Airborne Laser Scanning (ALS) has implied a disruptive transformation of how data are gathered for forest management planning in Nordic countries. We show in this study that the accuracy of ALS ...predictions of growing stock volume can be maintained and even improved over time if they are forecasted and assimilated with more frequent but less accurate remote sensing data sources like satellite images, digital photogrammetry, and InSAR. We obtained these results by introducing important methodological adaptations to data assimilation compared to previous forestry studies in Sweden. On a test site in the southwest of Sweden (58°27′N, 13°39′E), we evaluated the performance of the extended Kalman filter and a proposed modified filter that accounts for error correlations. We also applied classical calibration to the remote sensing predictions. We evaluated the developed methods using a dataset with nine different acquisitions of remotely sensed data from a mix of sensors over four years, starting and ending with ALS-based predictions of growing stock volume. The results showed that the modified filter and the calibrated predictions performed better than the standard extended Kalman filter and that at the endpoint the prediction based on data assimilation implied an improved accuracy (25.0% RMSE), compared to a new ALS-based prediction (27.5% RMSE).
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•Yield capacity describing forest site productivity was expressed through site index.•Observations from permanent plots in long-term experiments give valid reference estimates of total volume ...production.•Variations in volume yield levels are explained in a larger extent by basal area levels.•The yield capacity functions can be used to compare tree species’ production under similar management regimes.•The functions offer far-reaching support for assessing climate change mitigation potential of boreal forests in northern Europe.
Information on forest site productivity is a key component to assess the carbon sequestration potential of boreal forests. While site index (SI) is commonly used to indicate forest site productivity, expressions of SI in the form of yield capacity (potential maximum mean annual volume increment) is desirable since volume yield is central to the economic and ecological analyses of a given species and site. This paper assessed the functional relationship between SI and yield capacity on the basis of yield plot data from long-term experiments measured over several decades for Norway spruce (Picea abies), Scots pine (Pinus sylvestris), Lodgepole pine (Pinus contorta) and Larch (Larix decidua and Larix sibirica) in Sweden. Component models of total basal area and volume yield were also developed. SI was determined by existing height development functions using top height and age, whereas functions for stand-level (m2 ha−1) basal area development were constructed based on age, SI and initial stand density using difference equations and nonlinear mixed-effects models. The relation between volume yield (m3 ha−1) and top height was adjusted with total basal area production through nonlinear mixed-effects models. Species-specific parametric regression models were used to construct functional relationships between SI and yield capacity. The root mean square errors of the species-specific models ranged from 2 to 6% and 10–18% of the average values for the basal area and volume equations, respectively. For the yield capacity functions, the explained variations (R2) were within 80–96%. We compared our yield capacity functions to earlier functions of the species and significant differences were observed in both lower and higher SI classes, especially, for Scots pine and Norway spruce. The new functions give better prediction of yield capacity in current growing conditions; hence, they could later be used for comparing tree species’ production under similar site and management regimes in Sweden.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•We explored the potential of bi-temporal ALS data for site index estimation.•Species-specific site index models were developed using NFI and ALS data.•ALS estimated height and height increment were ...key predictors of site index.•Validation checks indicate that the functions seem suitable for their purpose.•Nationwide site index maps are provided at a resolution of 12.5 × 12.5 m.
Recent advancements in remote sensing of forests have demonstrated the capabilities of three-dimensional data acquired by airborne laser scanning (ALS) and, consequently, have become an integral part of enhanced forest inventories in Northern Europe. In Sweden, the first national laser scanning revolutionised forest management planning through low-cost production of large-scale and spatially explicit maps of forest attributes such as basal area, volume, and biomass, compared to the earlier practice based on field survey data. A second scanning at the national level was launched in 2019, and it provides conditions for the estimation of height growth and site index. Accurate and up-to-date information about site productivity is relevant for planning silvicultural treatments and for the prognosis of forest status and development over time. In this study, we explored the potential of bi-temporal ALS data and other auxiliary information to predict and map site productivity by site index according to site properties (SIS) of Norway spruce (Picea abies (L.) Karst) and Scots pine (Pinus sylvestris L.) in even-aged stands in Sweden. We linked ground survey data of SIS from more than 11,500 plots of the Swedish National Forest Inventory (NFI) to bi-temporal ALS data to predict and map site index using an area-based method and two regression modelling strategies: (1) a multiple linear regression (MLR) model with an ordinary least-squares parameter estimation method, and (2) a non-parametric random forests (RF) model optimised for hyper-parameter tuning. For model development, permanent plots were used, whereas the validation was done on the temporary plots of the Swedish NFI and an independent stand-level dataset. Species-specific models were developed, and the root mean square error (RMSE) metric was used to quantify the residual variability around model predictions. For both species, the MLR model gave precise and accurate estimates of SIS. The RMSE for SIS predictions was in the range of 1.96 – 2.11 m, and the relative RMSE was less than 10 % (7.68 – 9.49 %) of the reference mean value. Final predictors of site index include metrics of 90th percentile height and annual increment in the 95th percentile height, altitude, distance to coast, and soil moisture. Country-wide maps of SIS and the corresponding pixel-level prediction errors at a spatial resolution of 12.5 m grid cells were produced for the two species. Independent validations show the site index maps are suitable for use in operational forest management planning in Sweden.
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Data assimilation (DA) is often used for merging observations to improve the predictions of the current and future states of characteristics of interest. In forest inventory, DA has so far found ...limited use, although dense time series of remotely sensed (RS) data have become available for estimating forest characteristics. A problem in forest inventory applications based on RS data is that errors from subsequent predictions tend to be strongly correlated, which limits the efficiency of DA. One reason for such a correlation is that model-based predictions, using techniques such as parametric or non-parametric regression, are normally biased conditional on the actual ground conditions, although they are unbiased conditional on the RS predictor variables. A typical case is that predictions are shifted towards the mean, i.e., small true values are overestimated, and large true values are underestimated. In this study, we evaluated if the classical calibration of RS-based predictions could remove this type of bias and improve DA results. Through a simulation study, we mimicked growing stock volume predictions from two different sensors: one from a metric strongly correlated with growing stock volume, mimicking airborne laser scanning, and one from a metric slightly less correlated with growing stock volume, mimicking data obtained from 3D digital photogrammetry. Consistent with previous findings, in areas such as chemistry, we found that classical calibration made the predictions approximately unbiased. Further, in most cases, calibration improved the DA results, evaluated in terms of the root mean square error of predicted volumes, evaluated at the end of a series of ten RS-based predictions.
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•Height growth of Norway spruce and Scots pine were assessed from 1986 to 2018.•Trees grew faster than before, especially after the millennium shift.•Increased growth correlated ...positively with temperature but not precipitation.•Growth increases may suggest higher forest value and shorter rotation periods.
For boreal forests in colder climates, changes in environmental conditions are hypothesised to substantially affect ecosystem processes. In this study, trends of top height growth of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst) were analysed using permanent sample plot data from more than 300 long-term experimental sites distributed from temperate zones to the boreal forest conditions in Sweden. By regression analyses, the effects of temperature-sum and precipitation-sum on top height growth were assessed in the period 1986–2018. A significant upward temporal trend in height growth was observed for both species, with the trend more pronounced after the millennium shift. The magnitude of the annual relative height growth after the millennium was about 16.92% and 9.54% higher than expected, respectively for Scots pine and Norway spruce. A potential climate response on height growth was found for both species with temperature-sum positively correlated with top height growth. No significant effect of precipitation-sum on height growth was observed for either species. Our results suggest improved growing conditions and forest sites became more productive in response to increasing temperature in the northern temperate and boreal regions. The increasing growth trends may offer shorter rotation periods and increased forest value for Norway spruce and Scots pine, coupled with contributions of boreal forests to the emerging bio-economy and the regulation of global atmospheric carbon.
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Accurate and up-to-date data about growing stock volume are essential for forest management planning. Airborne Laser Scanning (ALS) is known for producing accurate wall-to-wall predictions but the ...data are at present collected at long time intervals. Digital Photogrammetry (DP) is cheaper and often more frequently available but known to be less accurate. This study investigates the potential of using contemporary DP data together with older ALS data and compares this with the case when only old ALS data are trained with recent field data. Combining ALS data from 2010 to 2011 with DP data from 2015, both trained with National Forest Inventory (NFI) field plot data from 2015, improved predictions of growing stock volume. Validation using data from 100 stands inventoried in 2015 gave an RMSE of 24.3% utilizing both old ALS data and recent DP data, 26.0% for old ALS only and 24.9% for recent DP only. If information about management actions were assumed available, combining old ALS and recent DP gave RMSE of 23.0%, only ALS 23.3% and only DP 23.8%.
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The prediction of tree biomass and stem volume is necessary for monitoring and assessing of national forest biomass, carbon stock and sustainable forest management. Such predictions of biomass or ...carbon stocks are generated by using either allometric models or applying biomass expansion factors (BEFs), where the former is a better method. Volume models are generated by using allometric models. The data for development of the new volume and biomass models for Iceland presented in this paper were collected between years 2000-2021, from 48 locations in even aged stands that were planted between 1942-1983. Because of the young age of forest plantations in Iceland, existing biomass and volume models need to be updated regularly as trees get older and larger. The new models use the same independent variables as the previous ones for Iceland but use a wider approach and have a different form than the older ones. Using the previous Icelandic models outside their data range results in underestimation for both aboveground biomass and stem volume.
Structural violence is harm done to individuals or groups through the normalization of social inequalities in political-economic organization. Researchers working in both modern and prehistoric ...contexts focus on the lived experiences of individuals and the health disparities that arise from such violence. With this article, I seek to contribute to this literature by considering how skeletal evidence of dissection from the 19th-century United States reflects structural violence. I focus on "death experiences" and suggest that studies of structural violence must consider not only how inequality may be embodied as health disparities in the living but also "disembodiment" and the treatment and fate of the dead body. Violencia estructural es el daño hecho a individuos o grupos a través de la normalización de desigualdades sociales en una organización político-económica. Investigadores trabajando en contextos tanto modernos como prehistóricos se centran en las experiencias vividas por individuos y las disparidades en salud surgidas de tal violencia. Con este artículo, busco contribuir a ésta literatura a través de considerar cómo evidencia esqueletal de disección del siglo XIX en los Estados Unidos refleja violencia estructural. Me enfoco en las "experiencias de muerte" y sugiero que estudios de violencia estructural deben considerar no sólo cómo la desigualdad puede ser corporizada como disparidades en salud en el viviente, sino también en "descorporización" y el tratamiento y destino del cuerpo muerto.
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The aim of this study was to investigate the profitability of management regimes including both early biomass thinning (leaving 4000 stems/ha and using systematic boom-corridor thinning) and ...conventional production of pulp and timber. Empirical data obtained from five dense (11,000-20,000 stems/ha) naturally regenerated Scots pine experimental plots in which pre-commercial thinning (PCT) to 2500 stems/ha and control treatments (no PCT) were originally applied were used to initiate simulations. Biomass thinning was simulated at mean heights 6-7 m (BIO1) and 8-9 m (BIO2) in control plots. Land expectation values (LEVs) were calculated (3% interest rate), after simulating stands development to final harvest. Given the targeted stand stem density, 36-67 oven dry tons/ha were harvested in the simulations. Compared with PCT, both BIO regimes resulted in a somewhat lower average tree size in all subsequent harvest operations but a higher LEV in four of the five stands, if thinning was integrated with bundling. Higher LEVs (on average 27%) were achieved when BIO2 was applied compared to BIO1. Consequently, high biomass removal from dense Scots pine stands early in rotation periods might provide substantial economic benefits for forest owners, but appropriate general decision tools are needed to maximize profit.
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The development of remote sensing methods through research and large-scale application nowadays makes it possible to obtain stand-level estimates of forest variables at short intervals and at low ...cost. This offers substantial possibilities to forestry practitioners, but it also poses challenges regarding how cost-efficient data acquisition strategies should be developed. For example, should cheap but low-quality data be acquired and discarded whenever new data become available or should investments be made in high-quality data that are continuously updated to last over a longer period of time? We suggest that the solution could be to establish data assimilation (DA) procedures linked to forest inventories to make appropriate use of data from several sources. With DA, old information is updated through growth forecasts and when new information becomes available it is assimilated with the old information; the different sources of information are made use of to the extent motivated by their accuracy. In this study we made a general assessment of the usefulness of DA in connection with stand-level forest inventories and we compared two different methodological approaches, the extended Kalman filter and the Bayesian method. Not surprisingly, the relative advantage of DA was found to be largest for cases where low-precision estimates of growing stock volume were obtained at short intervals and forecasts were made with accurate growth prediction models. The methodological comparison revealed a tendency of the extended Kalman filter to underestimate the variance of the estimates.
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