Talks and Poster Presentations (with Proceedings-Entry):
M. Hollaus, L. Eysn, C. Bauerhansl, F. Riccabona, B. Maier:
"Accuracy assessment of ALS-derived stem volume and biomass maps";
Talk: 1st EARSeL SIG Forestry workshop: Operational remote sensing in forest management,
Prague, Czech Republic;
- 2011-06-03; in: "1st Forestry Workshop: Operational Remote Sensing in Forest Management",
During the last decade airborne laser scanning (ALS) has been developed as a standard method for the acquisition of high precision topographic data. As an active remote sensing system ALS has several advantages in forested areas to achieve a terrain model (DTM) as well as a surface model (DSM) without being influenced by shadows or varying conditions of the sunlight. The normalized digital surface model (nDSM), calculated by subtracting the DTM from the DSM, represents object heights (i.e. canopy or tree heights) and is an important data source for the derivation of various forest parameters. In recent review papers Næsset (2004) and Hyyppä et al. (2008) concluded that the retrieval of mean stem volume and tree height from ALS data performs as well as, or better than, common photogrammetric methods and better than other remote sensing methods. Some researchers even think that ALS provides more accurate data than in-situ measurement techniques (e.g. Næsset, 2004). However, the verification of these statements is not easy to achieve due to different sampling designs and accuracies of forest inventory data being used as ground through data. For example, in Austria the national forest inventory (NFI) is based on the angle count sampling plots, which donīt refer to a fixed sample plot area. This fact makes the combination of the NFI data with any remote sensing data to a challenging task.
In this study we use 17 fully callipered sample areas and stand volume inventory data to assess the accuracies of stem volume and biomass maps for different Austrian test sites. Within these sample areas single tree parameters (i.e. diameter at breast height, tree height and species) were acquired for more than 1600 trees. For the calibration of the stem volume and biomass model available NFI data as well as local forest inventory data are used, which are both based on angle count sampling plots. This verification approach guarantees firstly the independency of calibration and validation data and secondly it allows accuracy analyses for different reference units (i.e. different forest stand sizes). In overall the results show higher accuracies for the estimated biomass than for the stem volume map, whereas the average relative accuracies are about 10% and 15% respectively. Furthermore, the achievable accuracies for different stand sizes are shown and discussed. These accuracy measures are compared with the output of accuracies derived from cross-validations using the forest inventories. The main factors influencing the accuracies are described and discussed including for example the measurement errors of the forest inventory data as well as the applied algorithms to estimate the stem volume and biomass maps from the ALS data. As the estimations of the stem volume and biomass maps are based on federal state wide data sets (ALS and NFI) the findings of this study are of high practical relevance for integrating ALS derived forest parameters into operational forest inventories.
Hyyppä, J., Hyyppä, H., Leckie, D., Gougeon, F., Yu, X. and Maltamo, M., 2008. Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests. International Journal of Remote Sensing, 29(5), 1339-1366.
Næsset, E., 2004. Practical Large-scale Forest Stand Inventory Using a Small-footprint Airborne Scanning Laser. Scandinavian Journal of Forest Research, 19(2), 164-179.
LiDAR, operational forest inventory, Alpine forests, angle count sampling, inventory design
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.