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
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