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Johannes Rahlf

Publications and source records attributed to Johannes Rahlf.

3 recordsLinked to original sources

Where onshore wind meets forests: electricity system planning with ecologically graded forests

Onshore wind is expected to supply much of the growth in renewables, yet its expansion increasingly extends into forests, where wind generation and forest conservation act as competing climate strategies for the same land. Net-zero system assessments typically treat forests homogeneously. Here, we grade forest exclusions by ecological value and couple them with a high-resolution net-zero electricity system model, representing onshore wind on forested and non-forested land as two distinct technologies. Applying a set of ecologically graded scenarios to Norway, we quantify how forest protection by its ecological value reshapes system design, the balance of onshore wind within and outside forests, and the robustness of these outcomes to complementary energy policy levers. At equal cost, the system treats forest as its preferred onshore resource, with forest wind comprising 60 to 90 percent of onshore capacity under permissive scenarios. Excluding forest raises system cost by up to 0.5 percent per GW of foregone forest wind, with diminishing returns as ecological criteria for forest exclusions tighten. Directing wind into forests does not compromise system efficiency, with onshore curtailment remaining largely unchanged at 3 to 8 percent. Land-use and technology decisions that appear independent may, in fact, interact, as solar deployment reshapes the value of each wind resource and determines which is displaced from the generation mix. By quantifying the ecological value forgone per unit of forest onshore wind, this study makes explicit a trade-off that energy system modelling usually leaves implicit, providing a transferable basis for balancing the competing climate strategies of protecting forests and sustaining wind expansion.

physics.soc-ph

Timber Volume Estimation Based on Airborne Laser Scanning -- Comparing the Use of National Forest Inventory and Forest Management Inventory Data

Large-scale forest resource maps based on national forest inventory (NFI) data and airborne laser scanning may facilitate synergies between NFIs and forest management inventories (FMIs). A comparison of models used in such a NFI-based map and a FMI indicate that NFI-based maps can directly be used in FMIs to estimate timber volume of mature spruce forests. Traditionally, FMIs and NFIs have been separate activities. The increasing availability of detailed NFI-based forest resource maps provides the possibility to eliminate or reduce the need of field sample plot measurements in FMIs if their accuracy is similar. We aim to 1) compare a timber volume model used in a NFI-based map and models used in a FMI, and 2) evaluate utilizing additional local sample plots in the model of the NFI-based map. Accuracies of timber volume estimates using models from an existing NFI-based map and a FMI were compared at plot and stand level. Estimates from the NFI-based map were similar to or more accurate than the FMI. The addition of local plots to the modeling data did not clearly improve the model of the NFI-based map.The comparison indicates that NFI-based maps can directly be used in FMIs for timber volume estimation in mature spruce stands, leading to potentially large cost savings.

stat.AP

National mapping and estimation of forest area by dominant tree species using Sentinel-2 data

Nation-wide Sentinel-2 mosaics were used with National Forest Inventory (NFI) data for modelling and subsequent mapping of spruce, pine and deciduous forest in Norway in 16 m $\times$ 16 m resolution. The accuracies of the best model ranged between 74% for spruce and 87% for deciduous forest. An overall accuracy of 90% was found on stand level using independent data from more than 42.000 stands. Errors mostly resulting from a forest mask reduced the model accuracies by approximately 10%. Nonetheless, efficiencies of national forest area estimates increased by 20% to 50% for model-assisted (MA) estimates and up to 90% for poststratification (PS). Greater minimum number of observations, however, constrained the use of PS. For estimates of sub-populations (municipalities), efficiencies improved by up to a factor of 8. However, even for municipalities with a decent number of NFI plots, direct NFI estimates were sometimes more precise than MA estimates. PS estimates were always more precise than direct and MA estimates but were applicable in fewer municipalities. The tree species prediction map is freely available as part of the Norwegian forest resource map and is used, among others, to improve maps of other variables of interest such as timber volume and biomass.

stat.AP