Remote sensing forest health assessment - a comprehensive literature review on a European level

被引:0
|
作者
Drechsel, Johannes [1 ,2 ]
Forkel, Matthias [2 ]
机构
[1] Landeshauptstadt Hannover, Dept Environm, Forestry Div, Hannover, Germany
[2] TUD Dresden Univ Technol, Fac Environm Sci Environm Remote Sensing, Helmholtzstr 10, DE-01069 Dresden, Germany
关键词
forest health assessment; remote sensing; PRISMA; literature review; Europe; BEETLE IPS-TYPOGRAPHUS; NORWAY SPRUCE; ALS DATA; TREES; UAV; LIDAR; DEFOLIATION; VITALITY; CLASSIFICATION; INDICATOR;
D O I
10.2478/forj-2024-0022
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Forest health assessments (FHA) have been carried out at European level since the 1980s in order to identify forest damage. The annual surveys are usually conducted without the use of remote sensing tools. However, the increasing availability of remote sensing observations potentially allows conduct FHA more wide-spread, more often, or in more comprehensive and comparable way. This literature review systematically evaluated 110 studies from 2015 to 2022 that use remote sensing for FHA in Europe. The purpose was to determine (1) which tree species were studied; (2) what types of damage were evaluated; (3) whether damage levels are distinguished according to the standard of the International Co-operative Program on Assessment and Monitoring of Air Pollution Effects on Forests (ICP-Forest); (4) the level of automation; and (5) whether the findings are applicable for a systematic FHA. The results show that spruce is the most studied tree species. Damage caused by bark beetles and drought were predominantly studied. In most studies only 2 damage levels are classified. Only four studies were able to perform a comprehensive FHA by identifying individual trees, classifying their species and damage levels. None of the studies investigated the suitability of their remote sensing approach for systematic forest health assessments. This result is surprising since programs such as SEMEFOR analyzed the potential of remote sensing for FHA already in the 1990s. We conclude that the availability of new satellite systems and advances in artificial intelligence and machine learning should be translated into FHA practice according to ICP standards.
引用
收藏
页码:14 / 39
页数:26
相关论文
共 50 条
  • [21] Remote sensing assessment of carbon storage by urban forest
    Kanniah, K. D.
    Muhamad, N.
    Kang, C. S.
    8TH INTERNATIONAL SYMPOSIUM OF THE DIGITAL EARTH (ISDE8), 2014, 18
  • [22] Assessment of forest restoration with multitemporal remote sensing imagery
    Cheng-Chien Liu
    Yi-Hsin Chen
    Mei-Heng Margaret Wu
    Chiang Wei
    Ming-Hsun Ko
    Scientific Reports, 9
  • [23] Assessment of forest restoration with multitemporal remote sensing imagery
    Liu, Cheng-Chien
    Chen, Yi-Hsin
    Wu, Mei-Heng Margaret
    Wei, Chiang
    Ko, Ming-Hsun
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [24] Remote sensing and forest inventory for wildlife habitat assessment
    McDermid, G. J.
    Hall, R. J.
    Sanchez-Azofeifa, G. A.
    Franklin, S. E.
    Stenhouse, G. B.
    Kobliuk, T.
    LeDrew, E. F.
    FOREST ECOLOGY AND MANAGEMENT, 2009, 257 (11) : 2262 - 2269
  • [25] SYSTEMATIC LITERATURE REVIEW REQUIREMENTS FOR HEALTH TECHNOLOGY ASSESSMENT IN EUROPEAN MARKETS
    Wright, C.
    Swanston, A.
    Nicholson, L.
    Marjenberg, Z.
    Pooley, N.
    VALUE IN HEALTH, 2024, 27 (06) : S253 - S253
  • [26] Remote Sensing Image Classification: A Comprehensive Review and Applications
    Mehmood, Maryam
    Shahzad, Ahsan
    Zafar, Bushra
    Shabbir, Amsa
    Ali, Nouman
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [27] TOPIC MODEL FOR REMOTE SENSING DATA: A COMPREHENSIVE REVIEW
    Zhu, Qiqi
    Wan, Jiangqin
    Zhong, Yanfei
    Guan, Qingfeng
    Zhang, Liangpei
    Li, Deren
    IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 1373 - 1376
  • [28] Remote Sensing Technologies for Enhancing Forest Inventories: A Review
    White, Joanne C.
    Coops, Nicholas C.
    Wulder, Michael A.
    Vastaranta, Mikko
    Hilker, Thomas
    Tompalski, Piotr
    CANADIAN JOURNAL OF REMOTE SENSING, 2016, 42 (05) : 619 - 641
  • [29] Review on Development of Forest Biomass Remote Sensing Satellites
    Cao Haiyi
    Qiu Xinyi
    He Tao
    ACTA OPTICA SINICA, 2022, 42 (17)
  • [30] Acquisition of Forest Attributes for Decision Support at the Forest Enterprise Level Using Remote-Sensing Techniques-A Review
    Surovy, Peter
    Kuzelka, Karel
    FORESTS, 2019, 10 (03):