Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 727-731, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-727-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
23 Jun 2016
WIDE-AREA MAPPING OF FOREST WITH NATIONAL AIRBORNE LASER SCANNING AND FIELD INVENTORY DATASETS
J.-M. Monnet1, C. Ginzler2, and J.-C. Clivaz3 1Université Grenoble Alpes, Irstea, UR EMGR, 2 rue de la Papeterie - BP 76, 38402 St-Martin-d’Hères, France
2Swiss Federal Research Institute WSL, Zuercherstrasse 111, 8903 Birmensdorf, Switzerland
3Canton du Valais - Arrondissement forestier du Valais Central – Rue Traversière 3, 1950 Sion, Switzerland
Keywords: Forest Inventory, Airborne Laser Scanning, Wide-area Mapping, Remote Sensing, Valais Abstract. Airborne laser scanning (ALS) remote sensing data are now available for entire countries such as Switzerland. Methods for the estimation of forest parameters from ALS have been intensively investigated in the past years. However, the implementation of a forest mapping workflow based on available data at a regional level still remains challenging. A case study was implemented in the Canton of Valais (Switzerland). The national ALS dataset and field data of the Swiss National Forest Inventory were used to calibrate estimation models for mean and maximum height, basal area, stem density, mean diameter and stem volume. When stratification was performed based on ALS acquisition settings and geographical criteria, satisfactory prediction models were obtained for volume (R2 = 0.61 with a root mean square error of 47 %) and basal area (respectively 0.51 and 45 %) while height variables had an error lower than 19%. This case study shows that the use of nationwide ALS and field datasets for forest resources mapping is cost efficient, but additional investigations are required to handle the limitations of the input data and optimize the accuracy.
Conference paper (PDF, 1015 KB)


Citation: Monnet, J.-M., Ginzler, C., and Clivaz, J.-C.: WIDE-AREA MAPPING OF FOREST WITH NATIONAL AIRBORNE LASER SCANNING AND FIELD INVENTORY DATASETS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 727-731, https://doi.org/10.5194/isprs-archives-XLI-B8-727-2016, 2016.

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