Errors in the Short-Term Forest Resource Information Update

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Luoma , V , Vastaranta , M , Eyvindson , K , Kankare , V , Saarinen , N , Holopainen , M & Hyyppa , J 2017 , Errors in the Short-Term Forest Resource Information Update . in I Ivan , A Singleton , J Horak & T Inspektor (eds) , The Rise of Big Spatial Data . Lecture Notes in Geoinformation and Cartography , Springer International Publishing AG , pp. 155-166 , GIS Symposium on the Rise of Big Spatial Data , Ostrava , Czech Republic , 16/03/2016 .

Title: Errors in the Short-Term Forest Resource Information Update
Author: Luoma, Ville; Vastaranta, Mikko; Eyvindson, Kyle; Kankare, Ville; Saarinen, Ninni; Holopainen, Markus; Hyyppa, Juha
Other contributor: Ivan, Igor
Singleton, Alex
Horak, Jiri
Inspektor, Tomas
Contributor organization: Department of Forest Sciences
Laboratory of Forest Resources Management and Geo-information Science
Forest Health Group
Forest Ecology and Management
Publisher: Springer International Publishing AG
Date: 2017
Language: eng
Number of pages: 12
Belongs to series: The Rise of Big Spatial Data
Belongs to series: Lecture Notes in Geoinformation and Cartography
ISBN: 978-3-319-45122-0
ISSN: 1863-2246
Abstract: Currently the forest sector in Finland is looking towards the next generation's forest resource information systems. Information used in forest planning is currently collected by using an area-based approach (ABA) where airborne laser scanning (ALS) data are used to generalize field-measured inventory attributes over an entire inventory area. Inventories are typically updated at 10-year interval. Thus, one of the key challenges is the age of the inventory information and the cost-benefit trade-off between using the old data and obtaining new data. Prediction of future forest resource information is possible through growth modelling. In this paper, the error sources related to ALS-based forest inventory and the growth models applied in forest planning to update the forest resource information were examined. The error sources included (i) forest inventory, (ii) generation of theoretical stem distribution, and (iii) growth modelling. Error sources (ii) and (iii) stem from the calculations used for forest planning, and were combined in the investigations. Our research area, Evo, is located in southern Finland. In all, 34 forest sample plots (300 m(2)) have been measured twice tree-by-tree. First measurements have been carried out in 2007 and the second measurements in 2014 which leads to 7 year updating period. Respectively, ALS-based forest inventory data were available for 2007. The results showed that prediction of theoretical stem distribution and forest growth modelling affected only slightly to the quality of the predicted stem volume in short-term information update when compared to forest inventory error.
Subject: Growth modelling
Forest planning
Airborne laser scanning
Forest inventory
4112 Forestry
Peer reviewed: Yes
Rights: cc_by_nc_nd
Usage restriction: openAccess
Self-archived version: acceptedVersion

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