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Träfflista för sökning "WFRF:(Granholm Ann Helen) srt2:(2015)"

Sökning: WFRF:(Granholm Ann Helen) > (2015)

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1.
  • Granholm, Ann-Helen, et al. (författare)
  • Estimating vertical canopy cover with dense point cloud data from matching of digital aerial photos
  • 2015
  • Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
    • This study aims to explore the use of dense point clouds from matching of aerial photos for estimation of vertical canopy cover (VCC), defined as the proportion of the forest floor covered by the vertical projection of the tree crowns. VCC is commonly estimated using vegetation ratio (VR) derived from airborne laser scanner (ALS) data. A reliable measure of VCC from matching aerial photos would aid in vegetation mapping and reduce the need for repeated ALS data acquisition. The test area is located in southern Sweden and covers a variety of vegetation types. In total 367 sample plots were placed in parts of the study area representing VCC ranging from 0 % up to close to 100 %. ALS data with a density of 20 returns per m2 was used for calculating the VR as the proportion of first returns above a threshold. Aerial imagery with a ground sample distance of 0.25 m was matched to produce dense point cloud data, which was used to derive digital surface models (DSMs) with grid size from 0.25 m up to 2.0 m. Local maxima (LM) detection was applied to the DSMs with search windows of 0.5 m size up to 2.0 m. The heights of the LM were normalized using a digital elevation model (DEM) derived from ALS data. Regression analysis was applied with the VR as dependent variable and the sum of the height of LM within sample plots as independent variable. Results from linear regression using heights of LM detected in a DSM of 0.25 m resolution with a 0.5 m search window gave an root mean square error (RMSE) of 5.5 % and relative RMSE (rRMSE) of 9.3 % in forest on rocky outcrops and boulders, while wooded pasture gave RMSE = 6.3 % and rRMSE = 19 %.
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2.
  • Granholm, Ann-Helen, et al. (författare)
  • The potential of digital surface models based on aerial images for automated vegetation mapping
  • 2015
  • Ingår i: International Journal of Remote Sensing. - : Informa UK Limited. - 0143-1161 .- 1366-5901. ; 36, s. 1855-1870
  • Tidskriftsartikel (refereegranskat)abstract
    • Segmentation of vegetation patches was tested using canopy height models (CHMs) representing the height difference between digital surface models (DSMs), generated by matching digital aerial images from the Z/I Digital Mapping Camera, and a digital elevation model (DEM) based on airborne laser scanner data. Three different combinations of aerial images were used in the production of the CHMs to test the effect of flight altitude and stereo overlap on segmentation accuracy. Segmentation results were evaluated using the standard deviation of photo-interpreted tree height within segments, as well as by visual comparison to existing maps. In addition, height percentiles extracted from the CHMs were used to estimate tree heights. Tree height estimation at the segment level yielded root mean square error (RMSE) values of 2.0 m, or 15.1%, and an adjusted coefficient of determination (adjusted R2) of 0.94 when using a CHM from images acquired at an altitude of 1200 m above ground level (agl) and with an along-track stereo overlap of 80%. When a CHM based on images acquired at 4800 m agl and an overlap of 60% was used, the corresponding results were an RMSE of 2.2 m, or 16.0%, and an adjusted R2 of 0.92. Tree height estimation at the plot level was most accurate for densely forested plots dominated by coniferous tree species (RMSE of 2.1 m, or 9.8%, and adjusted R2 of 0.88). It is shown that CHMs based on aerial images acquired at 4800 m agl and with 60% along-track stereo overlap are useful for the segmentation of vegetation and are at least as good as those based on aerial images collected at a lower flight altitude or with greater overlap.
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