Search

Map form information on forest biomass is required for estimating bioenergy potentials and monitoring carbon stocks. In Finland, the growing stock of forests is monitored using multi-source forest inventory, where variables are estimated in the form of thematic maps and area statistics by combining information of field measurements, satellite images and other digital map data. In this study, we used the multi-source forest inventory methodology for estimating forest biomass characteristics. The biomass variables were estimated for national forest inventory field plots on the basis of measured tree variables. The plot-level biomass estimates were used as reference data for satellite image interpretation. The estimates produced by satellite image interpretation were tested by cross-validation. The results indicate that the method for producing biomass maps on the basis of biomass models and satellite image interpretation is operationally feasible. Furthermore, the accuracy of the estimates of biomass variables is similar or even higher than that of traditional growing stock volume estimates. The technique presented here can be applied, for example, in estimating biomass resources or in the inventory of greenhouse gases.

Satellite sensor data have traditionally been used in multi-source forest inventory for estimating forest characteristics. Their advantages generally are large geographic coverage and large spectral range. Another remote sensing data source for forest inventories offering a large geographic coverage is high altitude aerial photography. In high altitude aerial photographs the spectral range is very narrow but the spatial resolution is high. This allows the extraction of texture features for forest inventory purposes. In this study we utilized a Landsat 7 ETM satellite image, a photo mosaic composed of high altitude panchromatic aerial photographs, and a combination of the aforementioned in estimating forest attributes for an area covering approximately 281 000 ha in Forestry Centre Häme-Uusimaa in Southern Finland. Sample plots of 9th National Forest Inventory (NFI9) were used as field data. In the estimation, 6 Landsat 7 ETM image channels were used. For aerial photographs, 4 image channels were composed from the spectral averages and texture features. In combining both data sources, 6 Landsat channels and 3 aerial image texture channels were selected for the analysis. The accuracy of forest estimates based on the Landsat image was better than that of estimates based on high altitude aerial photographs. On the other hand, using the combination of Landsat ETM spectral features and textural features on high altitude aerial photographs improved the estimation accuracy of most forest attributes.

Climate change mitigation requires countries to report their annual greenhouse gas (GHG) emissions and sinks, including those from land use, land use change, and forestry (LULUCF). In Finland, the LULUCF sector plays a crucial role in achieving net-zero GHG emissions, as the sector is expected to be a net sink. However, accurate estimates of LULUCF-related GHG emissions, such as methane (CH 4 ), remain challenging. We estimated LULUCF-related CH 4 emissions in Finland in 2013–2020 by combining national land cover and remote-sensed surface wetness data with CH 4 emissions estimated by an inversion model. According to our inversion model, most of Finland's CH 4 emissions were attributed to natural sources such as open pristine peatlands. However, our research indicated that forests with thin tree cover surrounding open peatlands may also be a significant source of CH 4 . Unlike open pristine peatlands and pristine peatlands with thin tree cover, surrounding transient forests are included in the Finnish GHG inventory if they meet the criteria used for forest land. The current Finnish national GHG inventory may therefore underestimate CH 4 emissions from forested organic soils surrounding open peatlands, although more precise methods and data are needed to verify this. Given the potential impact on net GHG emissions, CH 4 emissions from transitional forests on organic soils should be further investigated. Furthermore, the results demonstrate the potential of combining atmospheric inversion modelling of GHGs with diverse data sources and highlight the need for methods to more easily combine atmospheric inversions with national GHG inventories. [ABSTRACT FROM AUTHOR]

We present a data set covering three months of carbon dioxide (CO2) and energy fluxes measured by the eddy covariance method over a northern boreal lake that collects waters from a surrounding catchment dominated by upland forest and wetlands. The data period comprises more than half of the open-water period of 2013. The 30-min averages of CO2 fluxes ranged from -0.02 to 0.05 mg m-2 s-1. The monthly CO2 balances varied from 20 to 30 g m-2 (emission) between July and September, and decreased in October. A small daytime uptake of CO2, probably caused by the aquatic plants growing near the measurement mast, was observed from July to September. In September, we observed a temporary enhancement of CO2 efflux, which was attributed to both high wind speed and rapid cooling of the water and subsequent water column overturn. This peak was accompanied by a period of high sensible heat flux (SHF) from the water to the atmosphere, which is known to enhance the mixing of the water. The seasonal CO2 flux during the open-water period from the shallow part of the lake was estimated to be 120 g m-2 yr-1, which corresponds to a loss of approximately 25 g m-2 yr-1 from the terrestrial part of the catchment, assuming that the observed lake CO2 emissions result from the decomposition of the imported carbon. At midday, the net energy received by the lake was used mostly to heat the water, and only a minor part of it was converted to SHF and latent heat flux (LHF), with more energy used for the latter. While the SHF showed a clear diurnal cycle with a peak early in the morning and no flux in the afternoon, the diurnal pattern of LHF was more even, with evaporation occurring throughout the day until the freezing of the lake. Our data from this northern lake highlight the importance of thermal water mixing in the air-lake CO2 flux dynamics and imply that this flux constitutes a significant part of the annual catchment-scale carbon budget. [ABSTRACT FROM AUTHOR]

Forest characteristics vary largely at regional level and also on smaller geographic areas in Finland. The amount of greenhouse gas emissions is related to changes in biomass and for example to the soil type (e.g. upland soils vs. peatlands). Forest characteristics affects on forest management practices and on how vulnerable single stands are for disturbances. Hence, spatially accurate maps are needed for forest management planning. By means of map data we are able to consider where and which kind of operations in the forests are the most beneficial, e.g., in terms of climate change mitigation. In our study estimating and explaining spatial patterns across Finland is the main interest. For this we have analysed biomass changes on different soil and site types on forest land. The Finnish Multi-Source National Forest Inventory (MS-NFI) provide multi-temporal thematic raster layers for the whole country on large number of forest variables at pixel resolution of 16 m, e.g., timber volume and biomasses by tree species, land use class, site type (http://kartta.luke.fi/index-en.html). MS-NFI data is based satellite images (Landsat 5 TM/7 ETM+/8 OLI, Sentinel 2A-MSI, IRS P6, ALOS AVNIR-2), digital maps and NFI field data. We used MS-NFI layers from two time points to investigate the spatial variation of biomass. Silvicultural management and treatment units larger than individual pixels were created by automatic segmentation of the thematic forest maps. The segmentation of thematic maps was carried out using a modified implementation of the 'segmentation with directed trees' algorithm, which employs the local edge gradient for recognizing potential segment borders. This operation was done to decrease large random errors related to single pixel observations. We have produced segmented biomass maps and biomass change maps for the whole country. The biomass maps were evaluated with available data on forest resources, growth and drains, e.g., applying statistics on forestry or forest inventory data. The findings will be discussed in the paper including the spatial evaluation of carbon stock changes. According to previous studies the accuracy of biomass variables is relatively high and close to those on timber volumes. Distribution on forest site types according to thematic maps and field data is also analysed in the study due to it has effects to the emissions from soil. The reasons for the observed biomass changes will be studied and discussed. Decline in biomass are usually caused by timber harvesting, but also due to wind storms or deforestation. The maps on biomass provide useful tool for forest owners to analyse carbon stock changes in their forests and how to affect the amount of carbon by forest management. [ABSTRACT FROM AUTHOR]