Abstract
Surface models provide key knowledge of the 3-d structure of forests. Aerial stereo imagery acquired during routine mapping campaigns covering the whole of Switzerland (41,285 km2), offers a potential data source to calculate digital surface models (DSMs). We present an automated workflow to generate a nationwide DSM with a resolution of 1 × 1 m based on photogrammetric image matching. A canopy height model (CHM) is derived in combination with an existing digital terrain model (DTM). ADS40/ADS80 summer images from 2007 to 2012 were used for stereo matching, with ground sample distances (GSD) of 0.25 m in lowlands and 0.5 m in high mountain areas. Two different image matching strategies for DSM calculation were applied: one optimized for single features such as trees and for abrupt changes in elevation such as steep rocks, and another optimized for homogeneous areas such as meadows or glaciers. The country was divided into 165,500 blocks, which were matched independently using an automated workflow. The completeness of successfully matched points was high, 97.9%. To test the accuracy of the derived DSM, two reference data sets were used: (1) topographic survey points (n = 198) and (2) stereo measurements (n = 195,784) within the framework of the Swiss National Forest Inventory (NFI), in order to distinguish various land cover types. An overall median accuracy of 0.04 m with a normalized median absolute deviation (NMAD) of 0.32 m was found using the topographic survey points. The agreement between the stereo measurements and the values of the DSM revealed acceptable NMAD values between 1.76 and 3.94 m for forested areas. A good correlation (Pearson’s r = 0.83) was found between terrestrially measured tree height (n = 3109) and the height derived from the CHM. Optimized image matching strategies, an automatic workflow and acceptable computation time mean that the presented approach is suitable for operational usage at the nationwide extent. The CHM will be used to reduce estimation errors of different forest characteristics in the Swiss NFI and has high potential for change detection assessments, since an aerial stereo imagery update is available every six years.
Highlights
Knowledge of tree resources and the structure of forests is key for managing various forest functions and services
Even in the high mountain areas where snow and ice dominate, small structures are visible in the digital surface models (DSMs)
Once a digital terrain model based on airborne laser scanning (ALS) data is available, the photogrammetric updating of digital surface data and canopy height models using routinely acquired aerial stereo image data provides a valuable alternative to the acquisition of repeated ALS data
Summary
Knowledge of tree resources and the structure of forests is key for managing various forest functions and services. Forest characteristics are traditionally estimated in forest inventories based on sample plots. Stereo optical imagery or laser scanning data have tremendous potential for obtaining area-wide three-dimensional data over several thousands of hectares. Their usage in the analysis of forested areas over an entire country opens up new possibilities for biomass estimations [2,3], forest structure analysis [4,5], biodiversity assessment [6,7] and the optimization of forest inventories at a national level [8]
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