Forest practitioners’ requirements for remote sensing-based canopy height, wood-volume, tree species, and disturbance products

Author:

Fassnacht Fabian Ewald1,Mager Christoph2,Waser Lars T34ORCID,Kanjir Urša5,Schäfer Jannika2ORCID,Buhvald Ana Potočnik6,Shafeian Elham2,Schiefer Felix2,Stančič Liza5,Immitzer Markus7ORCID,Dalponte Michele89,Stereńczak Krzysztof1011,Skudnik Mitja121314ORCID

Affiliation:

1. Remote Sensing and Geoinformatics, Freie Universität Berlin , Malteserstraße 74-100, 12249 Berlin , Germany

2. Department of Geography and Geoecology, Karlsruh Institute of Technology , Kaiserstr. 12, 76131 Karlsruhe , Germany

3. Department of Land Change Sciences , Swiss National Forest Inventory, , Zürcherstrasse 111, 8903 Birmensdorf , Switzerland

4. Swiss Federal Institute for Forest, Snow and Landscape Research WSL , Swiss National Forest Inventory, , Zürcherstrasse 111, 8903 Birmensdorf , Switzerland

5. Institute for Anthropological and Spatial Studies, Research Centre of the Slovenian Academy of Sciences and Arts , Novi trg 2, 1000 Ljubljana , Slovenia

6. Faculty of Civil and Geodetic Engineering, University of Ljubljana , Jamova Cesta 2, 1000 Ljubljana , Slovenia

7. Institute of Geomatics, University of Natural Resources and Life Sciences, Vienna (BOKU) , 1190 Vienna , Austria

8. Forest Ecology Unit , Research and Innovation Centre, , via E. Mach 1, 38098 San Michele all’Adige , Italy

9. Fondazione Edmund Mach , Research and Innovation Centre, , via E. Mach 1, 38098 San Michele all’Adige , Italy

10. Department of Geomatics, Forest Research Institute , Braci Leśnej 3 Street, Sękocin Stary, 05-090 Raszyn , Poland

11. IDEAS NCBR Sp. z.o.o. , Ul. Chmielna 69, 00-801 Warszawa , Poland

12. Slovenian Forestry Institute , Večna pot 2, 1000 Ljubljana , Slovenia

13. Department of Forestry and Renewable Forest Resources , Biotechnical Faculty, , Večna pot 83, 1000 Ljubljana , Slovenia

14. University of Ljubljana , Biotechnical Faculty, , Večna pot 83, 1000 Ljubljana , Slovenia

Abstract

Abstract Despite decades of development, the uptake of remote sensing-based information products in the forestry sector is still lagging behind in central and southern Europe. This may partly relate to a mismatch of the developed remote sensing products and the requirements of potential users. Here, we present the results of a questionnaire survey in which we questioned 355 forest practitioners from eight central and southern European countries. We aimed to learn about forest practitioners' technical requirements for four remote sensing-based information products, including information on tree species, canopy height, wood volume/biomass, and forest disturbances. We asked for practitioners’ preferences with respect to thematic and spatial detail as well as the maximal acceptable error and the temporal frequency with which the information layers would be needed. We then examined whether the education, age, and professional background affect the requirements. Preferences with respect to spatial and thematic detail were comparably diverse while more homogenous patterns could be observed for demands with respect to errors and temporal frequency. Our results indicate that for some information products such as canopy height maps, existing remote sensing technology, and workflows can match all demands of practitioners. Remotely sensed information on forest disturbances partly fulfils the demands of the practitioners while for products related to tree species and wood volume/biomass the level of thematic detail and the accuracy of the products demanded by practitioners in central and southern Europe is not yet fully matched. We found no statistically significant differences between the demographic groups examined. The findings of this study improve our understanding of matches and mismatches of the technical requirements of practitioners for remote sensing-based information products.

Funder

German Academic Exchange Service

INSANE

Slovenian Research Agency Programme

ROVI project

Forest Biology, Ecology and Technology

Publisher

Oxford University Press (OUP)

Reference69 articles.

1. Tree species classification using Sentinel-2 imagery and Bayesian inference;Axelsson;Int J Appl Earth Obs Geoinf,2021

2. A questionnairebased review of the operational use of remotely sensed data by national forest inventories;Barret;Remote Sens Environ,2016

3. Tree species diversity does not compromise stem quality in major European forest types;Benneter;For Ecol Manag,2018

4. Mapping tree species proportions from satellite imagery using spectral–spatial deep learning;Bolyn;Remote Sens Environ,2022

5. Satellite remote sensing of forest resources: three decades of research development;Boyd;Prog Phys Geogr Earth Environ,2005

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