4.5 Article

Assessing height changes in a highly structured forest using regularly acquired aerial image data

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FORESTRY
卷 88, 期 3, 页码 304-316

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OXFORD UNIV PRESS
DOI: 10.1093/forestry/cpu050

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  1. Bavarian State Mininstry of Food, Agriculture and Forestry (in German: Bayerisches Staatsministerium fur Ernahrung, Landwirtschaft und Forsten)

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In this paper, we demonstrate the effectiveness of digital stereo images and canopy height models (CHMs) derived from them for forest height change assessment. Top heights were derived for 199 terrestrial inventory plots from forest inventories conducted in 2008 and 2013 in a forest near Traunstein, Germany. Semi-Global Matching was applied to two sets of aerial stereo images, acquired in 2009 and 2012, respectively, to compute CHMs. Subsequently, several height percentiles were calculated from the areas in the CHMs that lay within the inventory plot locations. The maximum CHM value (h(max)) had the highest correlation with the field-based canopy top heights and was selected for use in all further analysis. Periodic annual increments (PAIs) of forest height were calculated from both the remote sensing and the field data at the inventory plot locations. Scatterplots of the PAIs over top height revealed similar patterns in the results derived from the two data sets. The inventory plots were assigned to three height classes representing various forest successional stages - youth, full vigour and old age. The PAI distributions within the three height classes were significantly different from one another. Our findings suggest that CHMs derived from repeat aerial image surveys can be a viable tool to measure canopy heights and to assess forest height changes over time, even for a highly structured, mixed forest in central Europe.

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