Outlook for the Single-Tree-Level Forest Inventory in Nordic Countries
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In Nordic countries, the forest resource information systems have advanced to a state where substand-level information can be utilized. The demand of high detail up-to-date forest resource information has become a prerequisite for many of the operators working with the data, but the information on the forest attributes such as species-specific timber assortments and tree quality cannot be obtained accurately enough from the current inventory systems. Therefore, the forest organizations are actively looking forward and started the development of the next generation forest inventory platforms. The vision is, a radical leap in the cost effectiveness of forestry and wood supply will be gained through new digital services and Big Data applications. The most prominent solution for the increased demand on the information detail is single-tree-level forest inventory through various laser scanning technologies (airborne-, terrestrial- and mobile laser scanning, (ALS, TLS and MLS, respectively)) but it has not yet been adapted into operational forestry mainly due to the higher costs and challenges in data processing. Many studies have already concluded that single-tree-level information will play an important role in the next generation’s forest mapping systems that will be based on multisource approach. The challenges in multisource approach have been the data acquisition, automatic tree attribute measurements and the optimal data combinations. MLS and harvester data are of high interest technologies in the reference data acquisition but have not yet been implemented into practical applications. The goal of the present outlook was to evaluate and discuss the potential and challenges of the laser scanning technologies (especially ALS and TLS) in single-tree-level forest inventory as a part of multisource approach which, when implemented, will create a scenario for vast forest big data.
KeywordsRemote sensing Laser scanning Single-tree-level Forest inventory GIS Ostrava 2016
Our study was made possible by financial aid from the Finnish Academy project Centre of Excellence in Laser Scanning Research (CoE-LaSR, decision number 272195). We would like to acknowledge the partners in Forest Big Data (FBD)/Data to Intelligence (D2I) Digile/Tekes Program.
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