File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Isolating individual trees in a savanna woodland using small footprint lidar data

TitleIsolating individual trees in a savanna woodland using small footprint lidar data
Authors
Issue Date2006
Citation
Photogrammetric Engineering and Remote Sensing, 2006, v. 72, n. 8, p. 923-932 How to Cite?
AbstractThis study presents a new method of detecting individual treetops from lidar data and applies marker-controlled watershed segmentation into isolating individual trees in savanna woodland. The treetops were detected by searching local maxima in a canopy maxima model (CMM) with variable window sizes. Different from previous methods, the variable windows sizes were determined by the lower-limit of the prediction intervals of the regression curve between crown size and tree height. The canopy maxima model was created to reduce the commission errors of treetop detection. Treetops were also detected based on the fact that they are typically located around the center of crowns. The tree delineation accuracy was evaluated by a five-fold, cross-validation method. Results showed that the absolute accuracy of tree isolation was 64.1 percent, which was much higher than the accuracy of the method, which only searched local maxima within window sizes determined by the regression curve (37.0 percent). © 2006 American Society for Photogrammetry and Remote Sensing.
Persistent Identifierhttp://hdl.handle.net/10722/296597
ISSN
2023 Impact Factor: 1.0
2023 SCImago Journal Rankings: 0.309
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChen, Qi-
dc.contributor.authorBaldocchi, Dennis-
dc.contributor.authorGong, Peng-
dc.contributor.authorKelly, Maggi-
dc.date.accessioned2021-02-25T15:16:14Z-
dc.date.available2021-02-25T15:16:14Z-
dc.date.issued2006-
dc.identifier.citationPhotogrammetric Engineering and Remote Sensing, 2006, v. 72, n. 8, p. 923-932-
dc.identifier.issn0099-1112-
dc.identifier.urihttp://hdl.handle.net/10722/296597-
dc.description.abstractThis study presents a new method of detecting individual treetops from lidar data and applies marker-controlled watershed segmentation into isolating individual trees in savanna woodland. The treetops were detected by searching local maxima in a canopy maxima model (CMM) with variable window sizes. Different from previous methods, the variable windows sizes were determined by the lower-limit of the prediction intervals of the regression curve between crown size and tree height. The canopy maxima model was created to reduce the commission errors of treetop detection. Treetops were also detected based on the fact that they are typically located around the center of crowns. The tree delineation accuracy was evaluated by a five-fold, cross-validation method. Results showed that the absolute accuracy of tree isolation was 64.1 percent, which was much higher than the accuracy of the method, which only searched local maxima within window sizes determined by the regression curve (37.0 percent). © 2006 American Society for Photogrammetry and Remote Sensing.-
dc.languageeng-
dc.relation.ispartofPhotogrammetric Engineering and Remote Sensing-
dc.titleIsolating individual trees in a savanna woodland using small footprint lidar data-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.14358/PERS.72.8.923-
dc.identifier.scopuseid_2-s2.0-33746651021-
dc.identifier.volume72-
dc.identifier.issue8-
dc.identifier.spage923-
dc.identifier.epage932-
dc.identifier.isiWOS:000239417400008-
dc.identifier.issnl0099-1112-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats