Potential of Modern Photogrammetry Versus Airborne Laser Scanning for Estimating Forest Variables in a Mountain Environment

Sami Ullah,Pawan Datta,Petra Adler,Matthias Dees,Mathias Schardt,Barbara Koch

doi:10.3390/rs11060661

Sami Ullah, Pawan Datta + Show 4 more

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https://doi.org/10.3390/rs11060661

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Abstract

Digital stereo aerial photographs are periodically updated in many countries and offer a viable option for the regular update of information on forest variables. We compared the potential of image-based point clouds derived from three different sets of aerial photographs with airborne laser scanning (ALS) to assess plot-level forest attributes in a mountain environment. The three data types used were (A) high overlapping pan-sharpened (80/60%); (B) high overlapping panchromatic band (80/60%); and (C) standard overlapping pan-sharpened stereo aerial photographs (60/30%). We used height and density metrics at the plot level derived from image-based and ALS point clouds as the explanatory variables and Lorey’s mean height, timber volume, and mean basal area as the response variables. We obtained a RMSE = 8.83%, 29.24% and 35.12% for Lorey’s mean height, volume, and basal area using ALS data, respectively. Similarly, we obtained a RMSE = 9.96%, 31.13%, and 35.99% and RMSE = 11.28%, 31.01%, and 35.66% for Lorey’s mean height, volume and basal area using image-based point clouds derived from pan-sharpened stereo aerial photographs with 80/60% and 60/30% overlapping, respectively. For image-based point clouds derived from a panchromatic band of stereo aerial photographs (80%/60%), we obtained an RMSE = 10.04%, 31.19% and 35.86% for Lorey’s mean height, volume, and basal area, respectively. The overall findings indicated that the performance of image-based point clouds in all cases were as good as ALS. This highlights that in the presence of a highly accurate digital terrain model (DTM) from ALS, image-based point clouds offer a viable option for operational forest management in all countries where stereo aerial photographs are updated on a routine basis.

Highlights

Forest management relies on accurate, updated, and spatially detailed information about woody forest resources
Our results showed that the performance of airborne laser scanning (ALS) for estimating the Lorey’s mean height was more accurate than image-based point clouds (Table 4)
Our findings indicate that image-based point clouds have significant potential and offer a viable option for countries where stereo aerial photographs are updated at a regular basis and where highly accurate digital terrain model (DTM) from pre-existing ALS campaigns in forested areas are available

Summary

Introduction

Forest management relies on accurate, updated, and spatially detailed information about woody forest resources. The options for measuring forest heights, forest timber volume, and basal area with a full enumeration are achievable for selected stands, but are not applicable as standard methods in forest management inventories for geographically large forest areas due to the limitation of resources and high cost [1]. An alternative approach developed and implemented in Switzerland during the 1930s is the permanent sample plot approach [1,3,4], which is nowadays a widely used method for forest management planning in large forest areas. Integrating remote sensing (RS) with a field sample based forest inventory offers a solution for complementing the statistical results using a wall-to-wall mapping approach for all major forest attributes of the entire geographical forest area, and offers a new dimension of information for forest management and forest operations planning

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Conclusion