Aim Many thematic land cover maps, such as maps of vegetation types, are based on field inventories. Studies show inconsistencies among field workers in such maps, explained by inter-observer variation in classification and/or spatial delineation of polygons. In this study, we have tested a new method to assess the accuracy of these two components independently. Location Four study sites dominated by different ecosystems in southeast Norway. Methods We have used a vegetation-based land cover classification system adapted to a map scale of 1:5,000. First, a consensus map, a map that can be considered an approximation of a flawless map, was established. Secondly, the consensus map was adapted to test the accuracy of classification and polygon delineation independently. We used 10 field workers to generate a consensus map, and 14 new field workers (in pairs) to test the accuracy (n = 7). Results The results show that the accuracy of polygon delineation is lower than that of land cover classification. This is in contrast with previous studies, but previous research designs have not enabled a separation of the two accuracy components. Conclusion We recommend strengthening the training and harmonization of field workers in general, and increasing the emphasis on polygon delineation.
There is a need for monitoring methods for forest volume, biomass and carbon based on satellite remote sensing. In the present study we tested interferometric X-band SAR (InSAR) from the Tandem-X mission. The aim of the study was to describe how accurate volume and biomass could be estimated from InSAR height and test whether the relationships were curvilinear or not. The study area was a spruce dominated forest in southeast Norway. We selected 28 stands in which we established 192 circular sample plots of 250 m2, accurately positioned by a Differential Global Positioning System (dGPS). Plot level data on stem volume and aboveground biomass were derived from field inventory. Stem volume ranged fromzero to 596 m3/ha, and aboveground biomass up to 338 t/ha.We generated 2 Digital Surface Models (DSMs) fromInSAR processing of two co-registered, HH-polarized TanDEM-X image pairs – one ascending and one descending pair.We used a Digital TerrainModel (DTM) from airborne laser scanning (ALS) as a reference and derived a 10 m × 10 m Canopy Height Model (CHM), or InSAR height model. We assigned each plot to the nearest 10 m × 10 m InSAR height pixel. We applied a nonlinear, mixed model for the volume and biomass modeling, and from a full model we removed effects with a backward stepwise approach. InSAR heightwas proportional to volume and aboveground biomass, where a 1 m increase in InSAR height corresponded to a volume increase of 23 m3/ha and a biomass increase of 14 t/ha. Root Mean Square Error (RMSE) values were 43–44% at the plot level and 19–20% at the stand level.