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"Olsson, Ola"
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Essentials of advanced macroeconomic theory
\"Trying to summarize the essentials of macroeconomic theory in the wake of the financial crisis that has shaken not only Western economies but also the macroeconomic profession is no easy task. In particular, the notion that markets are self-correcting and always in equilibrium appears to have taken a heavy blow. However, the jury is still out on which areas should be considered as failures and what which constitute the future of research. The overall aim of this text is to provide a compact overview of the contributions that are currently regarded as the most important for macroeconomic analysis and to equip the reader with the essential theoretical knowledge that all advanced students in macroeconomics should be acquainted with. The result is a compact text that should act as the perfect complement to further study of macroeconomics: an introduction to the key concepts discussed in the journal literature and suitable for students from upper undergraduate level through to PhD courses.\"--Publisher's website.
Book
Challenges and Best Practices for Deriving Temperature Data from an Uncalibrated UAV Thermal Infrared Camera
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.
Journal Article
model for habitat selection and species distribution derived from central place foraging theory
We have developed a habitat selection model based on central place foraging theory. An individual’s decision to include a patch in its habitat depends on the marginal fitness contribution of that patch, which is characterized by its quality and distance to the central place. The essence of the model we have developed is a fitness isocline which is a function of patch quality and travel time to the patch. It has two parameters: the maximum travel distance to a patch of infinite quality and a coefficient that appropriately scales quality by travel time. Patches falling below the isocline will have positive marginal fitness values and should be included in the habitat. The maximum travel distance depends on the availability and quality of patches, as well as on the forager’s life history, whereas the scaling parameter mostly depends on life history properties. Using the model, we derived a landscape quality metric (which can be thought of as a connectivity measure) that sums the values of available habitat in the landscape around a central place. We then fitted the two parameters to foraging data on breeding white storks (Ciconia ciconia) and estimated landscape quality, which correlated strongly with reproductive success. Landscape quality was then calculated for a larger region where re-introduction of the species is currently going on in order to demonstrate how this model can also be regarded as a species distribution model. In conclusion, we have built a general habitat selection model for central place foragers and a novel way of estimating landscape quality based on a behaviorally scaled connectivity metric.
Journal Article
Automation of Building Permission by Integration of BIM and Geospatial Data
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.
Journal Article
Radiometric Correction of Multispectral UAS Images: Evaluating the Accuracy of the Parrot Sequoia Camera and Sunshine Sensor
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.
Journal Article
Wheat Yield Estimation at High Spatial Resolution through the Assimilation of Sentinel-2 Data into a Crop Growth Model
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.
Journal Article
Combining Sentinel-2 Data and Risk Maps to Detect Trees Predisposed to and Attacked by European Spruce Bark Beetle
The European spruce bark beetle is a major disturbance agent in Norway spruce forests in Europe, and with a changing climate it is predicted that damage will increase. To prevent the bark beetle population buildup, and to limit further spread during outbreaks, it is crucial to detect attacked trees early. In this study, we utilize Sentinel-2 data in combination with a risk map, created from geodata and forestry data, to detect trees predisposed to and attacked by the European spruce bark beetle. Random forest models were trained over two tiles (90 × 90 km) in southern Sweden for all dates with a sufficient number of cloud-free Sentinel-2 pixels during the period May–September in 2017 and 2018. The pixels were classified into attacked and healthy to study how detection accuracy changed with time after bark beetle swarming and to find which Sentinel-2 bands are more important for detecting bark beetle attacked trees. Random forest models were trained with (1) single-date data, (2) temporal features (1-year difference), (3) single-date and temporal features combined, and (4) Sentinel-2 data and a risk map combined. We also included a spatial variability metric. The results show that detection accuracy was high already before the trees were attacked in May 2018, indicating that the Sentinel-2 data detect predisposed trees and that the early signs of attack are low for trees at high risk of being attacked. For single-date models, the accuracy ranged from 63 to 79% and 84 to 94% for the two tiles. For temporal features, accuracy ranged from 65 to 81% and 81 to 92%. When the single-date and temporal features were combined, the accuracy ranged from 70 to 84% and 90 to 96% for the two tiles, and with the risk map included, the accuracy ranged from 83 to 91% and 92 to 97%, showing that remote sensing data and geodata can be combined to increase detection accuracy. The differences in accuracy between the two tiles indicate that local differences can influence accuracy, suggesting that geographically weighted methods should be applied. For the single-date models, the SWIR, red-edge, and blue bands were generally more important, and the SWIR bands were more important after the attack, suggesting that they are most suitable for detecting the early signs of a bark beetle attack. For the temporal features, the SWIR and blue bands were more important, and for the variability metric, the green band was generally more important.
Journal Article
Bushmeat hunting changes regeneration of African rainforests
To assess ecological consequences of bushmeat hunting in African lowland rainforests, we compared paired sites, with high and low hunting pressure, in three areas of southeastern Nigeria. In hunted sites, populations of important seed dispersers—both small and large primates (including the Cross River gorilla, Gorilla gorilla diehli)—were drastically reduced. Large rodents were more abundant in hunted sites, even though they are hunted. Hunted and protected sites had similar mature tree communities dominated by primate-dispersed species. In protected sites, seedling communities were similar in composition to the mature trees, but in hunted sites species with other dispersal modes dominated among seedlings. Seedlings emerging 1 year after clearing of all vegetation in experimental plots showed a similar pattern to the standing seedlings. This study thus verifies the transforming effects of bushmeat hunting on plant communities of tropical forests and is one of the first studies to do so for the African continent.
Journal Article
The origins of cultural divergence: evidence from Vietnam
Cultural norms diverge substantially across societies, often within the same country. We propose and investigate a self-domestication/selective migration hypothesis, proposing that cultural differences along the individualism–collectivism dimension are driven by the out-migration of individualistic people from collectivist core regions of states to peripheral frontier areas, and that such patterns of historical migration are reflected even in the current distribution of cultural norms. Gaining independence in 939 CE after about a thousand years of Chinese colonization, historical Vietnam emerged in the region that is now north Vietnam with a collectivist social organization. From the eleventh to the eighteenth centuries, historical Vietnam gradually expanded its territory southward to the Mekong River Delta through repeated waves of conquest and migration. Using a nationwide household survey, a population census, and a lab-in-the-field experiment, we demonstrate that areas annexed earlier to historical Vietnam are currently more prone to collectivist norms, and that these cultural norms are embodied in individual beliefs. Relying on many historical accounts, together with various robustness checks, we argue that the southward out-migration of individualistic people during the eight centuries of the territorial expansion is an important driver, among many others, of these cultural differences.
Journal Article
Climate change and market collapse: A model applied to Darfur
A recurring argument in the global debate is that climate deterioration is likely to make social conflicts over diminishing natural resources more common in the future. The exact mechanism behind such a development has so far not been successfully characterized in the literature. In this paper, we present a general model of a community populated by farmers and herders who can either divide up land in a market economy or in autarky. The key insight from our model is that decreasing resources can make trade between the two groups collapse, which in turn makes each group's welfare independent of that of the other. Predictions from the model are then applied to the conflict in Darfur. Our analysis suggests that three decades of drought in the area can at least partially explain the observed disintegration of markets and the subsequent rise of social tensions.
Journal Article