Continuous Cover Forestry and Remote Sensing: A Review of Knowledge Gaps, Challenges, and Potential Directions

被引:0
|
作者
Stoddart, Jaz [1 ]
Suarez, Juan [2 ]
Mason, William [2 ]
Valbuena, Ruben [3 ]
机构
[1] Bangor Univ, Sch Nat Sci, Bangor LL57 2DG, Wales
[2] Northern Res Stn, Forest Res, Agcy Forestry Commiss, Roslin EH25 9SY, Scotland
[3] Swedish Univ Agr Sci SLU, Dept Forest Resource Management, Div Forest Remote Sensing, Skogsmarksgrand 17, SE-90183 Umea, Sweden
关键词
Remote sensing; Continuous cover forestry; Biomass estimation; Individual tree growth models; Forest inventory; TREE SPECIES CLASSIFICATION; SCANNING POINT CLOUDS; LASER; HEIGHT; MODELS; REGENERATION; SILVICULTURE; ALGORITHMS; EXTRACTION; DIAMETER;
D O I
10.1007/s40725-023-00206-0
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Purpose of ReviewContinuous cover forestry (CCF) is a sustainable management approach for forestry in which forest stands are manipulated to create irregular stand structures with varied species composition. This approach differs greatly from the traditional approaches of plantation-based forestry, in which uniform monocultures are maintained, and thus, traditional methods of assessment, such as productivity (yield class) calculations, are less applicable. This creates a need to identify new methods to succeed the old and be of use in operational forestry and research. By applying remote sensing techniques to CCF, it may be possible to identify novel solutions to the challenges introduced through the adoption of CCF.Recent FindingsThere has been a limited amount of work published on the applications of remote sensing to CCF in the last decade. Research can primarily be characterised as explorations of different methods to quantify the target state of CCF and monitor indices of stand structural complexity during transformation to CCF, using terrestrial and aerial data collection techniques.SummaryWe identify a range of challenges associated with CCF and outline the outstanding gaps within the current body of research in need of further investigation, including a need for the development of new inventory methods using remote sensing techniques. We identify methods, such as individual tree models, that could be applied to CCF from other complex, heterogenous forest systems and propose the wider adoption of remote sensing including information for interested parties to get started.
引用
收藏
页码:490 / 501
页数:12
相关论文
共 50 条
  • [21] Present knowledge and future challenges in remote sensing for soil salinization monitoring: a review of bibliometric analysis
    Jiang, Zhuohan
    Ding, Jianli
    Li, Zhihui
    Liu, Junhao
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2025, 46 (01) : 247 - 272
  • [22] Remote Sensing Training in Ecology and Conservation challenges and potential
    Wegmann, Martin
    REMOTE SENSING IN ECOLOGY AND CONSERVATION, 2017, 3 (01) : 5 - 6
  • [23] Multimodal Classification of Remote Sensing Images: A Review and Future Directions
    Gomez-Chova, Luis
    Tuia, Devis
    Moser, Gabriele
    Camps-Valls, Gustau
    PROCEEDINGS OF THE IEEE, 2015, 103 (09) : 1560 - 1584
  • [24] Random forest in remote sensing: A review of applications and future directions
    Belgiu, Mariana
    Dragut, Lucian
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2016, 114 : 24 - 31
  • [25] Book review “Continuous Cover Forestry–Theories,Concepts,and Implementation” by Arne Pommerening
    Zhonghua Zhao
    Gangying Hui
    ForestEcosystems, 2023, 10 (06) : 774 - 775
  • [26] Assmann review: spatial ecology of rotational and continuous cover forestry in boreal landscapes
    Binkley, Dan
    EUROPEAN JOURNAL OF FOREST RESEARCH, 2025,
  • [27] Review of Crop Residue Fractional Cover Monitoring with Remote Sensing
    Zhang Miao
    Li Qiang-zi
    Meng Ji-hua
    Wu Bing-fang
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31 (12) : 3200 - 3205
  • [28] Remote Sensing of Snow Cover Using Spaceborne SAR: A Review
    Tsai, Ya-Lun S.
    Dietz, Andreas
    Oppelt, Natascha
    Kuenzer, Claudia
    REMOTE SENSING, 2019, 11 (12)
  • [29] Making Satellite Data Mainstream: Gaps, challenges, and opportunities for remote sensing experts
    Ravichandran, Aravind
    IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2024, 12 (04) : 373 - 376
  • [30] Review of Land Cover Classification Based on Remote Sensing Data
    Wang, Yi
    He, Ming-Yuan
    Xiang, Jie
    Zhou, Ze-Ming
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATION AND SENSOR NETWORKS (WCSN 2016), 2016, 44 : 751 - 756