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Having a detailed knowledge of the territory is a key factor for a sustainable management. In Catalonia, forest areas constitute the 42 % of land coverage and, therefore, there is a need for a best characterization of the forest structure and composition not only to quantify wood but also, and even more important, for wild fire prevention and fire propagation modelling.
Traditional forest inventories require costly ground surveys for gathering information over forest plots distributed along the territory, resulting in low resolution maps over all the surveyed areas.
In this presentation, the first high resolution maps of the Catalan forests showing aboveground biomass, carbon stock among other forest variables will be introduced. These maps have been obtained by the ICGC and CREAF by combining a 0.5 p/m2 LiDAR point cloud and terrain data from forest inventory plots.
The new methodology enables the generation of maps with a resolution of 20x20 m, 2500 larger than the previous available information. This important improvement is due to the use of LiDAR to obtain forest structure information at high resolution, rather than the discrete information of the previous traditional forest inventories. The new maps depict eight different biophysical variables of forest characteristics. These maps are useful for forest management plans and for fire risk prevention.
The maps have been published as Web Map Services and the data files are also available to the general public using a CC-BY license.
Topic Area: [1.3] Land management and monitoring Abstract Type: Oral Presentation
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