Received: 04 Dec 2015 – Accepted for review: 08 Dec 2015 – Discussion started: 21 Dec 2015
Abstract. Methods for the estimation of forest characteristics by airborne laser scanning (ALS) data have been introduced by several authors. Tree height (TH) and canopy closure (CC) describing the forest properties can be used in forest, construction and industry applications, as well as research and decision making. The National Land Survey has been collecting ALS data from Finland since 2008 to generate a nationwide high resolution digital elevation model. Although this data has been collected in leaf-off conditions, it still has the potential to be utilized in forest mapping. A method where this data is used for the estimation of CC and TH in the boreal forest region is presented in this paper. Evaluation was conducted in eight test areas across Finland by comparing the results with corresponding Multi-Source National Forest Inventory (MS-NFI) datasets. The ALS based CC and TH maps were generally in a good agreement with the MS-NFI data. As expected, deciduous forests caused some underestimation in CC and TH, but the effect was not major in any of the test areas. The processing chain has been fully automated enabling fast generation of forest maps for different areas.
This preprint has been withdrawn.
How to cite. Cohen, J.: Estimation of forest parameters using airborne laser scanning data, Geosci. Instrum. Method. Data Syst. Discuss., 5, 549–576, https://doi.org/10.5194/gid-5-549-2015, 2015.
An automatic process for the estimation of forest properties in high spatial resolution using National Land Survey's airborne laser scanning data is presented. Results were evaluated by compering against national MS-NFI forest data. The estimation accuracy was generally good, but deciduous forests in leaf-off conditions caused somewhat underestimation. The method can be used to support e.g. forest managing, construction planning, wood industry and other remote sensing applications and research.
An automatic process for the estimation of forest properties in high spatial resolution using...