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We investigated if coarse-resolution satellite data from the MODIS sensor can be used for regional monitoring of insect disturbances in Fennoscandia. A damage detection method based on z-scores of seasonal maximums of the 2-band Enhanced Vegetation Index (EVI2) was developed. Time-series smoothing was applied and Receiver Operating Characteristics graphs were used for optimisation. The method was developed in fragmented and heavily managed forests in eastern Finland dominated by Scots pine ( L.) (pinaceae) and with defoliation of European pine sawfly ( Geoffr.) (Hymenoptera: Diprionidae) and common pine sawfly ( L.) (Hymenoptera: Diprionidae). The method was also applied to subalpine mountain birch ( N.I. Orlova) forests in northern Sweden, infested by autumnal moth (Borkhausen) and winter moth ( L.). In Finland, detection accuracies were fairly low with 50% of the damaged stands detected, and a misclassification of healthy stands of 22%. In areas with long outbreak histories the method resulted in extensive misclassification. In northern Sweden accuracies were higher, with 75% of the damage detected and a misclassification of healthy samples of 19%. Our results indicate that MODIS data may fail to detect damage in fragmented forests, particularly when the damage history is long. Therefore, regional studies based on these data may underestimate defoliation. However, the method yielded accurate results in homogeneous forest ecosystems and when long-enough periods without damage could be identified. Furthermore, the method is likely to be useful for insect disturbance detection using future medium-resolution data, e.g. from Sentinelâ2.Pinus sylvestrisNeodiprion sertiferDiprion piniBetula pubescensssp. Czerepanovii Epirrita autumnata Operophtera brumata

Digital Twins are realistic digital representations of the physical world, frequently characterised by a two way link between digital and physical. Originating in manufacturing, they are now expanding to city and national scales. In this paper we explore connections between Geographic Information Science and National Digital Twins. Six different viewpoints and perspectives are presented on the topic, highlighting the importance of: geospatial data engineering; metadata engineering; standards; challenges facing mapping agencies; governance and public values; and a "reality check" that explores the gaps between what is required and what can currently be achieved. We present 22 recommendations and summarise the findings by presenting a high level research agenda to enable better understanding and articulation of the link between the two. [ABSTRACT FROM AUTHOR]

Monitoring crop growth and estimating crop yield are essential for managing agricultural production, ensuring food security, and maintaining sustainable agricultural development. Combining the mechanistic framework of a crop growth model with remote sensing observations can provide a means of generating realistic and spatially detailed crop growth information that can facilitate accurate crop yield estimates at different scales. The main objective of this study was to develop a robust estimation methodology of within-field winter wheat yield at a high spatial resolution (20 m × 20 m) by combining a light use efficiency-based model and Sentinel-2 data. For this purpose, Sentinel-2 derived leaf area index (LAI) time series were assimilated into the Simple Algorithm for Yield Estimation (SAFY) model using an ensemble Kalman filter (EnKF). The study was conducted on rainfed winter wheat fields in southern Sweden. LAI was estimated using vegetation indices (VIs) derived from Sentinel-2 data with semi-empirical models. The enhanced two-band vegetation index (EVI2) was found to be a useful VI for LAI estimation, with a coefficient of determination (R2) and a root mean square error (RMSE) of 0.80 and 0.65 m2/m2, respectively. Our findings demonstrate that the assimilation of LAI derived from Sentinel-2 into the SAFY model using EnKF enhances the estimation of within-field spatial variability of winter wheat yield by 70% compared to the baseline simulation without the assimilation of remotely sensed data. Additionally, the assimilation of LAI improves the accuracy of winter wheat yield estimation by decreasing the RMSE by 53%. This study demonstrates an approach towards practical applications of freely accessible Sentinel-2 data and a crop growth model through data assimilation for fine-scale mapping of crop yield. Such information is critical for quantifying the yield gap at the field scale, and to aid the optimization of management practices to increase crop production. [ABSTRACT FROM AUTHOR]

Biogenic volatile organic compound (BVOC) emissions from trees subjected to biotic stress are higher compared to healthy trees, and they may also have a different compound composition. This in turn affects atmospheric chemistry and can lead to either positive or negative feedback to the climate. Climate change favors the abundance of the European spruce bark beetle (Ips typographus) which attacks the bark of Norway spruce (Picea abies) trees, causing induced BVOC emissions from the trees as a response to the insect stress. Here, results are reported from a study analyzing the difference in emission rates between healthy and bark-beetle-infested Norway spruce trees, changes in emission rates over time since the infestation started, and differences in emission rates from bark-beetle-drilled entry and exit holes. Bark chamber measurements on both healthy and infested trees were performed during the summer of 2019 at Hyltemossa and Norunda research stations in Sweden. The measurements showed that induced BVOC emissions following the bark beetle infestation were dominated by entry hole emissions in the early growing season and exit hole emissions in the later season. The results showed a significant difference in emission rates between healthy and infested trees during both seasons. The seasonal average standardized BVOC emission rate of healthy trees was 32 ± 52 µ g m -2 h -1 (mean ± standard deviation), while the average standardized BVOC emission rates of infested trees were 6700 ± 6900 and 2000 ± 1300 µ g m -2 h -1 during the early and late season respectively. BVOC emission rates were highest at the start of the infestation and decreased exponentially with time, showing induced emission rates for up to 1 year after which the emission rates were similar to those from healthy bark. Constitutive needle emission rates from healthy trees were found to be 11 times higher than bark emissions from healthy trees. However, when Norway spruce trees were infested, the bark emission rates were instead 6 to 20 times higher than the needle emissions, causing substantial increases in the total tree BVOC emission rate. This could lead to high impacts on atmospheric processes, specifically the formation of secondary organic aerosols, which have a higher yield from some monoterpene compounds, which increased from infested trees. [ABSTRACT FROM AUTHOR]

Emissions of biogenic volatile organic compound (BVOC) from the bark of Norway spruce (Picea abies) trees can be affected by stress, such as infestation of spruce bark beetles (Ips typographus). We studied the difference in emission rates from healthy spruce bark and infested spruce bark, the influence of time since spruce bark beetle infestation started and the difference in emission rates from bark beetle drilled entry holes and exit holes. Bark chamber measurements on both healthy trees and infested trees were performed during the summer of 2019 at two sites in Sweden. To consider the seasonal pattern of the spruce bark beetle, we divided the emission rates from infested trees into two seasons, an early season dominated by entry holes and a late season with mainly exit holes. Our findings show a significant difference in emission rates from healthy and infested trees, independent of season. The seasonal average standardized emission rate from healthy trees was 31.89 ± 51.67 µg m-2 h-1 (mean ± standard deviation), while the average standardized emission rates from infested trees were 6385 µg m-2 h-1 and 2102 µg m-2 h-1 during early and late season respectively. We also found an exponentially decreasing relationship with BVOC emission rates and time since infestation started where the emission rates reached the same level as the constitutive BVOC emission rates from bark after around one year. When comparing bark monoterpene BVOC emission rates with emission rates from needles, we found that the constitutive needle emission rates were 11 times higher than the constitutive bark emissions. However, the emission rates from infested Norway spruce tree bark were instead 6 to 20 times higher than the constitutive needle emissions, causing substantial increases in the total tree BVOC emission rate (550 % to 1900 % increase). This study adds evidence that spruce bark beetle induced bark BVOC emissions are higher than previously thought and highlights the need for further research with more samples more frequently throughout the season to fully understand the impact, which is required to quantify spruce bark beetle infestations impacts on the atmospheric chemistry and climate change. [ABSTRACT FROM AUTHOR]

The Artic is exposed to faster temperature changes than most other areas on Earth. Constantly increasing temperature will lead to thawing permafrost and changes in the CH4 emissions from wetlands. One of the places exposed to those changes is the Abisko-Stordalen Mire in northern Sweden, where climate and vegetation studies have been conducted from the 1970s.In our study, we analyzed field-scale methane emissions measured by the eddy covariance method at Abisko-Stordalen Mire for three years (2014-2016). The site is a subarctic mire mosaic of palsas, thawing palsas, fully thawed fens, and open water bodies. A bimodal wind pattern prevalent at the site provides an ideal opportunity to measure mire patches with different permafrost statuses with one flux measurement system. The flux footprint for westerly winds is dominated by elevated palsa plateaus, while the footprint is almost equally distributed between palsas and thawing bog-like areas for easterly winds. As these patches are exposed to the same climatic conditions, we analyzed the differences in the responses of their methane emission for environmental parameters. The methane fluxes followed a similar annual cycle over the three study years, with a gentle rise during spring and a decrease during autumn and with no emission burst at either end of the ice-free season. The peak emission during the ice-free season differed significantly for the mire with two permafrost statuses: the palsa mire emitted 24 mg-CH4 m-2 d-1 and the thawing wet sector 56 mg-CH4 m-2 d-1. Factors controlling the methane emission were analyzed using generalized linear models. The main driver for methane fluxes was peat temperature for both wind sectors. Soil water content above the water table emerged as an explanatory variable for the three years for western sectors and the year 2016 in the eastern sector. Water table level showed a significant correlation with methane emission for the year 2016 as well. Gross primary production, however, did not show a significant correlation with methane emissions. Annual methane emissions were estimated based on four different gap-filing methods. The different methods generally resulted in very similar annual emissions. The mean annual emission based on all models was 4.2 ± 0.4 g- CH4 m-2 a-1 for western sector and 7.3 ± 0.7 g- CH4 m-2 a-1 for the eastern sector. The average annual emissions, derived from this data and a footprint climatology, were 3.6 ± 0.7 g-CH4 m-2 a-1 and 11 ± 2 g- CH4 m-2 a-1 for the palsa and thawing surfaces, respectively. Winter fluxes were relatively high, contributing 27-45 % to the annual emissions. [ABSTRACT FROM AUTHOR]

It is projected that forest disturbances, such as insect outbreaks, will have an increasingly negative impact on forests with a warmer climate. These disturbance events can have a substantial impact on forests' ability to absorb atmospheric CO2, and may even turn forests from carbon sinks into carbon sources; hence, it is important to develop methods to both monitor forest disturbances and to quantify the impact of these disturbance events on the carbon balance. In this study we present a method to monitor insect induced defoliation in a subarctic birch forest in northern Sweden, and to quantify the impact of these outbreaks on gross primary productivity (GPP). Since frequent cloud cover in the study area requires data with high temporal resolution and limits the use of finer spatial resolution sensors such as Landsat, defoliation was mapped with remote sensing data from the MODIS sensor with 250 × 250 m spatial resolution. The impact on GPP was estimated with a light use efficiency (LUE) model that was calibrated with GPP data obtained from eddy covariance (EC) measurements for years with undisturbed birch forest and for years with insect induced defoliation. Two methods were applied to estimate the impact on GPP: (1) A GPP reduction factor derived from EC-measured GPP was applied to estimate GPP loss, and (2) a LUE model was run both for undisturbed and defoliated forest and the differences in modelled GPP were derived. In the study area of 100 km2 the results showed a total decrease in carbon uptake over three outbreak years 2004, 2012, and 2013 of 44.6 ± 13 Gg C, which is of the same magnitude as the estimated annual GPP of 41.1 ± 12 Gg C for a year without disturbance. In the most severe outbreak year (2012), 76% of the birch forests were defoliated and annual GPP was merely 50% of GPP for years without disturbances. The study has generated valuable data that improve previous studies on impact estimates and demonstrates a potential for mapping insect disturbance impact over extended areas. [ABSTRACT FROM AUTHOR]

The current three-dimensionally (3D) delimited property units are in most countries registered using two-dimensional (2D) documentation and textual descriptions. This approach has limitations if used for representing the actual extent of complicated 3D property units, in particular in city centers. 3D digital models such as building information model (BIM) and 3D geographic information system (GIS) could be utilized for accurate identification of property units, better representation of cadastral boundaries, and detailed visualization of complex buildings. To facilitate this, several requirements need to be identified considering organizational, legal, and technical aspects. In this study, we formulate these requirements and then develop a framework for integration of 3D cadastre and 3D digital models. The aim of this paper is that cadastral information stored based on the land administration domain model (LADM) are integrated with BIM on building level for accurate representation of legal boundaries and with GIS on city level for visualization of 3D cadastre in urban environments. The framework is implemented and evaluated against the requirements in a practical case study in Sweden. The conclusion is that the integration of the cadastral information and BIM/GIS is possible on both conceptual level and data level which will facilitate that organizations dealing with cadastral information (cadastral units), BIM models (architecture, engineering, and construction companies), and GIS (surveying units on e.g., municipality level) can exchange information; this facilitates better representation and visualization of 3D cadastral boundaries. [ABSTRACT FROM AUTHOR]