Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2017
Abstract
The use of digital aerial photogrammetry (DAP) for forest inventory purposes has been widely studied and can produce comparable accuracy compared with airborne laser scanning (ALS) in small, homogeneous areas. However, the accuracy of DAP for large scale applications with heterogeneous terrain and forest vegetation has not yet been reported. In this study we examined the accuracy of timber volume, biomass and basal area prediction models based on DAP and national forest inventory (NFI) data on a large area in central Norway. Two separate point clouds were derived from aerial image acquisitions of 2010 and 2013. Vegetation heights were extracted by subtracting terrain elevation derived from ALS. A large number of NFI sample plots (483) measured between 2010 and 2014 were used as reference data to fit linear models for timber volume, biomass and basal area with height metrics derived from the DAP data as explanatory variables. Variables describing the heterogeneous environmental and image acquisition conditions were calculated and their influence on the model accuracy was tested. The results showed that forest parameter prediction using DAP works well when applied to a large area. The model fits of the timber volume, biomass and basal area models were good with R2 of 0.80, 0.81, 0.81 and RMSEs of 41.43 m3 ha−1 (55% of the mean observed value), 32.49 t ha−1 (47%), 5.19 m2 ha−1 (41%), respectively. Only a small proportion of the variation could be attributed to the heterogeneous conditions. The inclusion of the relative sun inclination led to an improvement of the model RMSEs by 2% of the mean observed values. The relatively low cost and stability across large areas make DAP an attractive source of auxiliary information for large scale forest inventories.
Authors
Stephanie Eisner Martina Flörke Alejandro Chamorro Prasad Daggupati Chantal Donnelly J. Huang Yeshewatesfa Hundecha Hagen Koch Andrey Kalugin Inna Krylenko Vimal Mishra Mikołaj Piniewski Luis Samaniego Ousmane Seidou Markus Wallner Valentina KrysanovaAbstract
No abstract has been registered
Authors
Signe Kynding Borgen Gry Alfredsen Johannes Breidenbach Lise Dalsgaard Gunnhild Søgaard Aaron SmithAbstract
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Authors
Kjersti Holt HanssenAbstract
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Authors
Holger Lange Jogeir N. Stokland Bernhard Ahrens Lise Dalsgaard Stephanie Eisner Hanna Lee Toby Marthews Helge Meissner Sebastian SippelAbstract
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Abstract
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Authors
Isabella Børja Kjell Andreassen Jan Čermák Lise Dalsgaard Arthur Gessler Douglas L. Godbold Rainer Hentschel Zachary E. Kayler Paal Krokene Nadezhda Nadezhdina Sabine Rosner Svein Solberg Halvor Solheim Jan Svetlik Mari Mette Tollefsrud Ole Einar TveitoAbstract
No abstract has been registered
Authors
Lise Dalsgaard Aaron Smith Ryan Bright Gunnhild Søgaard Gry Alfredsen Signe Kynding Borgen Johannes BreidenbachAbstract
No abstract has been registered