Automated Individual Tree Isolation on High-Resolution Imagery: Possible Methods for Breaking Isolations Involving Multiple Trees

One of the key problems in automated individual tree crown delineation, whether from multispectral or lidar data, is the grouping of several trees into a single tree crown outline (isol). Using airborne multispectral imagery, we explored four approaches to breaking such isols into multiple crowns: “core,” “tree top,” “template matching,” and “basin” breaks. Core breaks are made using only isol shape and morphological primitives. Tree top and template matching breaks utilize image maxima and pattern, and watershed drainage basins form the basis of basin breaks. The effectiveness of each of the four break types was assessed against the presence and position of the true boundary between multiple tree crowns and with reference to original isol shape. There was correspondence and differences between breaks of different types. A set of rules was developed to choose a single break when there was positional correspondence of several break types. The rules were based on isol shape type and the break types present. Despite being a complex and difficult issue, it was shown that the concept of identifying poor delineations, recognizing them as cases of multiple trees, and remediating the crown delineations is viable and worthy of further development.

[1]  Jay Lee,et al.  Research Article: Extensions to least-cost path algorithms for roadway planning , 2003, Int. J. Geogr. Inf. Sci..

[2]  Morten LarsenRoyal CROWN MODELLING TO FIND TREE TOP POSITIONS IN AERIAL PHOTOGRAPHS , 1997 .

[3]  R. Lucas,et al.  The delineation of tree crowns in Australian mixed species forests using hyperspectral Compact Airborne Spectrographic Imager (CASI) data , 2006 .

[4]  J. Cayford,et al.  Forest Regions of Canada , 1974 .

[5]  Darius S. Culvenor,et al.  Extracting Individual Tree Information , 2003 .

[6]  Morten Andreas Dahl Larsen,et al.  Comparison of six individual tree crown detection algorithms evaluated under varying forest conditions , 2011 .

[7]  Lindi J. Quackenbush,et al.  Developing Forestry Products from High Resolution Digital Aerial Imagery , 2000 .

[8]  Jungho Im,et al.  Indicators for separating undesirable and well-delineated tree crowns in high spatial resolution images , 2012 .

[9]  Yinghai Ke,et al.  A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing , 2011 .

[10]  F. Gougeon A Crown-Following Approach to the Automatic Delineation of Individual Tree Crowns in High Spatial Resolution Aerial Images , 1995 .

[11]  D. Leckie,et al.  Recognition and Possible Remediation of Automated Tree Delineations with Multiple Isolations per Tree (Split Cases) on High-Resolution Imagery , 2016 .

[12]  François A. Gougeon,et al.  Identifying tree crown delineation shapes and need for remediation on high resolution imagery using an evidence based approach , 2016 .

[13]  Barbara Koch,et al.  Investigating multiple data sources for tree species classification in temperate forest and use for single tree delineation , 2012, Int. J. Appl. Earth Obs. Geoinformation.

[14]  François A. Gougeon,et al.  Forest information extraction from high spatial resolution images using an individual tree crown approach , 2003 .

[15]  D. King,et al.  Approaches for optimal automated individual tree crown detection in regenerating coniferous forests , 2005 .

[16]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[17]  Pierre Soille,et al.  Morphological segmentation of binary patterns , 2009, Pattern Recognit. Lett..