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.
2015
Abstract
Remotely sensed data from airborne laser scanning (ALS) and interferometric synthetic aperture radar (InSAR) can greatly improve the precision of estimates of forest resource parameters such as mean biomass and biomass change per unit area. Field plots are typically used to construct models that relate the variable of interest to explanatory variables derived from the remotely sensed data. The models may then be used in combination with the field plots to provide estimates for a geographical area of interest with corresponding estimates of precision using model-assisted estimators. Previous studies have shown that field plot sizes found suitable for pure field surveys may be sub-optimal for use in combination with remotely sensed data. Plot boundary effects, co-registration problems, and misalignment problems favor larger plots because the relative impact of these effects on the models of relationships may decline by increasing plot size. In a case study in a small boreal forest area in southeastern Norway (852.6 ha) a probability sample of 145 field plots was measured twice over an 11 year period (1998/1999 and 2010). For each plot, field measurements were recorded for two plot sizes (200 m2 and 300/400 m2). Corresponding multitemporal ALS (1999 and 2010) and InSAR data (2000 and 2011) were also available. Biomass for each of the two measurement dates as well as biomass change were modeled for all plot sizes separately using explanatory variables from the ALS and InSAR data, respectively. Biomass change was estimated using model-assisted estimators. Separate estimates were obtained for different methods for estimation of change, like the indirect method (difference between predictions of biomass for each of the two measurement dates) and the direct method (direct prediction of change). Relative efficiency (RE) was calculated by dividing the variance obtained for a pure field-based change estimate by the variance of a corresponding estimate using the model-assisted approach. For ALS, the RE values ranged between 7.5 and 15.0, indicating that approximately 7.5–15.0 as many field plots would be required for a pure field-based estimate to provide the same precision as an ALS-assisted estimate. For InSAR, RE ranged between 1.8 and 2.5. The direct estimation method showed greater REs than the indirect method for both remote sensing technologies. There was clearly a trend of improved RE of the model-assisted estimates by increasing plot size. For ALS and the direct estimation method RE increased from 9.8 for 200 m2 plots to 15.0 for 400 m2 plots. Similar trends of increasing RE with plot size were observed for InSAR. ALS showed on average 3.2–6.0 times greater RE values than InSAR. Because remote sensing can contribute to improved precision of estimates, sample plot size is a prominent design issue in future sample surveys which should be considered with due attention to the great benefits that can be achieved when using remote sensing if the plot size reflects the specific challenges arising from use of remote sensing in the estimation. That is especially the case in the tropics where field resources may be scarce and inaccessibility and poor infrastructure hamper field work.
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Authors
Tuva Grytli Geoffrey Guest Carine Lausselet Francesco Cherubini Ryan Bright Per Kr. Rørstad Helmer Belbo Rasmus Astrup Øyvind Skreiberg Morten Seljeskog Franziska Goile Anders Hammer StrømmanAbstract
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Authors
Svein Solberg Belachew Gizachew Zeleke Erik Næsset Terje Gobakken Ole Martin Bollandsås Ernest William Mauya Håkan Olsson Rogers Ernerst Malimbwi Eliakimu ZahabuAbstract
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Authors
Svein Solberg Belachew Gizachew Zeleke Erik Næsset Terje Gobakken Ole Martin Bollandsås Eliakimu Zahabu Rogers Ernerst Malimbwi Håkan OlssonAbstract
No abstract has been registered
Authors
Svein Solberg Belachew Gizachew Zeleke Erik Næsset Terje Gobakken Ole Martin Bollandsås Ernest William Mauya Håkan Olsson Rogers Malimbwi Eliakimu ZahabuAbstract
No abstract has been registered
Authors
Holger Lange Lise Dalsgaard Signe Kynding Borgen O. Janne Kjønaas Ingeborg Callesen Jari Liski Line Tau StrandAbstract
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Authors
Tonje Økland Jørn-Frode Nordbakken Holger Lange Ingvald Røsberg O. Janne Kjønaas Kjersti Holt Hanssen Nicholas ClarkeAbstract
Whole-tree harvest (WTH), i.e. harvesting of forest residues (twigs, branches and crown tops) in addition to stems, for bioenergy purposes may lead to biodiversity loss and changes in species composition in forest ground vegetation, which in turn also will affect soil properties. Effects of clear-cut harvesting on ground vegetation have been investigated at two Norway spruce sites in southern east and western Norway, respectively, differing in climate and topography. Experimental plots at these two sites were either harvested conventionally (stem-only harvest, SOH), leaving harvest residues spread on the site,or WTH was carried out, with the residues collected into piles at the site for six - nine months prior to removal. Vegetation plots in the eastern site were established and analysed before WTH and SOH in 2008 and reanalysed after harvesting in 2010, 2012 and 2014. In the western site vegetation plots were established before WTH and SOH in 2010 and reanalysed after harvesting in 2012 and 2014 (and planned for 2016). All vegetation plots are permanently marked. Pre-as well as post-harvesting species abundances of all species in each vegetation plot were each time recorded as percentage cover (vertical projection) and subplot frequency. Environmental variables (topographical, soil physical, soil chemical, and tree variables) were recorded only once; before WTH and SOH. Effec ts of WTH and SOH on ground vegetation biodiversity and cover are presented.