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Estimating stand volume of Xylosma racemosum forest based on texture parameters and derivative texture indices of ALOS imagery
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics.
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2014 (English)In: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, ISSN 1000-1298, Vol. 45, no 7, 245-254 p.Article in journal (Refereed) Published
Abstract [en]

The Xylosma racemosum forest located in Huairou District of Beijing was chosen as research objects, texture parameters as well as derivative texture indices of different window sizes from ALOS fusion imagery with resolution of 2.5 m were measured. Stepwise multiple regression models were developed to describe the relationship between textures (including texture parameters and derivative texture indices) and field measurements of stand volume. The main objective was to compare estimation accuracy between model established by texture parameters and that by derivative texture indices, select the most effective Xylosma racemosum stand volume estimate model and select the most effective window size. Results indicate that the value of adjusted R2 of fitting models established by derivative texture indices were better than those of texture parameters at the same window size, the value of adjusted R2 of stand volume model could be improved significantly by combination of texture parameters and derivative texture indices at the same window size, the optimal estimation model of Xylosma racemosum stand volume was obtained when all of the texture parameters and derivative texture indices of all window sizes were introduced into stepwise multiple regression, 11×11 was the optimal window size with the largest adjusted R2 for fitting Xylosma racemosum stand volume by texture parameters and derivative texture indices generated at one single window size.

Place, publisher, year, edition, pages
2014. Vol. 45, no 7, 245-254 p.
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:kth:diva-161023DOI: 10.6041/j.issn.1000-1298.2014.07.038Scopus ID: 2-s2.0-84904385517OAI: oai:DiVA.org:kth-161023DiVA: diva2:794887
Note

QC 20150313

Available from: 2015-03-13 Created: 2015-03-06 Last updated: 2015-03-13Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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