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Charcoal Kiln Detection from LiDAR-derived Digital Elevation Models Combining Morphometric Classification and Image Processing Techniques
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
2017 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Sustainable development
Sustainable development according to the University's criteria is not relevant for the essay/thesis
Abstract [en]

This paper describes a unique method for the semi-automatic detection of historic charcoal production sites in LiDAR-derived digital elevation models. Intensified iron production in the early 17th century has remarkably influenced ways of how the land in Sweden was managed. Today, the abundance of charcoal kilns embedded in the landscape survives as cultural heritage monuments that testify about the scale forest management for charcoal production has contributed to the uprising iron manufacturing industry. An arbitrary selected study area (54 km2) south west of Gävle city served as an ideal testing ground, which is known to consist of already registered as well as unsurveyed charcoal kiln sites. The proposed approach encompasses combined morphometric classification methods being subjected to analytical image processing, where an image that represents refined terrain morphology was segmented and further followed by Hough Circle transfer function applied in seeking to detect circular shapes that represent charcoal kilns. Sites that have been identified manually and using the proposed method were only verified within an additionally established smaller validation area (6 km2). The resulting outcome accuracy was measured by calculating harmonic mean of precision and recall (F1-Score). Along with indication of previously undiscovered site locations, the proposed method showed relatively high score in recognising already registered sites after post-processing filtering. In spite of required continual fine-tuning, the described method can considerably facilitate mapping and overall management of cultural resources.

Place, publisher, year, edition, pages
2017. , v+33+appendixes p.
Keyword [en]
charcoal kilns, automatic feature extraction, LiDAR, morphometric classification, Hough Circle transfer
Keyword [lt]
medžio anglies krosnis, automatinis objektų išgavimas, LiDAR, morformetrinė klasifikacija, Hough apskritimo transformacija
Keyword [sv]
kolbottnar efter resmila, automatisk funktion extraktion, LiDAR, morfometrisk klassificering, Hough Circle överföring
National Category
History and Archaeology Remote Sensing Geosciences, Multidisciplinary
Identifiers
URN: urn:nbn:se:hig:diva-24374OAI: oai:DiVA.org:hig-24374DiVA: diva2:1111940
Subject / course
Geomatics
Educational program
Geomatics – master’s programme (one year) (swe or eng)
Presentation
2017-06-12, 11320, Kungsbäcksvägen, 802 67, Gävle, 17:16 (English)
Supervisors
Examiners
Available from: 2017-06-25 Created: 2017-06-19 Last updated: 2017-08-21Bibliographically approved

Open Access in DiVA

fulltext(4006 kB)50 downloads
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File name FULLTEXT01.pdfFile size 4006 kBChecksum SHA-512
90160880a809f1c94c765ce361a3d7df7de6d4044134978bfd55a49f8ff2e5c8da3b87b64ac4c413568a4cb05ed6be447b0ef666ac76289226eb4d015b6d77e5
Type fulltextMimetype application/pdf

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Land management, GIS
History and ArchaeologyRemote SensingGeosciences, Multidisciplinary

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • sv-SE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • de-DE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf