Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Impact of error: Implementation and evaluation of a spatial model for analysing landscape configuration
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
2012 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Quality and error assessment is an essential part of spatial analysis which with the increasingamount of applications resulting from today’s extensive access to spatial data, such as satelliteimagery and computer power is extra important to address. This study evaluates the impact ofinput errors associated with satellite sensor noise for a spatial method aimed at characterisingaspects of landscapes associated with the historical village structure, called the HybridCharacterisation Model (HCM), that was developed as a tool to monitor sub goals of theSwedish Environmental Goal “A varied agricultural landscape”. The method and errorsimulation method employed for generating random errors in the input data, is implemented andautomated as a Python script enabling easy iteration of the procedure. The HCM is evaluatedqualitatively (by visual analysis) and quantitatively comparing kappa index values between theoutputs affected by error. Comparing the result of the qualitative and quantitative evaluationshows that the kappa index is an applicable measurement of quality for the HCM. Thequalitative analysis compares impact of error for two different scales, the village scale and thelandscape scale, and shows that the HCM is performing well on the landscape scale for up to30% error and on the village scale for up to 10% and shows that the impact of error differsdepending on the shape of the analysed feature. The Python script produced in this study couldbe further developed and modified to evaluate the HCM for other aspects of input error, such asclassification errors, although for such studies to be motivated the potential errors associatedwith the model and its parameters must first be further evaluated.

Place, publisher, year, edition, pages
2012. , 47 p.
Series
BA, 14
Keyword [en]
remote sensing, error assessment, error, spatial analysis, python, siljan, error matrix, kappa
National Category
Other Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-79214OAI: oai:DiVA.org:su-79214DiVA: diva2:548147
Presentation
2012-03-16, 16:56 (English)
Uppsok
Life Earth Science
Supervisors
Examiners
Available from: 2012-09-20 Created: 2012-08-29 Last updated: 2012-09-20Bibliographically approved

Open Access in DiVA

Impact of error(8489 kB)520 downloads
File information
File name FULLTEXT01.pdfFile size 8489 kBChecksum SHA-512
8561c8f87d6bf91ca447b14aac763261d18f7831932ab77e2cf22150db0e7d1fa191f93a978bbdcca256936c0b5f52e8052344cd020f0b896ab938b1a29d923e
Type fulltextMimetype application/pdf

By organisation
Department of Physical Geography and Quaternary Geology
Other Earth and Related Environmental Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 520 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 309 hits
CiteExportLink to record
Permanent link

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