Automated tree recognition in old growth conifer stands with high resolution digital imagery

Leckie, Donald G.; Gougeon, François A.; Tinis, Sally; Nelson, Trisalyn A.; Burnett, C.N.; Paradine, Dennis

doi:10.1016/j.rse.2004.10.011

Cited by 149 publications

(90 citation statements)

References 12 publications

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“…Thus, this approach may be limited in mixed stands or in natural forests composed of different species. The analysis should be selected to characterize either conifer or broadleaved stands, using the applied threshold setting on the algorithm to delineate shaded and bright areas of the tree crowns (Leckie et al 2003a(Leckie et al , 2005.…”

Section: Discussionmentioning

confidence: 99%

Application of high-resolution airborne data using individual tree crowns in Japanese conifer plantations

Katoh

Gougeon

Leckie

2009

Journal of Forest Research

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We investigated conifer plantation management in Japan using high-resolution airborne data based on an individual tree crown (ITC) approach. This study is the first to apply this technique to Japanese forests. We found that forest resources can be measured at the level of a single tree. We also produced a tree crown map for a test site with Chamaecyparis obtusa, Pinus densiflora, Larix kaempferi, Cryptomeria japonica, other conifers, and broadleaved trees, with a classification accuracy of 78%. Forest stand polygons with tree cover types were generated from this map, a tree density map, and a crownoccupied area map. Forest information for the stand polygons was extracted automatically and compared to detailed field survey data. The error rate between our ITC estimates and the field survey data ranged from 0.3 to 30.2%, depending on tree crown size, density, and other factors. Errors were highest for high-density stands with mixed compositions and tree crown diameters of ≤5.0 m. However, the error for stands with crown diameters ≥6.2 m was 11.6% or less. Therefore, this technique is best suited to pure Japanese conifer plantations without multiple layers or high-density stands.

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Section: Discussionmentioning

confidence: 99%

Application of high-resolution airborne data using individual tree crowns in Japanese conifer plantations

Katoh

Gougeon

Leckie

2009

Journal of Forest Research

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“…Accurate forest information at the individual tree level is of high importance for the selection of target trees. Therefore, individual tree crown delineation methods have received greater attention from researchers in the forest remote sensing field [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…The template-matching algorithms match a synthetic image model or template of a tree crown to radiometric values [21][22][23]. The valley-following method, developed by Gougeon [24], has been successfully used to extract tree crowns and tops of man-made coniferous forests in temperate zones by using aerial photographs [18][19][20]. Additionally, the individual tree crown (ITC) approach using the valley-following method has been successfully programmed by the Pacific Forestry Centre of the Canadian Forest Service, which made it possible to delineate tree crowns and tops on a large scale.…”

Section: Introductionmentioning

confidence: 99%

Interpretation of Forest Resources at the Individual Tree Level at Purple Mountain, Nanjing City, China, Using WorldView-2 Imagery by Combining GPS, RS and GIS Technologies

et al. 2013

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This study attempted to measure forest resources at the individual tree level using high-resolution images by combining GPS, RS, and Geographic Information System (GIS) technologies. The images were acquired by the WorldView-2 satellite with a resolution of 0.5 m in the panchromatic band and 2.0 m in the multispectral bands. Field data of 90 plots were used to verify the interpreted accuracy. The tops of trees in three groups, namely ≥10 cm, ≥15 cm, and ≥20 cm DBH (diameter at breast height), were extracted by the individual tree crown (ITC) approach using filters with moving windows of 3 × 3 pixels, 5 × 5 pixels and 7 × 7 pixels, respectively. In the study area, there were 1,203,970 trees of DBH over 10 cm, and the interpreted accuracy was 73.68 ± 15.14% averaged over the 90 plots. The numbers of the trees that were ≥15 cm and ≥20 cm DBH were 727,887 and 548,919, with an average accuracy of 68.74 ± 17.21% and 71.92 ± 18.03%, respectively. The pixel-based classification showed that the classified accuracies of the 16 classes obtained using the eight multispectral bands were higher than those obtained using only the four standard bands. The increments ranged from 0.1% for the water class to 17.0% for Metasequoia glyptostroboides, with an average value of 4.8% for the 16 classes. In addition, to overcome the "mixed pixels" problem, a crown-based supervised classification, which can improve the classified accuracy of both dominant OPEN ACCESSRemote Sens. 2014, 6 88 species and smaller classes, was used for generating a thematic map of tree species. The improvements of the crown-to pixel-based classification ranged from −1.6% for the open forest class to 34.3% for Metasequoia glyptostroboides, with an average value of 20.3% for the 10 classes. All tree tops were then annotated with the species attributes from the map, and a tree count of different species indicated that the forest of Purple Mountain is mainly dominated by Quercus acutissima, Liquidambar formosana and Pinus massoniana. The findings from this study lead to the recommendation of using the crown-based instead of the pixel-based classification approach in classifying mixed forests.

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“…The ALS data in the study area have a point density ranging from 13 to 30 points per m 2 . The original orthophotos with a resolution of 25 cm were rescaled to a resolution of 50 cm, which was most suitable for individual tree extraction [1,43,51].…”

Section: Airborne Lidar Datamentioning

confidence: 99%

Interpretation of Forest Resources at the Individual Tree Level in Japanese Conifer Plantations Using Airborne LiDAR Data

Deng

Katoh

2016

Remote Sensing

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More than 50% of the national lands in Japan have been surveyed by airborne laser scanning (ALS) data with different point densities; and developing an effective approach to take full advantage of these ALS data for forest management has thus become an urgent topic of study. This study attempted to assess the utility of ALS data for individual tree detection and species classification in a mixed forest with a high canopy density. For comparison, two types of tree tops and tree crowns in the study area were delineated by the individual tree crown (ITC) approach using the green band of the orthophoto imagery and the digital canopy height model (DCHM) derived from the ALS data, respectively. Then, the two types of tree crowns were classified into four classes-Pinus densiflora (Pd), Chamaecyparis obtusa (Co), Larix kaempferi (Lk), and broadleaved trees (Bl)-by a crown-based classification approach using different combinations of the three orthophoto bands with intensity and slope maps as follows: RGB (red, green and blue); RGB and intensity (RGBI); RGB and slope (RGBS); and RGB, intensity and slope (RGBIS). Finally, the tree tops were annotated with species attributes from the two best-classified tree crown maps, and the number of different tree species in each compartment was counted for comparison with the field data. The results of our study suggest that the combination of RGBIS yielded greater classification accuracy than the other combinations. In the tree crown classifications delineated by the green band and DCHM data, the improvements in the overall accuracy compared to the RGB ranged from 5.7% for the RGBS to 9.0% for the RGBIS and from 8.3% for the RGBS to 11.8% for the RGBIS. The laser intensity and slope derived from the ALS data may be valuable sources of information for tree species classification, and in terms of distinguishing species for the detection of individual trees, the findings of this study demonstrate the advantages of using DCHM instead of optical data to delineate tree crowns. In conclusion, the synthesis of individual tree delineation using DCHM data and species classification using the RGBIS combination is recommended for interpreting forest resources in the study area. However, the usefulness of this approach must be verified in future studies through its application to other forests.

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Automated tree recognition in old growth conifer stands with high resolution digital imagery

Cited by 149 publications

References 12 publications

Application of high-resolution airborne data using individual tree crowns in Japanese conifer plantations

Application of high-resolution airborne data using individual tree crowns in Japanese conifer plantations

Interpretation of Forest Resources at the Individual Tree Level at Purple Mountain, Nanjing City, China, Using WorldView-2 Imagery by Combining GPS, RS and GIS Technologies

Interpretation of Forest Resources at the Individual Tree Level in Japanese Conifer Plantations Using Airborne LiDAR Data

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