Correlations, distributions, and trends in forest inventory errors and their effects on forest planning

被引:30
作者
Makinen, Antti [1 ]
Kangas, Annika [1 ]
Mehtatalo, Lauri [2 ]
机构
[1] Univ Helsinki, Dept Forest Resource Management, FIN-00014 Helsinki, Finland
[2] Univ Joensuu, Fac Forest Sci, FIN-80101 Joensuu, Finland
关键词
GROWTH; UNCERTAINTY; STRATEGIES; PREDICTION; SYSTEMS;
D O I
10.1139/X10-057
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Errors in forest planning data are known to have various undesired effects, which have been examined previously by simulating their impact on forest planning systems. In most cases, the simulation of forest inventory errors has been simplified by assuming the error distribution to be Gaussian, possibly with a constant bias, and neglecting possible correlations between the errors in various attributes. The first aim here was to examine the distributions, correlations, and trends in errors when using alternative forest inventory methods, and the second was to analyse how different error simulation methods affect the estimated economic losses caused by suboptimal harvest timing on account of errors. We found that the errors were not normally distributed, had notable trends, and showed significant correlations between the errors for the various attributes. The most important factor affecting the inoptimality losses was the powerful tendency to underestimate the growing stock properties of mature stands. The error simulation method clearly makes a difference when analysing the effects of errors, and it is therefore important to use a simulation method that generates realistic errors.
引用
收藏
页码:1386 / 1396
页数:11
相关论文
共 50 条
  • [31] Potential of using data assimilation to support forest planning
    Saad, Rami
    Eyvindson, Kyle
    Gong, Peichen
    Lamas, Tomas
    Stahl, Goran
    CANADIAN JOURNAL OF FOREST RESEARCH, 2017, 47 (05) : 690 - 695
  • [32] Assessment of bias due to random measurement errors in stem volume growth estimation by the Swedish National Forest Inventory
    Suty, Nicole
    Nystrom, Kenneth
    Stahl, Goran
    SCANDINAVIAN JOURNAL OF FOREST RESEARCH, 2013, 28 (02) : 174 - 183
  • [33] Isolating spatial effects on beta diversity to inform forest landscape planning
    Holland, Jeffrey D.
    LANDSCAPE ECOLOGY, 2010, 25 (09) : 1349 - 1362
  • [34] Effects of national forest inventory plot location error on forest carbon stock estimation using k-nearest neighbor algorithm
    Jung, Jaehoon
    Kim, Sangpil
    Hong, Sungchul
    Kim, Kyoungmin
    Kim, Eunsook
    Im, Jungho
    Heo, Joon
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2013, 81 : 82 - 92
  • [35] Quantify and account for field reference errors in forest remote sensing studies
    Persson, Henrik Jan
    Ekstrom, Magnus
    Stahl, Goran
    REMOTE SENSING OF ENVIRONMENT, 2022, 283
  • [36] A random forest model for basal area increment predictions from national forest inventory data
    Jevsenak, Jernej
    Skudnik, Mitja
    FOREST ECOLOGY AND MANAGEMENT, 2021, 479
  • [37] Inference on forest attributes and ecological diversity of trees outside forest by a two-phase inventory
    Marchetti, Marco
    Garfi, Vittorio
    Pisani, Caterina
    Franceschi, Sara
    Marcheselli, Marzia
    Corona, Piermaria
    Puletti, Nicola
    Vizzarri, Matteo
    di Cristofaro, Marco
    Ottaviano, Marco
    Fattorini, Lorenzo
    ANNALS OF FOREST SCIENCE, 2018, 75 (02)
  • [38] Stochastic goal programming in forest planning
    Eyvindson, Kyle
    Kangas, Annika
    CANADIAN JOURNAL OF FOREST RESEARCH, 2014, 44 (10) : 1274 - 1280
  • [39] Accounting for climate change in a forest planning stochastic optimization model
    Garcia-Gonzalo, Jordi
    Pais, Cristobal
    Bachmatiuk, Joanna
    Weintraub, Andres
    CANADIAN JOURNAL OF FOREST RESEARCH, 2016, 46 (09) : 1111 - 1121
  • [40] Forest site classification and grading using mixed-variables clustering and nonlinear mixed-effects modeling based on forest inventory data
    Wu, Biyun
    Lei, Xiangdong
    Xu, Qigang
    Qin, Yangping
    Duan, Guangshuang
    He, Xiao
    Ammer, Christian
    Pierick, Kerstin
    Sharma, Ram P.
    Lei, Yuancai
    Guo, Hong
    Gao, Wenqiang
    Li, Yutang
    FORESTRY, 2025,