Entwicklung der Waldinventur: von der Vollkluppierung zum virtuellen Wald

Griess, Verena C.; Brüggemann, Noëmi; Rosset, Christian; Bont, Leo Gallus (2023). Entwicklung der Waldinventur: von der Vollkluppierung zum virtuellen Wald Schweizerische Zeitschrift für Forstwesen, 174(6), pp. 367-371. Schweizerischer Forstverein 10.3188/szf.2023.0367

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Where entire forests were completely clumped for planning in the past, today drones are buzzing around. Developments for deriving forestry parameters from remote sensing data are progressing rapidly. Various projects are in progress to derive important forest planning parameters such as tree species, volume, and regeneration as well as for the operational application of remote sensing data in stand maps. Risk indication maps are also becoming increasingly important. In addition, research is being conducted into cheaper means of data collection. In the future, data collection, data processing, and data visualisation are to be combined in virtual forests and, through modelling of different management strategies and climate scenarios, support those responsible in making decisions relevant to management.

Item Type:	Journal Article (Original Article)
Division/Institute:	School of Agricultural, Forest and Food Sciences HAFL School of Agricultural, Forest and Food Sciences HAFL > Multifunctional Forest Management > Forest Ecosystem and Management
Name:	Griess, Verena C.; Brüggemann, Noëmi; Rosset, Christian0009-0001-6284-5135 and Bont, Leo Gallus
Subjects:	S Agriculture > SD Forestry
ISSN:	0036-7818
Publisher:	Schweizerischer Forstverein
Projects:	[UNSPECIFIED] TBk [UNSPECIFIED] waldmonitoring.ch
Language:	German
Submitter:	Christian Rosset
Date Deposited:	18 Dec 2023 14:40
Last Modified:	12 Jan 2024 10:33
Publisher DOI:	10.3188/szf.2023.0367
Related URLs:	https://www.e-periodica.ch/digbib/volume...
Uncontrolled Keywords:	forest inventory, remote sensing data, forest planning parameters, risk indication maps
ARBOR DOI:	10.24451/arbor.20745
URI:	https://arbor.bfh.ch/id/eprint/20745