File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Individual tree-crown delineation and treetop detection in high-spatial-resolution aerial imagery

TitleIndividual tree-crown delineation and treetop detection in high-spatial-resolution aerial imagery
Authors
Issue Date2004
Citation
Photogrammetric Engineering and Remote Sensing, 2004, v. 70, n. 3, p. 351-357 How to Cite?
AbstractThe cost of forest sampling can be reduced substantially by the ability to estimate forest and tree parameters directly from aerial photographs. However, in order to do so it is necessary to be able to accurately identify individual treetops and then to define the region in the vicinity of the treetop that encompasses the crown extent. These two steps commonly have been treated independently. In this paper, we derive individual tree-crown boundaries and treetop locations under a unified framework. We applied a two-stage approach with edge detection followed by marker-controlled watershed segmentation. A Laplacian of Gaussian edge detection method at the smallest effective scale was employed to mask out the background. An eight-connectivity scheme was used to label the remaining tree objects in the edge map. Subsequently, treetops are modeled based on both radiometry and geometry. More specifically, treetops are assumed to be represented by local radiation maxima and also to be located near the center of the tree-crown. As a result, a marker image was created from the derived treetop to guide a watershed segmentation to further differentiate touching and clumping trees and to produce a segmented image comprised of individual tree crowns. Our methods were developed on a 256- by 256-pixel CASI image of a commercially thinned trial forest. A promising agreement between our automatic methods and manual delineation results was achieved in counting the number of trees as well as in delineating tree crowns. © 2004 American Society for Photogrammetry and Remote Sensing.
Persistent Identifierhttp://hdl.handle.net/10722/296567
ISSN
2019 Impact Factor: 1.265
2015 SCImago Journal Rankings: 0.830
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWang, Le-
dc.contributor.authorGong, Peng-
dc.contributor.authorBiging, Gregory S.-
dc.date.accessioned2021-02-25T15:16:10Z-
dc.date.available2021-02-25T15:16:10Z-
dc.date.issued2004-
dc.identifier.citationPhotogrammetric Engineering and Remote Sensing, 2004, v. 70, n. 3, p. 351-357-
dc.identifier.issn0099-1112-
dc.identifier.urihttp://hdl.handle.net/10722/296567-
dc.description.abstractThe cost of forest sampling can be reduced substantially by the ability to estimate forest and tree parameters directly from aerial photographs. However, in order to do so it is necessary to be able to accurately identify individual treetops and then to define the region in the vicinity of the treetop that encompasses the crown extent. These two steps commonly have been treated independently. In this paper, we derive individual tree-crown boundaries and treetop locations under a unified framework. We applied a two-stage approach with edge detection followed by marker-controlled watershed segmentation. A Laplacian of Gaussian edge detection method at the smallest effective scale was employed to mask out the background. An eight-connectivity scheme was used to label the remaining tree objects in the edge map. Subsequently, treetops are modeled based on both radiometry and geometry. More specifically, treetops are assumed to be represented by local radiation maxima and also to be located near the center of the tree-crown. As a result, a marker image was created from the derived treetop to guide a watershed segmentation to further differentiate touching and clumping trees and to produce a segmented image comprised of individual tree crowns. Our methods were developed on a 256- by 256-pixel CASI image of a commercially thinned trial forest. A promising agreement between our automatic methods and manual delineation results was achieved in counting the number of trees as well as in delineating tree crowns. © 2004 American Society for Photogrammetry and Remote Sensing.-
dc.languageeng-
dc.relation.ispartofPhotogrammetric Engineering and Remote Sensing-
dc.titleIndividual tree-crown delineation and treetop detection in high-spatial-resolution aerial imagery-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.14358/PERS.70.3.351-
dc.identifier.scopuseid_2-s2.0-21244504049-
dc.identifier.volume70-
dc.identifier.issue3-
dc.identifier.spage351-
dc.identifier.epage357-
dc.identifier.isiWOS:000221403200010-
dc.identifier.issnl0099-1112-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats