UAV-based forest health monitoring: a systematic review
Date
2022-07
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
In recent years, technological advances have led to the increasing use of unmanned
aerial vehicles (UAVs) for forestry applications. One emerging field for drone application is forest
health monitoring (FHM). Common approaches for FHM involve small-scale resource-extensive
fieldwork combined with traditional remote sensing platforms. However, the highly dynamic nature
of forests requires timely and repetitive data acquisition, often at very high spatial resolution, where
conventional remote sensing techniques reach the limits of feasibility. UAVs have shown that they
can meet the demands of flexible operation and high spatial resolution. This is also reflected in a
rapidly growing number of publications using drones to study forest health. Only a few reviews
exist which do not cover the whole research history of UAV-based FHM. Since a comprehensive
review is becoming critical to identify research gaps, trends, and drawbacks, we offer a systematic
analysis of 99 papers covering the last ten years of research related to UAV-based monitoring of
forests threatened by biotic and abiotic stressors. Advances in drone technology are being rapidly
adopted and put into practice, further improving the economical use of UAVs. Despite the many
advantages of UAVs, such as their flexibility, relatively low costs, and the possibility to fly below
cloud cover, we also identified some shortcomings: (1) multitemporal and long-term monitoring
of forests is clearly underrepresented; (2) the rare use of hyperspectral and LiDAR sensors must
drastically increase; (3) complementary data from other RS sources are not sufficiently being exploited;
(4) a lack of standardized workflows poses a problem to ensure data uniformity; (5) complex machine
learning algorithms and workflows obscure interpretability and hinders widespread adoption; (6) the
data pipeline from acquisition to final analysis often relies on commercial software at the expense of
open-source tools.
Description
CITATION: Ecke, S. et al. 2022. UAV-Based forest health monitoring : a systematic review. Remote Sensing, 14(13):3205, doi:10.3390/rs14133205.
The original publication is available at https://www.mdpi.com
The original publication is available at https://www.mdpi.com
Keywords
Forest monitoring, Remote sensing -- Equipment and supplies, Drone aircraft, Forest health, Technological innovations
Citation
Ecke, S. et al. 2022. UAV-Based forest health monitoring : a systematic review. Remote Sensing, 14(13):3205, doi:10.3390/rs14133205.