XXII ISPRS Congress 2012: Technical Commission VIII

Shortis, M.; Shimoda, H.; Cho, K.

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Type of content:: Konferenzschrift

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Reihe:: ISPRS archives

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Editor:: International Society for Photogrammetry and Remote Sensing

Author:: International Society for Photogrammetry and Remote Sensing, 22.; 2012; Melbourne

Document type:: Multivolume work

Volume

Persistent identifier:: 1663822514

Title:: Technical Commission VIII

Scope:: 590 Seiten

Type of content:: Konferenzschrift

DOI:: 10.14463/KXP:1663822514

Year of publication:: 2014

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663822514

Illustration:: Illustrationen, Diagramme

Reihe:: ISPRS archives (volume 39, B8 (2012))

Signature of the source:: ZS 312(39,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Shortis, M.; Shimoda, H.; Cho, K.

Editor:: International Society for Photogrammetry and Remote Sensing

Author:: International Society for Photogrammetry and Remote Sensing, 22.; 2012; Melbourne

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VIII/7: Forestry]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: ESTIMATING MIXED BROADLEAVES FOREST STAND VOLUME USING DSM EXTRACTED FROM DIGITAL AERIAL IMAGES H. Sohrabi

Document type:: Multivolume work

Structure type:: Chapter

maples (Acer velutinum), Persian Ironwood Tree (Parrotia persica) and few other species, which is typical for the region. Data set consist of 76 ortho-rectified CIR images of UltraCamD which has been in 19.8.2006. Focal length, mapping scale, ground pixel size and radiometric resolution were 101.4 mm, 1:15000, 14 cm and 8 bit, respectively. Digital surface models (DSMs) were generated automatically using an image matching approach from CIR aerial images with a spatial resolution of 1 to 10 m size by 1m span. All DSMs were checked manually for probable errors. Tonekabon Figure 1. The location of study area 2.2 Ground data and statistical methods 120 ground circular sample plot were located at study area and diameter, species and height of three random trees were recorded and standing volume in each plot were calculated. Also, corresponding to each ground sample plot, standard deviation of DSM pixels was calculated. 80 percent of samples were used for constructing regression equations and 20 percent for validating the equations. Non-linear regression analysis was used for modelling. Bias, relative bias, RMSE and relative RMSE of estimating standing volume were calculated using following equations: SG, zy.) Bias — 4L — — (1) n Bus =100x 22 @) y International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia Y 6, -y,y RMSE z4|: (3) n RMSE, «19042 MSE (4 M where: 9, and y,: estimated and true value for i, observation n: number of observations y : mean of true observations 3. RESULTS Results showed that at 5 to 7 m pixel size, the correlation coefficient of standard deviation of pixels and standing volume of sample plots are higher than other pixel sizes (figure 2). So. 5 m resolution DSM (which was the most correlated pixel size) was used for further analysis. 0.60 0.50 - 0.40 4 0.30 4 | 0.20 + | 0.10 + | 0.00 | correlation coefficient T | | 0 1. 245344. 5. 6. 7, 8. 9. 19. 1] | Pixel size (m) / Figure 2. Correlation of standard deviation of different pixel size of DSM and forest standing volume at sample plots Table 1. Results of regression analysis, y: stand volume in sample plot and x: standard deviation of DSM pixels of sample plot Model Equation r Sig. Power Model y-17.334x ^? 0.58 TE Different regression models were fitted and the most suitable one based on correlation coefficient and standard error of model was power regression model (table 1 and figure 3). Inter After holdir mean percer Table In the stand been volun fact t appro Crowr variat Many volun expre sattel 79% 2006) et al., et al. 2006 Pekk: Tuon using (200¢ Tepor 49.89 volur One | is to heigt apply

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