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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]

One of the biggest challenges in urban densifications is securing adequate daylight access. This study examines the potential of using semantic 3D city models as input to daylight simulations. It is focusing on investigating input data requirements to these simulations from a geodata, 3D city model specification and measuring guideline perspective. To achieve this, geodata simulation input requirements for the most common daylight metrics are documented. Next, 3D city model data from two Swedish municipalities along with 3D data constructed by ourselves in CAD- and GIS-environments are utilized to explore the impact of using 3D city models of different levels of detail (LOD) and positional accuracy in daylight simulations linked to Swedish and European laws and recommendations. Similarly, the measuring guidelines and 3D city model specification requirements related to balconies and other façade accessories are also evaluated along with the utilization of façade reflectance properties and colour. It is found that LOD1 is sufficient for the obstruction angle metric for most roof types but for e.g., gabled roofs LOD2 should be used. A positional accuracy on a decimetre-level is accurate enough for the aforementioned metric. Daylight factor simulations require that balconies and façade accessories protruding more than a couple of decimetres must be represented in the 3D city model along with information on façade material and colour. The outcome of the study is expressed in the form of a list of recommendations for the creation of national profiles of 3D city models supporting daylight simulations. [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 Arctic is exposed to even faster temperature changes than most other areas on Earth. Constantly increasing temperature will lead to thawing permafrost and changes in the methane (CH 4) 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 since the 1970s. In our study, we analyzed field-scale methane emissions measured by the eddy covariance method at Abisko–Stordalen Mire for 3 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 status with one flux measurement system. The flux footprint for westerly winds was dominated by elevated palsa plateaus, while the footprint was almost equally distributed between palsas and thawing bog-like areas for easterly winds. As these patches are exposed to the same climatic and weather 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 3 study years, with a gentle rise during spring and a decrease during autumn, without emission bursts at either end of the ice-free season. The peak emission during the ice-free season differed significantly for the two mire areas with different permafrost status: the palsa mire emitted 19 mg-C m -2 d -1 and the thawing wet sector 40 mg-C 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 3 years for western sectors and the year 2016 in the eastern sector. The 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 3.1 ± 0.3 g-C m -2 a -1 for the western sector and 5.5 ± 0.5 g-C m -2 a -1 for the eastern sector. The average annual emissions, derived from these data and a footprint climatology, were 2.7 ± 0.5 and 8.2 ± 1.5 g-C 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]

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 both to 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 de- foliation 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 250m x 250m 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 from 5 years with undisturbed birch forest and 1 year with insect-induced de- foliation. Two methods were applied to estimate the impact on GPP: (1) applying a GPP reduction factor derived from EC measured GPP to estimate GPP loss, and (2) running a LUE model for both undisturbed and defoliated forest and deriving the differences in modelled GPP. In the study area of 100 km² the results suggested a substantial setback to the carbon uptake: an average decrease in regional GPP over the three outbreak years (2004, 2012, and 2013) was estimated to 15±5Gg C yr-1, compared to the mean regional GPP of 40±12Gg C yr-1 for the 5 years without defoliation, i.e. 38%. In the most severe outbreak year (2012), 76% of the birch forests were defoliated, and annual regional GPP was merely 50% of GPP for years without disturbances. The study has generated valuable data on GPP reduction, and demonstrates a potential for mapping insect disturbance impact over extended areas. [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]

Unmanned aerial systems (UAS) carrying commercially sold multispectral sensors equipped with a sunshine sensor, such as Parrot Sequoia, enable mapping of vegetation at high spatial resolution with a large degree of flexibility in planning data collection. It is, however, a challenge to perform radiometric correction of the images to create reflectance maps (orthomosaics with surface reflectance) and to compute vegetation indices with sufficient accuracy to enable comparisons between data collected at different times and locations. Studies have compared different radiometric correction methods applied to the Sequoia camera, but there is no consensus about a standard method that provides consistent results for all spectral bands and for different flight conditions. In this study, we perform experiments to assess the accuracy of the Parrot Sequoia camera and sunshine sensor to get an indication if the quality of the data collected is sufficient to create accurate reflectance maps. In addition, we study if there is an influence of the atmosphere on the images and suggest a workflow to collect and process images to create a reflectance map. The main findings are that the sensitivity of the camera is influenced by camera temperature and that the atmosphere influences the images. Hence, we suggest letting the camera warm up before image collection and capturing images of reflectance calibration panels at an elevation close to the maximum flying height to compensate for influence from the atmosphere. The results also show that there is a strong influence of the orientation of the sunshine sensor. This introduces noise and limits the use of the raw sunshine sensor data to compensate for differences in light conditions. To handle this noise, we fit smoothing functions to the sunshine sensor data before we perform irradiance normalization of the images. The developed workflow is evaluated against data from a handheld spectroradiometer, giving the highest correlation (R2 = 0.99) for the normalized difference vegetation index (NDVI). For the individual wavelength bands, R2 was 0.80–0.97 for the red-edge, near-infrared, and red bands. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a proposal for a national building standard in Sweden. We define requirements for the proposed standard, e.g., it should support development of 3D city models, connect to building information models (BIM) and national registers and be based on a national classification system for the urban environment. Based on these requirements we develop an Application Domain Extension (ADE) of the building model in the proposed CityGML 3.0 standard denoted CityGML Sve-Test. CityGML 3.0 includes several new features of interest, e.g., the space concept, enhanced possibilities to convert data, and to link to other standards. In our study we create test data according to CityGML Sve-Test and evaluate it against the requirements. It is shown that BIM models (in Industry Foundation Classes, IFC, format) can be converted to CityGML Sve-Test and that a classification system facilitates this conversion. The CityGML Sve-Test dataset can be used to increase the automation level in building permissions checking and a related study shows that CityGML 3.0 has capabilities to link to legal information and be a base for 3D cadastral index maps. Based on our experience, we suggest that the national building standard should conform to international standards and, if possible, include a classification system. The exchange format (GML, JSON etc.) might change, but to be based on a standardized data model ensures harmonized structures and concepts. [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]

Miniaturized thermal infrared (TIR) cameras that measure surface temperature are increasingly available for use with unmanned aerial vehicles (UAVs). However, deriving accurate temperature data from these cameras is non-trivialsince they are highly sensitive to changes in their internal temperature and low-cost models are often not radiometrically calibrated. We present the results of laboratory and field experiments that tested the extent of the temperature-dependency of a non-radiometric FLIR Vue Pro 640. We found that a simple empirical line calibration using at least three ground calibration points was sufficient to convert camera digital numbers to temperature values for images captured during UAV flight. Although the camera performed well under stable laboratory conditions (accuracy ±0.5 °C), the accuracy declined to ±5 °C under the changing ambient conditions experienced during UAV flight. The poor performance resulted from the non-linear relationship between camera output and sensor temperature, which was affected by wind and temperature-drift during flight. The camera's automated non-uniformity correction (NUC) could not sufficiently correct for these effects. Prominent vignetting was also visible in images captured under both stable and changing ambient conditions. The inconsistencies in camera output over time and across the sensor will affect camera applications based on relative temperature differences as well as user-generated radiometric calibration. Based on our findings, we present a set of best practices for UAV TIR camera sampling to minimize the impacts of the temperature dependency of these systems. [ABSTRACT FROM AUTHOR]

The building permission process is to a large extent an analogue process where much information is handled in paper format or as pdf files. With the ongoing digitalisation in society, there is a potential to automate this process by integrating Building Information Models (BIM) of planned buildings and geospatial data to check if a building conforms to the building permission regulations. In this study, an inventory of which regulations in the (Swedish) detailed development plans that can be automatically checked or supported by 3D visualisation was conducted. Then, two of these regulations, the building height and the building footprint area, were studied in detail to find to which extent they can be automatically checked by integration of BIM and geospatial data. In addition, a feasibility study of one visual criterion was conducted. One concern when automating the building permission process is the variability of content within the Industry Foundation Classes (IFC) data model. Variations in modelling methods and model content leads to differences in IFC models' content and structure; these differences complicate automated processes. To facilitate automated processes, requirements on the production of IFC models for building permission applications could be defined in the form of model view definitions or delivery specifications. [ABSTRACT FROM AUTHOR]