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Bridging theory and implementation - Testing an abstract classification system for practical mapping by field survey and 3D aerial photographic interpretation
Stockholm University, Faculty of Science, Department of Physical Geography.
Number of Authors: 32019 (English)In: Norsk Geografisk Tidsskrift, ISSN 0029-1951, E-ISSN 1502-5292, Vol. 73, no 5, p. 301-317Article in journal (Refereed) Published
Abstract [en]

The abstract classification system Nature in Norway (NiN) has detailed ecological definitions of a high number of ecosystem units, but its applicability in practical vegetation mapping is unknown because it was not designed with a specific mapping method in mind. To investigate this further, two methods for mapping - 3D aerial photographic interpretation of colour infrared photos and field survey - were used to map comparable neighbouring sites of 1 km(2) in Hvaler Municipality, south-eastern Norway. The classification accuracy of each method was evaluated using a consensus classification of 160 randomly distributed plots within the study sites. The results showed an overall classification accuracy of 62.5% for 3D aerial photographic interpretation and 82.5% for field survey. However, the accuracy varied for the ecosystem units mapped. The classification accuracy of ecosystem units in acidic, dry and open terrain was similar for both methods, whereas classification accuracy of calcareous units was highest using field survey. The mapping progress using 3D aerial photographic interpretation was more than two times faster than that of field survey. Based on the results, the authors recommend a method combining 3D aerial photographic interpretation and field survey to achieve effectively accurate mapping in practical applications of the NiN system.

Place, publisher, year, edition, pages
2019. Vol. 73, no 5, p. 301-317
Keywords [en]
classification, colour infrared photos, mapping accuracy, Nature in Norway (NiN), vegetation mapping
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-179588DOI: 10.1080/00291951.2020.1717595ISI: 000512583400001OAI: oai:DiVA.org:su-179588DiVA, id: diva2:1416440
Available from: 2020-03-23 Created: 2020-03-23 Last updated: 2020-03-23Bibliographically approved

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