JAGDZEITUNG, 2016, 187 (1-2): : 1 - 13
  • [8] Predicting stand-thinning maturity from airborne laser scanning data
    Vastaranta, Mikko
    Holopainen, Markus
    Yu, Xiaowei
    Hyyppa, Juha
    Hyyppa, Hannu
    Viitala, Risto
    [J]. SCANDINAVIAN JOURNAL OF FOREST RESEARCH, 2011, 26 (02) : 187 - 196
  • [9] Road Manhole Cover Delineation Using Mobile Laser Scanning Point Cloud Data
    Yu, Yongtao
    Guan, Haiyan
    Li, Dilong
    Jin, Chunhua
    Wang, Cheng
    Li, Jonathan
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2020, 17 (01) : 152 - 156
  • [10] An Agent-Based Simulated Annealing Algorithm for Data Reduction
    Czarnowski, Ireneusz
    Jedrzejowicz, Piotr
    [J]. AGENT AND MULTI-AGENT SYSTEMS: TECHNOLOGIES AND APPLICATIONS, PT II, PROCEEDINGS, 2010, 6071 : 130 - 139