SWS Academic Research eLibraryEarth & Planetary Sciences

Scholarly record

MONITORING AND ASSESSMENT OF STORM DAMAGE TO FORESTS USING THE PHOTOGRAMMETRIC METHOD

Natalja Liba, Kaupo Kokamägi, Rauno Künnapuu, Kärt Metsoja

First published: 2023-10-01https://doi.org/10.5593/sgem2023/2.1/s10.38View metrics

Abstract

The escalating intensity of climate change-induced storms necessitates efficient methods for surveying storm-damaged forests. This study conducted in Estonia employed Unmanned Aerial Vehicles (UAVs), equipped with compact cameras, to assess damage over a 16 square kilometer storm-affected area. We created digital surface models (DSMs) and orthophoto mosaics using two types of drones - a fixedwing and a multirotor. While both types had their distinct advantages depending on the terrain, a 70% x 70% overlap of images was found to be inadequate for proper alignment of images in heavily forested areas. Comparing drone-generated DSMs with existing DSM data was a quick method for locating storm-damaged areas, although not ideal for accurately calculating their extent. It was also found that orthophoto mosaics with a 0.2 m resolution were sufficient for damage analysis.

Publication Impact Profile

PlumX
  • Citations
  • Scopus - Citation Indexes: 1
  • Captures
  • Mendeley - Readers: 1

Publication details

Title
MONITORING AND ASSESSMENT OF STORM DAMAGE TO FORESTS USING THE PHOTOGRAMMETRIC METHOD
Authors
Natalja Liba, Kaupo Kokamägi, Rauno Künnapuu, Kärt Metsoja
Proceedings
SGEM International Multidisciplinary Scientific GeoConference- EXPO Proceedings; 23rd SGEM International Multidisciplinary Scientific GeoConference Proceedings 2023, Informatics, Geoinformatics and Remote Sensing, Vol 23, Issue 2.1.
Publisher
STEF92 Technology
Year
2023
Pages
299-306
SWS Citekey
Liba202310299306
ISSN
1314-2704
ISBN
978-619-7603-57-6
Language
en
Publication type
Conference Paper
Proceedings contents
Open official contents
Keywords
References10
  1. Romagnoli F, Cadei A, Costa M, Marangon D, Pellegrini G, Nardi D, Masiero M, Secco L, Grigolato S, Lingua E, Picco L. Windstorm impacts on European forest-related systems: An interdisciplinary perspective. Forest Ecology and Management. 2023 Aug 1;541:121048.DOI: 10.1016/j.foreco.2023.121048

  2. Augustynczik, A. L., Dobor, L., & Hlasny, T. (2021). Controlling landscape-scale bark beetle dynamics: Can we hit the right spot?. Landscape and Urban Planning, 209, 104035. DOI: 10.1016/j.landurbplan.2020.104035

  3. Gaia V. L., Saverio F, Tania, G. C, Francesco P, Dario P. Satellite open data to monitor forest damage caused by extreme climate-induced events: a case study of the Vaia storm in Northern Italy, Forestry: An International Journal of Forest Research, Volume 94, Issue 3, Pages 407�416, DOI: 10.1093/forestry/cpaa043, 2021

  4. Tang, L., Shao, G. Drone remote sensing for forestry research and practices. J. For. Res. 26, 791�797, 2015. DOI: 10.1007/s11676-015-0088-y

  5. Brovkina, O., Cienciala, E., Surovy, P., & Janata, P. (2018). Unmanned aerial vehicles (UAV) for assessment of qualitative classification of Norway spruce in temperate forest stands. Geo-spatial information science, 21(1), 12-20. DOI: 10.1080/10095020.2017.1416994

  6. Minarik R, Langhammer J Use of a multispectral uav photogrammetry for detection and tracking of forest disturbance dynamics. Int Arch PhotogrammRemote Sens Spat Inf Sci 41, 2016. DOI: 10.5194/isprsarchives-XLI-B8-711-2016 https://doi.org/10.5194/isprs-archives-xli-b8-711-2016

  7. Mokros M, Vybostok J, Merganic J, Hollaus M, Barton I, Koren M, Tomastik J, Cernava J. Early stage forest windthrow estimation based on unmanned aircraft system imagery. Forests. 2017 Sep;8(9):306.DOI: 10.3390/f8090306

  8. Schiefer, F., Kattenborn, T., Frick, A., Frey, J., Schall, P., Koch, B., & Schmidtlein, S. (2020). Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks. ISPRS Journal of Photogrammetry and Remote Sensing, 170, 205-215. DOI: 10.1016/j.isprsjprs.2020.10.015

  9. Kokamagi K; Kunnapuu R; Liba N Jarvselja metsade tormikahjustuste seire mehitamata ohusoidukitega (Forest storm damage monitoring in Jarvselja, Estonia with unmanned aerial vehicles) Forestry Studies / Metsanduslikud Uurimused, 76, 99?105. 2022. DOI: 10.2478/fsmu-2022-0007

  10. Rahu, O., & Siim, K. Jarvselja oppe-ja katsemetskonna tormikahjude hindamine fotogrammmeetriliste meetoditega (Magistritoo, Eesti Maaulikool) 2022.

View or Download full articleAccess options
Full paper accessChoose SWS login, librarian support, or instant article download.

SWS access login

Login as SWS Scientific Committee

Authors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.

For librarian assistance: [email protected]

Purchase Instant Access

48-hour online accessComing soon
Online-only accessComing soon
Download the full article in PDF formatEUR 35
  • Article can be downloaded after successful payment.
  • Article may be used according to SWS library access terms.
  • Article cannot be redistributed.
Get full paper

Back to publication list