Prioritizing requirements is one of the most important and influential steps in the creation of a software product. The process is iterative; it takes place during the entire agile software development. Through prioritizing requirements, it is decided which requirements are to be developed, in which order, and why. 

The aim of this study is to investigate how companies that design software prioritize requirements and to identify which prioritization methods they might use during this process. The purpose of this study is to gain an understanding for why a well-balanced prioritization is important, which specific prioritization factors give value to a product, as well as identifying how these factors are related to the result. The purpose is also to investigate the difficulties that exist in a prioritization process, and to create an overview of some of the most used prioritization methods in agile software development. 

This study is conducted in collaboration with the software company Monitor ERP in order to analyze the company's prioritization processes used to develop their business management system Monitor. The method used is a qualitative study that consists of observations of meetings about prioritization processes, and semi-structured interviews. Processing of collected material was done by organizing, analyzing, and compiling results according to concepts and categories that emerged from the literature study. The results documents work processes, common goals, prioritization aspects and challenges in the requirements prioritization at Monitor ERP. 

A well-balanced prioritization proved to be important to be able to deliver the right functionality on time and to be able to provide dependable estimates of development, which in turn leads to customers gaining confidence in both the product and the company. A number of prioritization factors that give value to the Monitor software were identified, many of which contribute to increasing customer satisfaction and product quality. Monitor ERP does not use any specific prioritization methods, but the development philosophy Minimum Viable Product is used as a basis for their prioritization choices. During the prioritization process, challenges such as limited resources, unpredictable tasks, difficulties with time estimation, and a challenge in balancing customer value and customer focus were experienced.

Millions of new websites are created daily, making it challenging to determine which ones are safe. Cybersecurity involves protecting companies and users from cyberattacks. Cybercriminals exploit various methods, including phishing attacks, to trick users into revealing sensitive information. In Australia alone, there were over 74,000 reported phishing attacks in 2022, resulting in a financial loss of over $24 million. Artificial intelligence (AI) and machine learning are effective tools in various domains, such as cancer detection, financial fraud detection, and chatbot development. Machine learning models, such as Random Forest and Support Vector Machines, are commonly used for classification tasks. With the rise of cybercrime, it is crucial to use machine learning to identify both known and new malicious URLs. The purpose of the study is to compare different instance selection methods and machine learning models for classifying malicious URLs.

In this study, a dataset containing approximately 650,000 URLs from Kaggle was used. The dataset consisted of four categories: phishing, defacement, malware, and benign URLs. Three datasets, each consisting of around 170,000 URLs, were generated using instance selection methods (DRLSH, BPLSH, and random selection) implemented in MATLAB. Machine learning models, including SVM, DT, KNNs, and RF, were employed. The study applied these instance selection methods to a dataset of malicious URLs, trained the machine learning models on the resulting datasets, and evaluated their performance using 16 features and one output feature.

In the process of hyperparameter tuning, the training dataset was used to train four models with different hyperparameter settings. Bayesian optimization was employed to find the best hyperparameters for each model. The classification process was then conducted, and the results were compared. The study found that the random instance selection method outperformed the other two methods, BPLSH and DRLSH, in terms of both accuracy and elapsed time for data selection. The lower accuracies achieved by the DRLSH and BPLSH methods may be attributed to the imbalanced dataset, which led to poor sample selection.

Amid the rapid proliferation of thousands of new websites daily, distinguishing safe ones from potentially harmful ones has become an increasingly complex task. These websites often collect user data, and, without adequate cybersecurity measures such as the efficient detection and classification of malicious URLs, users’ sensitive information could be compromised. This study aims to develop models based on machine learning algorithms for the efficient identification and classification of malicious URLs, contributing to enhanced cybersecurity. Within this context, this study leverages support vector machines (SVMs), random forests (RFs), decision trees (DTs), and k-nearest neighbors (KNNs) in combination with Bayesian optimization to accurately classify URLs. To improve computational efficiency, instance selection methods are employed, including data reduction based on locality-sensitive hashing (DRLSH), border point extraction based on locality-sensitive hashing (BPLSH), and random selection. The results show the effectiveness of RFs in delivering high precision, recall, and F1 scores, with SVMs also providing competitive performance at the expense of increased training time. The results also emphasize the substantial impact of the instance selection method on the performance of these models, indicating its significance in the machine learning pipeline for malicious URL classification

UAV (Unmanned Aircraft Vehicle) has revolutionized the creation of orthophotos with its contribution to increased safety, lower costs and more effective ways when making orthophotos. The traditional aerial photogrammetry with airplanes and placement of flight signals has been the standard method for years. To fly with UAV instead of an airplane is cheaper and saves time, however, the placement and measurements of flight signals is still time consuming and therefore expensive. The company DJI has developed a new UAV called Phantom 4 RTK that supports satellite based technology for direct georeferercing.

This study compared two different measuring methods when producing orthophotos with UAV: direct georeferencing with NRTK (Network Real Time Kinematic) and indirect georeferencing when using different number of Ground Control Points (GCP). The study was conducted at the University of Gävle over an area of eight hectares. An investigation of the deviation in plane and height resulted in acceptable units based on the guidelines that were followed in HMK – Ortofoto and the controls that were followed from SIS- TS 21144:2016.

The RMS value in plane for the indirect georeferencing method is 0,0102 m. For the direct georeferencing method the RMS value in plane when using ground control points is between 0,0132 and 0,0148 m. At last the RMS value for the direct georeferencing method without ground control points is 0,0136m. The RMS value in height is between the intervals 0,008-0,025 m.

The data presented in this study show that an accepted quality in the orthophotos can be acquired based on the RMS values in plane and height for every georeferencing that was tested. After accomplished controls and evaluation the results show that the different georeferencing methods doesn´t differantiate too much from each other based on their quality. However, the direct georeferencing method with ground control points is more effective from a time perspective.

Phantom 4 RTK is new on the market and more research is necessary in order to understand the potential of this technology and its posibility to integrate into society. More research is recquired for the direct georeferencing method in order to evaluate the quality of orthophotos.

In our everyday life, we as users encounter many different interfaces, therefore it is of great importance that they work well and have clear instructions for how to use them, i.e., that they have a good usability. Through the increased digitization, people today can work or study remotely, which is something that has been of great help recently during the covid pandemic. Since remote work and education has become common, it is important that we can also do our usability tests remotely.

The purpose of this work is to investigate the usability of the time reporting system Tidig and to compare different test tools to see which tool is best suited for future usability tests on Tidig. The tests will be of the type URUT (Unmoderated Remote Usability Testing), which means that usability tests are unmoderated and done remotely for easier data collection. With the given data the result is expected to give a better picture of the usability of time reporting systems for future improvement work as well as which tool should be used in future usability tests.

The results of the usability tests have shown that the time reporting system Tidig has a high usability. During the usability tests, the participants did not have a major difficulty in solving most of the tasks. The questions that were asked showed that the participants were satisfied with the system but would like small improvements to be made on certain parts of the time reporting system. The comparison of the tools shows that the tool best suited for future usability tests on Tidig is the Loop11 test tool. Loop11 offers a variety of functions to collect quantitative and qualitative data, the test tool also provides statistics on tasks, questions and the questionnaires.

Public transport plays an important role in sustainable urban development. Increased use of public transport and walking contributes to improving the climate by reducing greenhouse gas emissions. To increase the number of people choosing to walk to public transport, the accessibility and quality of bus stops need to be improved. Factors such as safety, security, attractiveness and accessibility can be used to encourage more people to walk to public transport. More transport options help individuals from different income groups and communities to have greater access to more destinations. Not all income groups have the same need for public transportation. For example, high-income earners are not as dependent on public transport as low-income earners.    The aim for the study is to increase knowledge on whether there is a relationship between neighborhood income levels, accessibility and quality of bus stops. The methods used to conduct the study included a network analysis that includes population, building as well as income estimation. Furthermore, a field observation was conducted in the study areas Husby and Trångsund, along with a survey and a Chi2-test. The study found a significant difference between the quality and accessibility of bus stops based on neighborhood income level. The income level of a neighborhood influences the quality of its bus stops, as confirmed in Husby by a Chi2-test, which demonstrated a statistical correlation. The quality of the bus stops was assessed using a checklist based on scientific literature and general guidelines. Bus stops in Trångsund can be considered of higher quality, as they meet more of the criteria on the checklist compared to Husby. Income levels in the neighborhoods also affect the accessibility of bus stops. In Husby, the annual median income for all income groups is lower than the Swedish average, which mean that residents are more dependent on public transportation. In contrast, the annual median income for high earners in Trångsund is higher than the Swedish average. High income earners are more likely to use private cars which may reduce reliance on public transport. Therefore, accessibility to bus stops may be better in Husby than in Trångsund, based on the results of the population, building and income estimation. 

In the case of infrastructure projects, the authority should inform the nearby residents about what is happening in their area. Research shows that anchoring and trust are created when dialogues are applied in the planning process. These democratic processes are important to satisfy the interests of the public. The social aspect of a sustainable development is strengthened by allowing the public to participate in society's development, which in turn leads to greater equality. Changes create different reactions and communication has a significant role in the link between the public and authority, since information flows can contribute to less irritations and misunderstandings. An authority like the Swedish Traffic Authority not only has to deal with the public when establishing infrastructure projects, but also systems for planning processes, legislation, and financial frameworks. The purpose of this study is to investigate how the Traffic authority goes about giving out information to nearby residents in the planning process of new infrastructure and how the distribution of information affects the nearby residents' acceptance of the infrastructure project.

A case study is carried out over two “2minus1” rural roads in Sundsvall and Timrå municipalities. For methods, questionnaires and interviews are used in studies, with the aim of collecting qualitative and quantitative data. Two methods are used to be able to verify results, as well as to get an overall picture of how the process works when establishing a “2minus1” road. Web-based questionnaires were sent to nearby residents at the two “2minus1” road, several interviews of nearby residents were conducted during site visits, and interviews were conducted with employees at the Swedish Traffic Authority who have expertise in establishing “2minus1” roads.

The results of the interviews with the Swedish Traffic authority showed that there is no elaborate process for how they should distribute information to nearby residents when establishing a “2minus1” roads. This is because the “2minus1” roads are a new type of road and only a few of them have been established in Sweden. The results of the study indicate that information has a great importance for the acceptance of nearby residents. Acceptance is affected by when the information is distributed and whether the content of the information is adapted to the target group. By providing information on how the “2minus1” roads should be used and providing an understanding of the benefits of a “2minus1” roads, it contributes to greater acceptance by residents. Acceptance is a complex subject that can depend on many different factors. Acceptance is not only impact by information, but it can also depend on personal preferences.

Multidecadal sea level variation in the Baltic Sea is investigated from 1900 to 2020 deploying satellite and in situ datasets. As a part of this investigation, nearly 30 years of satellite altimetry data are used to compare with tide gauge data in terms of linear trend. This, in turn, leads to validation of the regional uplift model developed for the Fennoscandia. The role of North Atlantic Oscillation (NAO) in multidecadal variations of the Baltic Sea is also analyzed. Although NAO impacts the Baltic Sea level on seasonal to decadal time scales according to previous studies, it is not a pronounced factor in the multidecadal variations. The acceleration in the sea level rise of the basin is reported as statistically insignificant in recent studies or even decelerating in an investigation of the early 1990s. It is shown that the reason for these results relates to the global warming hiatus in the 1950s−1970s, which can be seen in all eight tide gauges used for this study. To account for the slowdown period, the acceleration in the basin is investigated by fitting linear trends to time spans of six to seven decades, which include the hiatus. These results imply that the sea level rise is accelerated in the Baltic Sea during the period 1900–2020.

The detection of cracks in sand moulds has long been a challenge for both safety and maintenance purposes. Traditional image processing techniques have been employed to identify and quantify these defects but have often proven to be inefficient, labour-intensive, and time-consuming. To address this issue, we sought to develop a more effective approach using deep learning techniques, specifically semantic segmentation. We initially examined three different architectures—U-Net, SegNet, and DeepCrack—to evaluate their performance in crack detection. Through testing and comparison, U-Net emerged as the most suitable choice for our project. To further enhance the model's accuracy, we combined U-Net with VGG-19, VGG-16, and ResNet architectures. However, these combinations did not yield the expected improvements in performance. Consequently, we introduced a new layer to the U-Net architecture, which significantly increased its accuracy and F1 score, making it more efficient for crack detection. Throughout the project, we conducted extensive comparisons between models to better understand the effects of various techniques such as batch normalization and dropout. To evaluate and compare the performance of the different models, we employed the loss function, accuracy, Adam optimizer, and F1 score as evaluation metrics. Some tables and figures explain the differences between models by using image comparison and evaluation metrics comparison; to show which model is better than the other. The conducted evaluations revealed that the U-Net architecture, when enhanced with an extra layer, proved superior to other models, demonstrating the highest scores and accuracy. This architecture has shown itself to be the most effective model for crack detection, thereby laying the foundation for a more cost-efficient and trustworthy approach to detecting and monitoring structural deficiencies.

The concept of importance of criteria is used as a central element in several decision making contexts, specifically in value aggregation, e.g. as an input to decision support tools. For example, in the analytic hierarchy process (AHP) decision makers are asked to estimate how much more important one criterion is than another. However, it is not clear how people understand aggregation models based on importance of criteria in decision making situations. The purpose of this descriptive study is to investigate if people find an aggregation model in simple value aggregation tasks which remind of the way AHP elicits the input. Further, the purpose is to investigate if people's tendency to find a model depends on their cognitive abilities. In an exploratory laboratory experiment, participants assessed which of two alternatives is the best, based on information about the importance of two criteria and how good the two alternatives are compared to each other with respect to these criteria. The results confirm that people are willing to use importance of criteria and goodness of alternatives as input in value aggregations and show three main models for aggregation. More participants with higher numeracy applied a clear model compared to those with lower numeracy. None of the identified models was one of AHP's models but one of them reminded of one of the ways input can be aggregated in the AHP. The three models identified in the experiment are based on lexicographic order, multiplication and a combination of multiplication and addition. How the results could be used in a prescriptive context is discussed in the paper.

Assessment of an application for wind power establishment is a multi-criteria problem including the coreproblem: whether to grant permission or not. In Sweden, County Administrative Boards decide the outcomes of these kinds of applications. Five permit officers were interviewed to investigate the difficultiesand the type of value aggregation in this work, and to test reasoning models as possible decision supporttools. The commonly used type of aggregation was condition-based aggregation. Aggregation based onvalue differences, which means weighing together aspects for and against the wind power establishment,was considered difficult to apply by the respondents. Most of them agreed that some of the aspects thatspeak against granting permission could be aggregated but that aggregation of all aspects would be harddue to differences between aspects. In addition, the value of the main aspect that speaks for permission,climate friendly energy supply, is very difficult to estimate. Thus, aggregation based on value differencesis a difficult question and how it could be performed is discussed in the paper. If policymakers wish tomake it possible to take both positive and negative aspects into consideration and to discuss thetrade-offs transparently, the investigated method can be a way forward.

Engaging in the social game of UNO represents a form of social interaction aimed atpromoting enjoyment. Each UNO card deck consists of five different colors (blue,red, green, yellow and joker) and various symbols. However participating in such agame can be frustrating for individuals with color vision impairment. Since a substantial portion of the game relies on accurately identifying the color of each card.The overall purpose of this research is to develop a prototype for object recognitionof UNO cards to support individuals with color vision impairment. This thesis involves comparing object recognition methods, namely Convolutional Neural Network (CNN) and Template Matching (TM). Each method will be compared with respect to color and symbol recognition both separately and combined.  

The development of such a prototype will be through creating and training two different CNN models, where the first model focuses on solely symbol recognitionwhile the other model incorporates both color and symbol recognition. These models will be trained though an algorithm called YOLOv5 which is considered state-ofthe-art (SOTA) with fast execution. At the same time, two models of TM inspiredmethods, hue template test and binary template test, will be developed with thehelp of OpenCV and by creating templates for the cards. Each template will be usedas a way to compare the detected card in order to classify it. Additionally, the KNearest Neighbor (KNN) algorithm, a machine learning algorithm, will be developed specifically to identify the color of the cards. Finally a comparative analysis ofthese methods will be conducted by evaluating performance metrics such as accuracy, precision, recall and latency. The comparison will be carried out in betweeneach method using a confusion matrix for color and symbol in respective models.

The study’s findings revealed that the model combining CNN and KNN demonstrated the best performance during the validation of the different models. Furthermore, the study shows that template tests are faster to implement than CNN due tothe training that a neural network requires. Moreover, the execution time showsthat there is a difference between the different models, where CNN achieved thehighest performance.

The International Association of Geodesy defined the International Height Reference System (IHRS) in 2015. IHRS will be realised through the International Reference Frame (IHRF) primarily by geopotential numbers (or physical heights). On the global scale, a sparse core reference network will be the basis for the realisation. To ensure local access to the frame and the best possible conditions for height datum unification, denser realisations (or densifications) will be needed. The adopted realisations can be either regional, national, or local. According to the published recommendations on regional IHRS realisation, GNSS ellipsoidal heights and a gravimetric (quasi-) geoid model form the basis to compute a pointwise IHRS realisation, but it is possible to supplement this by local levelling to gain local access to the frame and improve the relative uncertainty. The main purpose of this article is to investigate different ways to incorporate levelling observations in the IHRS realisation process and explore potential improvements. The investigation is a case study over Sweden that uses an initial pointwise IHRS realisation and precise levelling observations from the Baltic Levelling Ring (BLR) project. The levelling network is adjusted with respect to the pointwise IHRF geopotential numbers using three different approaches regarding the a priori variance-covariance matrix used for weighting of the observations. The approaches are constrained adjustment, weighted adjustment with realistic a priori uncertainties (variance covariance matrix) and weighted adjustment with Variance Component Estimation (VCE) to iteratively tune the a priori variance-covariance matrix. It is shown that the pointwise IHRS realisation can be improved significantly by the inclusion of levelling observations. Both the estimated standard uncertainty of the adjusted IHRF geopotential numbers as well as the relative standard uncertainty between nodal benchmarks are reduced by approximately 40 percent in the Swedish case. To fully exploit the potential of precise levelling observations in the IHRS realisation process, it is recommended to use some form of weighted adjustment, preferably using VCE to obtain a realistic balance between the initial pointwise and levelling observations.

A common global vertical reference frame for physical heights is essential in many applications, but an equivalent to the three-dimensional International Terrestrial Reference System has until recently been lacking for physical heights. The International Height Reference System, IHRS, was defined in 2015. It will be realised by the International Height Reference Frame, IHRF, on the global level by a sparse core reference network. To ensure local access and enable optimum height datum unification, adopted regional or national realisations (or densifications) are required. This thesis explores regional and national realisations of IHRS, employing both the standard pointwise methodology as well as levelling assisted approaches. Levelling observations have the potential to improve pointwise IHRS realisations. The thesis studies a regional levelling network that is adjusted with respect to an initial pointwise IHRS realisation using different approaches. The evaluation of these solutions is based on the resulting geopotential numbers and their estimated standard uncertainties. It is shown that including levelling observations in the IHRS realisation process might lead to significant improvements. It is recommended to employ a weighted adjustment of pointwise geopotential numbers and levelling observations, and to utilise variance component estimation as a tool to estimate a priori uncertainties. With a comparison to the Swedish levelling based realisation of the European Vertical Reference System, RH 2000, differences in the definitions of reference systems are explored. Corrections related to known effects, such as permanent tide concepts, postglacial land uplift epoch and zero level, are here considered. It is shown that the differences in the obtained geopotential numbers can be explained to rather large extent by these corrections. Finally, the thesis discusses how national and regional realisations of IHRS should be interpreted with respect to the global realisation.

The International Height Reference System (IHRS) was defined by the International Association of Geodesy in 2015. Since then, the international geodetic community has been working on the specification and establishment of its realisation, the International Height Reference Frame (IHRF). This frame will primarily be realised by geopotential numbers (or physical heights) in a sparse global reference network. In Sweden, only one such global station is planned. Regional and national realisations (or densifications) computed in accordance with the IHRS definition are needed to enable the best possible unification of height datums. The main purpose of this article is to make a case study for Sweden regarding the national realisation of IHRS and to investigate in what way preliminary IHRF differs from the current Swedish levelling-based realisation of the European Vertical Reference System, RH 2000. The two different quasigeoid models that we consider best over Sweden at the present time are used to compute the preliminary IHRS realisations in the study. The realisations are compared to each other and to RH 2000. It is shown that a very significant part of the difference to RH 2000 is due to the different postglacial land uplift epochs, permanent tide concepts, and zero levels. The standard deviation for the difference between one of the preliminary national IHRS realisations and RH 2000 is reduced from 75.5 to 19.2 mm after correction of the postglacial land uplift and permanent tide effects. The corresponding mean differences are –208.5 and –454.7 mm, respectively. The magnitude of the mean difference thus increases when the corrections in question are applied.

The International Height Reference System (IHRS) was defined by the International Association of Geodesy (IAG) in 2015. The global International Height Reference Frame (IHRF) should provide access to the IHRS in a broad sense. To provide high accuracy local access, regional (or national) realisations will also be needed. This study aims at evaluating different approaches to compute a denser regional realisation of IHRS in case a high accuracy levelling network is available. Using Sweden as a case study region, a GNSS (Global Navigation Satellite System) and geoid based pointwise realisation is compared with three types of levelling assisted realisations. The latter are made by applying least squares adjustments of the precise levelling observations with fixed potential value(s) from either the global IHRF station in Sweden or the pointwise potentials of a larger number of stations. It is concluded that making a minimum constraint adjustment with one station fixed is not the best option. It is favourable to fix a reasonable number of pointwise stations at an internal distance over which the relative uncertainty of levelling is significantly lower than the relative uncertainty of the pointwise solution. The investigation is made using levelling data from the third precise levelling of Sweden, the NKG2015 quasigeoid model and the NKG2016LU postglacial land uplift model.

This thesis examines data collection and visualization for the TEIS (Tietoevry Integration Server) integration engine at Gävle Municipality. The aim is to analyze and visualize the integrations performed by TEIS to enhance the understanding of its processes and data flows. 

The work began with collecting data from the TEIS API using Postman. By employing various API calls, relevant information about workspaces, folders, integrations, processes, and triggers was extracted. Subsequently, a web application was developed using React to visualize this data. The application allows hierarchical navigation through the workspaces and presents detailed information about the various components in TEIS. 

To streamline data management and improve the application's performance, a database was integrated to store information about triggers, integrations, and processes. This reduced the time to match triggers with their respective integrations from several minutes to just a few seconds. 

A survey was conducted to evaluate the web application among system developers at Gävle Municipality. The results showed that the application met the users' needs and expectations, but some suggestions for improvements were highlighted, such as adding filter functions and clickable charts. 

In conclusion, the method and solution for collecting and visualizing data from TEIS were found to be effective. The web application provides a comprehensive and clear view of TEIS integrations, improving Gävle Municipality's ability to monitor and understand the system's performance and potential problem areas. 

A recently introduced GNSS instrument on the market is Leica GS18 T with tilt compensation, based on GNSS/Inertial Navigation Systems (INS) integration, with no need to centre the survey pole with the GNSS instrument over the target point being measured. Besides making surveying faster, the tilt compensation technique enables measuring of hidden points where the use of conventional GNSS measuring normally is not possible without more time-consuming methods. The instrument also has advanced GNSS signal tracking which makes surveying in challenging environments possible.

In this study, the Leica GS18 T has on behalf of Lantmäteriet been tested through studying the measurement uncertainty in network RTK measurement with tilted survey pole in three different situations: with the survey pole tilted in various degrees in both favourable and challenging survey environments; with tilt towards north, east, south and west to test if the tilt direction would affect the result; and for surveying of building corners as a possible field of application. In the latter case, the result was compared with what can be achieved with the conventional hidden point method using intersection of distances. The analysis of the measurement uncertainty was based on calculations of standard uncertainty, RMS (Root Mean Square) and mean deviation.

The measurement uncertainty from the first part of the test was on cm-level horizontally, both in favourable and challenging survey environments, and in height on mm-level in favourable survey environment and on cm-level in challenging survey environment. Further, the results indicate that the tilt direction affects measurement uncertainty. The reason for this is not clarified and needs further investigation. The measurements of building corners resulted in a mean deviation of approximately 12 mm when the survey pole was tilted 30°. The hidden point method using intersection of distances generally resulted in lower mean deviation, even though the difference is relatively small (4 mm at best). To summarize, Leica GS18 T seems to be well suited for measuring with tilt in detailed surveying, at least if the requirements of position uncertainty is on cm-level.

Condominiums are a specific variant of three-dimensional property formation, which are intended to house a residential apartment. The requirement that condominiums must be formed at least three in a cohesive unit, means that facilities such as building frames and facades will be common to several condominiums. These facilities are managed by the owners of the condominiums through a community association. Breviksängar in municipality of Öckerö, was one of the first areas with condominiums in Sweden, and in addition, it consists of privately owned and real estate company-owned condominiums, which are leased as rental apartments. Thanks to a study conducted by Berntsson and Halldin (2012), it has been possible to conduct a study on the management over time. A literature study has been part of the study to obtain background information on the formation of condominiums with the necessary rights and how the equivalent of condominiums works abroad regarding management.The purpose of the study was to examine how the management was perceived twelve years after the previous survey and to map any differences and to find out if the change in the role of the real estate company had had an impact on how the company is perceived. In addition, the residents' knowledge of the boundaries between individual condominiums and shared facilities was investigated. The study showed that a larger proportion are positive towards the community association today than in 2012. The proportion of people who expressed themselves negatively about the company has decreased. The results showed that when the area was new, there was a certain optimism about the combination of rental apartments and ownership rights in the same area, also in other places in Sweden. A clear change can be discerned in this study when the uncertainty among the respondents is now significantly greater.

The purpose of this paper is to examine the pros and cons of compulsory acquisition of rooftop space for mass upscaling of solar panels. It attempts to find what uses a legal tool for compulsory acquisition could bring to society, as well as what the cost of such a tool would mean for each landowner. By looking at existing law it is also the hope of the writer to establish whether there is already a functioning way to accomplish this kind of mass development of rooftop-mounted solar panels. While it is not included in the paper to describe what a potential new piece of law would look like, it concludes that if Sweden was to implement a way to accomplish a mass development of this kind, it should be done by creating a separate act to limit how and by whom the compulsory acquisition can be performed. 

Our complex planet is continuously undergoing temporal and spatial changes. In this context, ongoing processes in the Earth subsystems (geosphere, biosphere, cryosphere, hydrosphere, and atmosphere) cause changes in the gravity field of the Earth across a wide range of temporal and spatial scales. Accordingly, by both spatially and temporally tracing our planet’s ever-changing gravity field, scientists can better constrain the underlying processes contributing to such dynamic changes of mass distribution within the Earth system. Monitoring the Earth’s gravity field and its temporal variations is essential, among others, for tracking disasters and specifying land areas with a high risk of flooding, earthquakes, and droughts, movements of tectonic plates, and providing accurate positioning through satellite positioning technology. On short-term timescales, temporal variations in the Earth’s gravity field are mainly caused by the movement of water in its various forms. Accordingly, sea-level variations and ice-sheet and glacier changes, which are known as critical indicators of global warming and climate change, can be accurately monitored by tracking the Earth’s gravity field changes. Since there is a close link between water redistribution and the Earth’s energy cycle, climate system, food security, human and ecosystem health, energy generation, economic and societal development, and climate extremes (droughts and floods), it is essential to accurately monitor water mass exchange between the Earth system components. Among all observational techniques, satellite gravimetry has provided an integrated global view of ongoing processes within the Earth system. The current generation of satellite gravimetry missions (the Gravity Recovery and Climate Experiment (GRACE) mission and its successor, GRACE Follow-On) has dramatically revolutionized our understanding of dynamic processes in the Earth’s surface and, consequently, has significantly improved our understanding of the Earth’s climate system. By considering different aspects of studying the Earth’s gravity field, this thesis brings new insights to the determination and analysis of the mass change in the Earth system. First, by studying the shortcomings of the common techniques of estimating the geoid potential, a new approach is examined that simultaneously estimates the geoid potential, W0, and the geometrical parameters of the reference Mean Earth Ellipsoid (MEE). In this regard, as the geoid needs to be considered as a static equipotential surface, the sensitivity of the estimations to the time dependent Earth’s gravity field changes is studied. Secondly, relying on the GRACE monthly gravity fields and the complementary observational techniques, and by pushing the limit of GRACE, mass redistribution over land and ocean is investigated. Within the ocean, satellite altimetry and Argo products are utilized along with the GRACE monthly solutions for quantifying the global barystatic sea-level change and assessing the closure of the global mean sea level budget. Over land, a region with relatively high temporal mass change (oil and water extraction) is chosen in which by taking advantage of having in-situ observations and hydrological models, the ability of GRACE products in quantifying the changes in groundwater storage is studied. In this frame, for both the ocean and land studies, different aspects of the processing of GRACE monthly gravity fields are investigated and GRACE inherent errors are addressed appropriately to arrive at reliable and accurate estimates of the Earth’s surface mass change. As the final contribution in this thesis, a rigorous analytical model for detecting surface mass change from the time-variable gravity solutions is proposed and examined in different case studies of surface mass change. Since the launch of the GRACE twin satellites, the GRACE(-FO) time-varying gravity fields are conventionally converted into the surface mass change using a spherical analytical model that approximates the Earth by a sphere. More recently, the analytical mass change detection model has been improved by considering an ellipsoid as the shape of the Earth, which improved the previous estimations of surface mass change, especially over high latitudes with relatively large mass change signals. However, by taking into account the real shape of the Earth and considering more realistic assumptions, a new analytical solution for the problem of surface mass change detection from the time-varying gravity fields is proposed in this thesis. It is shown that the simplistic spherical and ellipsoidal geometries are no longer tenable and the new model surpasses the common spherical approach and its ellipsoidal version.

Sea level changes over time because of water mass exchange among the oceans and continents, ice sheets, and atmosphere. It fluctuates also due to variations of seawater salinity and temperature known as the steric contributor. GRACE-based Stokes coefficients provide a valuable source of information, about the water mass exchange as the main contributor to the Earth’s gravity field changes, within decadal scales. Moreover, measuring seawater temperature and salinity at different layers of ocean depth, Argo floats help to model the steric component of Global Mean Sea Level. In this study, we evaluate the Global Mean Sea Level (GMSL) budget closure using satellite altimetry, GRACE, and Argo products. Hereof, considering the most recent released GRACE monthly products (RL06), we examine an iterative remove-restore method to minimize the effect of artifact leaked large signal from ice sheets and land hydrology. In addition, the effect of errors and biases in geophysical model corrections, such as GIA, on the GMSL budget closure is estimated. Moreover, we quantify the influence of spatial and decorrelation filtering of GRACE data on the GMSL budget closure. In terms of the monthly fluctuations of sea level, our results confirm that closing the GMSL budget is highly dependent on the choice of the spatial averaging filter. In addition, comparing the trends and variations for both the global mean sea level time series and those estimated for mass and steric components, we find that spatial averaging functions play a significant role in the sea level budget closure.

Time-varying spherical harmonic coefficients determined from the Gravity Recovery and Climate Experiment (GRACE) data provide a valuable source of information about the water mass exchange that is the main contributor to the Earth’s gravity field changes within a period of less than several hundred years. Moreover, by measuring seawater temperature and salinity at different layers of ocean depth, Argo floats help to measure the steric component of global mean sea level (GMSL). In this study, we quantify the rate of barystatic sea-level change using both GRACE RL05 and RL06 monthly gravity field models and compare the results with estimates achieved from a GMSL budget closure approach. Our satellite altimetry-based results show a trend of 3.90 ± 0.14 mm yr−1 for the GMSL rise. About 35% or 1.29 ± 0.07 mm yr−1 of this rate is caused by the thermosteric contribution, while the remainder is mainly due to the barystatic contribution. Our results confirm that the choice of decorrelation filters does not play a significant role in quantifying the global barystatic sea-level change, and spatial filtering may not be needed. GRACE RL05 and RL06 solutions result in the barystatic sea-level change trends of 2.19 ± 0.13 mm yr−1 and 2.25 ± 0.16 mm yr−1, respectively. Accordingly, the residual trend, defined as the difference between the altimetry-derived GMSL and sum of the steric and barystatic components, amounts to 0.51 ± 0.51 and 0.45 ± 0.44 mm yr−1 for RL05 and RL06-based barystatic sea-level changes, respectively, over January 2005 to December 2016. The exclusion of the halosteric component results in a lower residual trend of about 0.36 ± 0.46 mm yr−1 over the same period, which suggests a sea-level budget closed within the uncertainty. This could be a confirmation on a high level of salinity bias particularly after about 2015. Moreover, considering the assumption that the GRACE-based barystatic component includes all mass change signals, the rather large residual trend could be attributed to an additional contribution from the deep ocean, where salinity and temperature cannot be monitored by the current observing systems. The errors from various sources, including the model-based Glacial Isostatic Adjustment signal, independent estimation of geocenter motion that are not quantified in the GRACE solutions, as well as the uncertainty of the second degree of zonal spherical harmonic coefficients, are other possible contributors to the residual trend.

The geoid, according to the classical Gauss–Listing definition, is, among infinite equipotential surfaces of the Earth’s gravity field, the equipotential surface that in a least squares sense best fits the undisturbed mean sea level. This equipotential surface, except for its zero-degree harmonic, can be characterized using the Earth’s global gravity models (GGM). Although, nowadays, satellite altimetry technique provides the absolute geoid height over oceans that can be used to calibrate the unknown zero-degree harmonic of the gravimetric geoid models, this technique cannot be utilized to estimate the geometric parameters of the mean Earth ellipsoid (MEE). The main objective of this study is to perform a joint estimation of W0, which defines the zero datum of vertical coordinates, and the MEE parameters relying on a new approach and on the newest gravity field, mean sea surface and mean dynamic topography models. As our approach utilizes both satellite altimetry observations and a GGM model, we consider different aspects of the input data to evaluate the sensitivity of our estimations to the input data. Unlike previous studies, our results show that it is not sufficient to use only the satellite-component of a quasi-stationary GGM to estimate W0. In addition, our results confirm a high sensitivity of the applied approach to the altimetry-based geoid heights, i.e., mean sea surface and mean dynamic topography models. Moreover, as W0 should be considered a quasi-stationary parameter, we quantify the effect of time-dependent Earth’s gravity field changes as well as the time-dependent sea level changes on the estimation of W0. Our computations resulted in the geoid potential W0 = 62636848.102 ± 0.004 m2 s−2 and the semi-major and minor axes of the MEE, a = 6378137.678 ± 0.0003 m and b = 6356752.964 ± 0.0005 m, which are 0.678 and 0.650 m larger than those axes of GRS80 reference ellipsoid, respectively. Moreover, a new estimation for the geocentric gravitational constant was obtained as GM = (398600460.55 ± 0.03) × 106 m3 s−2.

According to the classical Gauss–Listing definition, the geoid is the equipotential surface of the Earth’s gravity field that in a least-squares sense best fits the undisturbed mean sea level. This equipotential surface, except for its zero-degree harmonic, can be characterized using the Earth’s Global Gravity Models (GGM). Although nowadays, the satellite altimetry technique provides the absolute geoid height over oceans that can be used to calibrate the unknown zero-degree harmonic of the gravimetric geoid models, this technique cannot be utilized to estimate the geometric parameters of the Mean Earth Ellipsoid (MEE). In this study, we perform joint estimation of W0, which defines the zero datum of vertical coordinates, and the MEE parameters relying on a new approach and on the newest gravity field, mean sea surface, and mean dynamic topography models. As our approach utilizes both satellite altimetry observations and a GGM model, we consider different aspects of the input data to evaluate the sensitivity of our estimations to the input data. Unlike previous studies, our results show that it is not sufficient to use only the satellite componentof a quasi-stationary GGM to estimate W0. In addition, our results confirm a high sensitivity of the applied approach to the altimetry-based geoid heights, i.e. mean sea surface and mean dynamic topography models. Moreover, as W0 should be considered a quasi-stationary parameter, we quantify the effect of time-dependent Earth’s gravity field changes as well as the time-dependent sea-level changes on the estimation of W0. Our computations resulted in the geoid potential W0 = 62636848.102 ± 0.004 m2s-2 and the semi-major and –minor axes of the MEE,a = 6378137.678 ± 0.0003 m and b = 6356752.964 ± 0.0005 m, which are 0.678 and 0.650 m larger than those axes of the GRS80 reference ellipsoid, respectively. Moreover, a new estimation for the geocentric gravitational constant was obtained as GM = (398600460.55 ± 0.03) × 106 m3s-2.

Enhetstestning mot databaser inriktade mot geografiska informationssystem kan vara ett komplicerat arbete att utföra. Det innebär både att ha tillgång till användbart data samt att använda verktyg för att utföra dessa tester på. Denna studie har undersökt hur data bestående av ytor kan genereras och hur verktyg inriktade på enhetstestning mot databaser kan användas för att uppnå en förbättrad arbetsmetodik för enhetstestning mot databaser. Arbetet har resulterat i förslag på metoder som kan användas för att generera geografiska data. En applikation har utvecklats för att generera dessa data. Dessutom har en metod för att genomföra enhetstester mot en postgreSQL databas, baserad på verktyget pgTAP, presenterats. Föreslagna metoder kan möjliggöra en förbättring av arbetsmetodiken vid enhetstestning mot databasermen det finns fortfarande många förbättringar att utforska.

The electrification of the transport sector is dependent on the establishment of new charging infrastructure for electric vehicles. In order to achieve Sweden’s environmental goals, the government has commissioned Lantmäteriet to chart the obstacles of establishing charging infrastructure within joint facilities. During the charting, Lantmäteriet has observed the fact that joint property associations that manage joint facilities for garage and parking purposes receive government grants for charging infrastructure, even though the joint facility does not include charging infrastructure. This paper aims to investigate how joint property associations manage permit issues and agreements regarding charging infrastructure, when charging infrastructure is not included in the joint facility. This paper also examines if these issues are taken into account in the grant processing by Naturvårdsverket. The aim of this paper is to generate new knowledge that can be used in Lantmäteriet’s work. The study has been carried out through interviews with joint property associations and through communication with representatives from Naturvårdsverket. The results show that it is common for joint property associations to set up charging infrastructure contrary to the purpose of the facility. Furthermore, it is stated that ignorance and the fact that the associations consciously make decisions against the purpose of the facility due to time and cost causes, are the main reasons for the establishment. The authors also state that Naturvårdsverket and Lantmäteriet have different views on when and how charging infrastructure can be considered a part of a joint property. Furthermore, it is concluded that inconsistent legislation makes it difficult for ordinary people who administer joint property associations to comply with current laws and regulations.

In the event of a traffic accident, it is often important to restore the site to its normal condition as fast as possible. Occasionally, the accident scene must be documented so that the cause of the accident can be investigated at a later stage. Traditionally, this work has been performed by taking pictures of the site and measuring different distances. Lately, terrestrial laser scanning has also become a reliable alternative. With that said, it is possible that photogrammetry and other types of laser scanning also could be utilized to achieve similar results.   

The aim of this study is to investigate how handheld laser scanning and UAS photogrammetry can be used to document a traffic accident. This is achieved by examining the positional uncertainty and visual quality of the point clouds. Moreover, the advantages and disadvantages of each method are explored, for instance in terms of time consumption and costs, in order to finally come to a conclusion of which method is best suited for documenting a traffic accident.

A traffic accident with two involved cars was staged and initially laser scanned with the handheld laser scanner Leica BLK2GO. Thereafter, pictures were collected with the unmanned aerial vehicle Leica Aibot followed by the creation of a reference point cloud with the terrestrial laser scanner Leica C10. By comparing the coordinates of control points in the reference point cloud with the coordinates of the corresponding control points in the two other point clouds, their positional uncertainty could be determined.

The results of the study show that both the point cloud produced by the handheld laser scanner and UAS photogrammetry have a positional uncertainty (standard uncertainty) of 0.019 m. Both methods are applicable for documenting a traffic accident but compared to terrestrial laser scanning, the point clouds are deficient in different ways. BLK2GO produces a relatively dark point cloud and dark objects are reproduced worse than lighter objects. In the point cloud produced by Leica Aibot, there were noticeable cavities in the bodies of the cars. Handheld laser scanning is a time-efficient method while UAS photogrammetry can be performed at a lower cost.

In conclusion, it is not possible to arrive at an unambiguous conclusion with regards to which method that is best suited for documenting a traffic accident. The choice depends on the prevailing circumstances at the accident scene.

One of the greatest challenges of today is to change our behavior to act more pro-environmentally to reduce global warming. We need to make sacrifices for the environment, e.g., use a means of transportation that take a longer time but causes less CO₂ emission. The present thesis aims to study different factors (intrinsic, extrinsic motivational, and extrinsic motivational-neutral information) that influence us when making tradeoffs between self and environment. Paper I examined how an anchor (a reference price) and an ecolabel influence price judgments. It was found that both a judgment of an objective fact (product price) and a subjective preference (willingness to pay for the product) were affected by an anchor. An eco-label resulted in higher judgments of objective facts. People with higher environmental concern were more affected by an anchor when stating their willingness to pay than their low concern counterparts. In Paper II and Paper III, an interaction between a high anchor and a normative message that put the emissions into context was found when making a tradeoff between CO₂ emissions and travel time for a flight (Paper II) or a car journey (Paper III). People with higher concern for the environment gave a longer travel time when they received a high anchor (Paper II and Paper III) or no anchor (Paper III). Paper IV investigated how a survey measuring environmental concern can be divided to different indices and how they predict answers in a tradeoff task. The result suggests that a two-factor structure divided into ecocentric and anthropocentric concern is a possible alternative and that people scoring higher on any of the environmental concern indices were willing to travel for a longer time. Taken together, the results show that normative messages, anchors, and concern for the environment are factors that can influence and interact when people make tradeoffs between self and environment in environmental judgment and decision making.

One of the today’s greatest challenges is to adjust our behavior so that we can avoid a major climate disaster. To do so, we must make sacrifices for the sake of the environment. The study reported here investigates how anchors (extrinsic motivational-free information) and normative messages (extrinsic motivational information) influence people’s tradeoffs between travel time and carbon dioxide (CO2) emissions in the context of car travel and whether any interactions with environmental concern (an intrinsic motivational factor) can be observed. In this study, people received either a CO2, health or no normative message together with either a high anchor, a low anchor, or no anchor. People that received both a high anchor and a CO2 emission normative message were willing to travel for a longer time than those that only received a high anchor. If a low anchor was presented, no differences in willingness to travel for a longer time were found between the three different conditions of normative message groups, i.e., CO2 normative message, health normative message, or no normative message. People with higher concern for the environment were found to be willing to travel for a longer time than those with lower concern for the environment. Further, this effect was strongest when a high anchor was presented. These results suggest that anchors and normative messages are among the many factors that can influence people’s tradeoffs between CO2 emission and travel time, and that various factors may have to be combined to increase their influence over pro-environmental behavior and decisions.

The way by which various sources of external information interact in their effects on judgment is rarely investigated. Here, we report two experiments that examine how two sources of external information—an anchor (a reference price) and an eco-label—influence judgments of an objective fact (product price) and a subjective preference (willingness-to-pay for the product). Participants’ price judgments were drawn in the direction of the anchor point, whereas the eco-label resulted in higher judgments of objective fact (Experiment 1) but did not influence subjective preference (Experiment 2). Interestingly, the eco-label seemed to strengthen the effect of the high anchor in judgments of objective fact. Further, participants with higher environmental concern answered a higher price on the subjective preference questions when they received a high anchor, as well as a lower price when they received a low anchor in comparison to the low environmental concern group. This study demonstrates that various external information sources can strengthen each other’s effects on consumer belief about products, while the effects are weaker for consumers’ preferences. The implications of the results for decision making are discussed.

The addition of environmentally friendly items to conventional items sometimes leads people to believe that the carbon footprint of the entire set decreases rather than increases. This negative footprint illusion is supposedly underpinned by an averaging bias: people base environmental impact estimates not on the total impact of items but on their average. Here, we found that the illusion’s magnitude increased with the addition of a greater number of “green” items when the number of conventional items remained constant (Studies 1 and 2), supporting the averaging-bias account. We challenged this account by testing what happens when the number of items in the conventional and “green” categories vary while holding the ratio between the two categories constant (Study 3). At odds with the averaging-bias account, the magnitude of the illusion increased as the category size increased, revealing a category-size bias, and raising questions about the interplay between these biases in the illusion.

The term green infrastructure captures the need to conserve biodiversity and to sustain landscapes’ different ecosystem services. Maintaining green infrastructures through protected areas, management and landscape restoration requires knowledge in geography, spatial data about biophysical, anthropogenic and immaterial values, spatial comprehensive planning, and thus geographical information systems (GIS). To understand land use planning practices and planning education regarding GIS in Sweden we interviewed 43 planners and reviewed 20 planning education programmes. All planners used GIS to look at data but did not carry out spatial analyses of land covers. BSc programmes included more GIS than MSc programmes but very few taught analyses for spatial planning. As key spatial planning actors, municipalities’ barriers and bridges for improved GIS use for collaborative learning about green infrastructures are discussed. A concluding section presents examples of how GIS can support spatial planning for green infrastructures.

The purpose of this study is to find out if vicinity to alpine ski resorts affect the transfer prices of properties. The study should also describe and analyse whether the taxation level of singel-family house properties close to a ski resort should be managed through value area divisions. The study is written on behalf of Lantmäteriet.

In Sweden, the land is divided into various large properties. Each property is unique, which means that they have different values. The most important factor for the property’s tax assessment value is its geographical location. If the property is far from the community with poor communications to a nearby city, it probably has a low property value. If the property on the other hand has good communications, close to shops, schools and access to municipal water and sewage, it probably has a higher property value. In order to investigate this, two local price surveys on two alpine ski resorts has been done, Björnrike and Lofsdalen in the municipality of Härjedalen. Data on sales has been collected for each area, which has been analysed and processed into the result of this study. Interviews have also been done in the study.

The study shows that there is a connection between family-house properties that have ski-in/ski-out location and the tax assessment value. Properties that have this location are sold for a higher purchase price than the properties that do not have a ski-in/ski-out location. This study has only investigated how the ski-in/ski-out location affects the market value of properties in Björnrike and Lofsdalen. However, real estate agents from various alpine ski resorts in Sweden agree that the sales prices are higher for properties and condominiums with a ski-in/ski-out location.

In Björnrike, the value difference is not significant enough in order to be managed through value area divisions. In Lofsdalen, on the other hand, family-house properties with ski-in/ski-out location should be handled with separate value area divisions. One suggestion that this study has resulted in, and which is reported in the discussion, is that family-house properties at alpine ski resorts could be handled in different location classes in relation to the ski slope and the ski lift. Based on the location class, the family-houses would then be assessed differently. The closer to the ski slope the property is located, the higher the location factor the property will have, which affects the tax assessment value.

Infrastructure investments is a large part of the regional development in Sweden, researchers in the subject agrees that investment in infrastructure generate increased economic development, one thing they still share a disagreement in which calculating methods are suitable. Are there any winners or losers in infrastructure projects, for example, smaller cities in the countryside where highways have previously passed, have they benefited from a quicker and easier commuting to the city, or have they been adversely affected when the highway has been given a new stretch?

This research report focuses in one of the largest infrastructure investments in northern Sweden, European road 4 (E4) through Sundsvall. The research, combined with location-based sales comparison method and local analyzes, will show what effect market values will have on the houses real estate’s and what influence the road construction might have regarding to the values of the properties.

The results of these studies are shown trough the average changes in property prices in the areas of Njurundabommen, Nedre Haga/Skönsberg, Nolby/Kvissleby and Västbo. However, the result was shown to have too few transactions, which is common in local level sales analyzes. This generates uncertainty in the result, meaning that the values can be large in relation to the actual sales development. The uncertainty was minimized in the results by merging two similar areas, which finally gave a result that indicates that the areas in the study had a more negative development towards Sundsvall and Sweden, since the area received a new infrastructure in the form of the E4 Sundsvall.

Fungerande infrastruktur är viktigt för att samhället ska fungera. Det är därför också viktigt att Trafikverket och kommuner får tillgång till mark för utbyggnad av bland annat vägar och järnvägar. Samtidigt görs ett intrångi någons enskilda äganderätt. Markåtkomst för dessa ändamål kan ske med en frivillig överenskommelse mellan parterna men i vissa fall tvingas Trafikverket och kommuner att tvångsvis förvärva marken.

Syftet med arbetet är att ta reda på om Trafikverket och kommuner har några särskilda principer för markåtkomst gällande utbyggnad av vägar och järnvägar, samt försöka ta reda på hur fastighetsägare behandlas i en sådan process. Målet är att kunna bidra med ett bättre underlag för både Trafikverket och kommuner vad gäller deras riktlinjer för markåtkomst. För att besvara frågeställningarna i studien har intervjuer med ett antal kommuner samt sakkunniga inom Trafikverket genomförts.

Resultatet visade att det finns riktlinjer för hur själva markåtkomsten ska hanteras men ingen respondent ansåg att de hade några riktlinjer för hur en fastighetsägare ska behandlas i processen. Den största skillnaden mellan Trafikverket och kommunerna var att kommunerna nästan aldrig använder tillfälliga nyttjanderätter i detaljplanplanen utan förlitar sig på frivilliga överenskommelser ifall de behöver tillgång till mark, medan Trafikverket använder sig utav tillfälliga nyttjanderätter i väg- och järnvägsplan i större utsträckning. I slutsatsen framgår det att den främsta faktorn för att nå en överenskommelse är tidig kontakt med fastighetsägare där det är viktigt att visa förståelse för dennes situation. Många respondenter var också enade om att det är viktigt att hela tiden hålla fastighetsägare informerade om vad som ska ske och hur deras fastighet kommer att påverkas. Trots att det inte finns fastställda riktlinjer för hur en fastighetsägare ska behandlas verkar de flesta ändå utgå från liknande ”principer”. 

This study is a bachelor thesis at the Study Programme in Land Management with financial/legal orientation at the University of Gävle. 

Municipalities in Sweden are voluntarily responsible for road maintenance and financing of private roads, even though the actual responsibility is imposed on the property owners. One of the reasons behind these occurrences is the mergers of the municipalities that took place in the sixties and seventies, which made the remaining municipalities take over the management of the private roads. Over the decades, municipalities may decide to return these voluntarily managed private roads to the property owners. The returning of these private roads to the property owners is done through facility procedures to secure a long-lasting road maintenance. 

The aim of this study is to investigate these types of facility procedures that have occurred in reference to transitions from municipal to private management of private roads. The objective is to create a base of knowledge that the Swedish municipalities and cadastral authorities can use when working with these kinds of phenomenon. To reach the aim and objective, interviews have been done with five experts in the field and with five joint property management associations. These interviews provide valuable information from both experts and property owners. Five cadastral dossiers have been analysed to give a deeper understanding of the cadastral process and to supplement the interviews. 

The study shows that the road maintenance, in the analysed and the interviewed cases, often gets better when a private road’s management transfers from municipal to private. The property owners sometimes remain frustrated after the ending of the cadastral process, but this frustration has not been shown to affect the road maintenance in a negative way. In order to achieve a smooth cadastral process that leads to an appropriate management, the municipalities should assist the property owners with the application. As a starting point, the State cadastral authority should handle these types of cases to achieve better objectivity and neutrality, even though there is a municipal cadastral authority available. It is at last important that the cadastral process include communication, dialogue and clarity, and by doing so making the property owners aware of the situation.

Risk perception can be defined as people’s interpretation and subjective assessment of risk. The perception of risk is a crucial factor that is believed to impact people when taking financial decisions. Previous research shows clear differences between men’s and women’s risk taking in financial decision. Men are in general portrayed as more risk taking and not viewing risk as something problematic, whilst women are not as positive towards risk. The purpose with this study is to gain understanding of how risk perception differs between men and women when taking financial decisions, and to examine if there are any differences in men’s and women’s perception of risk throughout five dimensions of financial risk perception. To answer the study’s formulated research questions, a quantitative study in the form of questionnaire has been carried out. Collected data have been analyzed through a descriptive data analysis and t-tests. The results of this study are in line with previous research and indicate that women perceive financial risk as significantly higher than what men do. On the other hand, the study did not provide a clear result regarding differences between the genders’ risk perception in the five dimensions of financial risk perception. However, the study showed that women perceived the significant negative consequences for financial investments as significantly larger than men. This result can also be considered to be in line with previous research. Due to this, the result of the study can be seen as having contributed with further empirical support to previous scientific research regarding the differences between men and women’s risk perception when making investment decisions.

This thesis examines the internal corruption risk assessment processes employed by civil society organizations (CSOs) in Kampala, Uganda. Corruption poses significant challenges to social and economic development, particularly in developing nations like Uganda, where it undermines public trust and impedes progress. CSOs play a pivotal role in addressing these issues by promoting transparency and accountability. Through qualitative interviews and document reviews with five organizations, this study investigates the frameworks and methods CSOs use to identify, assess, and mitigate internal corruption risks. The six-step risk assessment model by Rausand & Haugen (2020) was used as a guiding framework to analyze these processes.  Key findings reveal diverse approaches: some CSOs employ structured and regularly updated risk assessments, while others rely on informal or outdated practices. Notably, none of the CSOs specifically focus on corruption risk assessment; instead, corruption is embedded within broader, general risk assessments. The study finds that limited funding, expertise, and external pressures significantly hinder CSOs' ability to conduct comprehensive assessments. Despite these challenges, CSOs demonstrate a common commitment to combating corruption, often driven by organizational values rather than formal structures. This study highlights the need for adaptable risk assessment frameworks that align with the varying capacities of CSOs, suggesting that improvements in documentation, transparency, and resource allocation could strengthen their anti-corruption efforts. The study contributes to a better understanding of risk management in Uganda’s civil society and offers recommendations to enhance their organizational integrity and effectiveness in anti-corruption initiatives.

Digital terrain models (DTMs) are a commonly used tool in planning various development projects within the state, municipalities, and the private sector. In planning for road and rail construction, the Swedish technical specification SIS-TS21144:2016 is often used as a document for controlling the production process of DTMs. Given that new technology opens the possibilities for faster, more efficient, and climate-smart data collection, this study aims to evaluate Unmanned Aerial System (UAS) with Light Detection and Ranging (LiDAR) from YellowScan and to evaluate the measurement uncertainty in height. In this study, the results of the study are compared with class 2 SIS-TS 21144:2016 for the flight heights 50 m and 80 m and the scanning angles 0 (in nadir), 10, 20 and 40 degrees. The site of the study is located just southwest of Gävle in a closed gravel pit with both hard packed and slightly looser substrates. The size of the study area was limited to 200 x 300 m, equivalent to 6 hectares. With Global Navigation Satellite System (GNSS) equipment, two control points were measured with Network-RTK (Real Time Kinematic). Subsequently, a control network of eight points was created. A total of 26 control grids were measured for comparisons of collected LiDAR data. The data collection was carried out with the Unmanned Aerial Vehicle (UAV) GeoDrone X4L equipped with LiDAR Scanner YellowScan Surveyor with an integrated Inertial Measurement Unit (IMU) from Applanix. Together, these units formed an UAS that could be remotely controlled and communicate its position. All processing was performed in software from Terrasolid, based on data from the flight route that was first processed in YellowScan CloudStation. The points were classified to distinguish ground points used in the generation of the DTM. An adjustment of the point cloud was made with the intention of raising ground level points to reduce the noise present in the data. The control grids could then be compared to the DTM and analysed. The results of the study show that YellowScan Surveyor achieves a Root Mean Square (RMS) in height of 0,024 m at 50 meters flight altitude, which equals 0,047m expanded measurement uncertainty (2 sigma level, 95 %). Even at 80 meters, relatively low uncertainty is achieved with an RMS of 0,040 m. The results of the study indicate that the influence of measurements at a wider scanning angle is not the only factor that deteriorates the results.   

Feeling safe is important for residents in their neighborhoods, but how do residents living in an area rumored to be unsafe perceive safety? This case study examined the perceived safety in a vulnerable area (Swedish: Utsatt område) in Gävle, Sweden. These vulnerable neighborhoods fall under the Swedish million housing program that consist of residential areas with large and high resident buildings that are often densified. This study aimed to examine the residents’ perception of safety in a neighborhood with the same conditions, in addition to evaluate crime prevention in the area using crime prevention through environmental design principles. territoriality, natural surveillance, activity support and access control. The aim of this study was achieved by using the following methods: CPTED inventory, safety walks and a survey. The safety walk was conducted with residents of the area. The inventory showed that crime prevention in the area is considered low, however, the results from safety walk suggest that the residents perceive the area as moderately safe. This study provides some suggestions in order to provide better crime prevention and better perception of safety in the area.Examples among the suggestions were to better the lighting and create more pedestrian crossovers on the car-based roads to decrease possible barrier effects. 

In cities where land availability is limited, rooftop photovoltaic panels (RPVs) offer high potential for satisfying concentrated urban energy demand by using only rooftop areas. However, accurate estimation of RPVs potential in relation to their spatial distribution is indispensable for successful energy planning. Classification, plane segmentation, and spatial analysis are three important aspects in this context. Classification enables extracting rooftops and allows for estimating solar energy potential based on existing training samples. Plane segmentation helps to characterize rooftops by extracting their planar patches. Additionally, spatial analyses enable the identification of rooftop utilizable areas for placing RPVs. This dissertation aims to address some issues associated with these three aspects, particularly (a) training support vector machines (SVMs) in large datasets, (b) plane segmentation of rooftops, and (c) identification of utilizable areas for RPVs. SVMs are among the most potent classifiers and have a solid theoretical foundation. However, they have high time complexity in their training phase, making them inapplicable in large datasets. Two new instance selection methods were proposed to accelerate the training phase of SVMs. The methods are based on locality-sensitive hashing and are capable of handling large datasets. As an application, they were incorporated into a rooftop extraction procedure, followed by plane segmentation. Plane segmentation of rooftops for the purpose of solar energy potential estimation should have a low risk of overlooking superstructures, which play an essential role in the placement of RPVs. Two new methods for plane segmentation in high-resolution digital surface models were thus developed. They have an acceptable level of accuracy and can successfully extract planar segments by considering superstructures. Not all areas of planar segments are utilizable for mounting RPVs, and some factors may further limit their useability. Two spatial methods for identifying RPV-utilizable areas were developed in this realm. They scrutinize extracted planar segments by considering panel installation regulations, solar irradiation, roof geometry, and occlusion, which are necessary for a realistic assessment of RPVs potential. All six proposed methods in this thesis were thoroughly evaluated, and the experimental results show that they can successfully achieve the objectives for which they were designed.

Training support vector machines (SVMs) for pixel-based feature extraction purposes from aerial images requires selecting representative pixels (instances) as a training dataset. In this research, locality-sensitive hashing (LSH) is adopted for developing a new instance selection method which is referred to as DR.LSH. The intuition of DR.LSH rests on rapidly finding similar and redundant training samples and excluding them from the original dataset. The simple idea of this method alongside its linear computational complexity make it expeditious in coping with massive training data (millions of pixels). DR.LSH is benchmarked against two recently proposed methods on a dataset for building extraction with 23,750,000 samples obtained from the fusion of aerial images and point clouds. The results reveal that DR.LSH outperforms them in terms of both preservation rate and maintaining the generalization ability (classification loss). The source code of DR.LSH can be found in https://github.com/mohaslani/DR.LSH.

Rooftop solar energy has long been regarded as a promising solution to cities’ growing energy demand and environmental problems. A reliable estimate of rooftop solar energy facilitates the deployment of photovoltaics and helps formulate renewable-related policies. This reliable estimate underpins the necessity of accurately pinpointing the areas utilizable for mounting photovoltaics. The size, shape, and superstructures of rooftops as well as shadow effects are the important factors that have a considerable impact on utilizable areas. In this study, the utilizable areas and solar energy potential of rooftops are estimated by considering the mentioned factors using a three-step methodology. The first step involves training PointNet++, a deep network for object detection in point clouds, to recognize rooftops in LiDAR data. Second, planar segments of rooftops are extracted using clustering. Finally, areas that receive sufficient solar irradiation, have an appropriate size, and fulfill photovoltaic installation requirements are identified using morphological operations and predefined thresholds. The obtained results show high accuracy for rooftop extraction (93%) and plane segmentation (99%). Moreover, the spatially detailed analysis indicates that 17% of rooftop areas are usable for photovoltaics.

The considerable potential of rooftop photovoltaics (RPVs) for alleviating the high energy demand of cities has made them a proven technology in local energy networks. Identification of rooftop areas suitable for installing RPVs is of importance for energy planning. Having these suitable areas referred to as utilizable areas greatly assists in a reliable estimate of RPVs energy production. Within such a context, this research aims to propose a spatially detailed methodology that involves (a) automatic extraction of buildings footprint, (b) automatic segmentation of roof faces, and (c) automatic identification of utilizable areas of roof faces for solar infrastructure installation. Specifically, the innovations of this work are a new method for roof face segmentation and a new method for the identification of utilizable rooftop areas. The proposed methodology only requires digital surface models (DSMs) as input, and it is independent of other auxiliary spatial data to become more functional. A part of downtown Gothenburg composed of vegetation and high-rise buildings with complex shapes was selected to demonstrate the methodology performance. According to the experimental results, the proposed methodology has a high success rate in building extraction (about 95% correctness and completeness) and roof face segmentation (about 85% completeness and correctness). Additionally, the results suggest that the effects of roof occlusions and roof superstructures are satisfactorily considered in the identification of utilizable rooftop areas. Thus, the methodology is practically effective and relevant for the detailed RPVs assessments in arbitrary urban regions where only DSMs are accessible.

Support vector machines (SVMs) are powerful classifiers that have high computational complexity in the training phase, which can limit their applicability to large datasets. An effective approach to address this limitation is to select a small subset of the most representative training samples such that desirable results can be obtained. In this study, a novel instance selection method called border point extraction based on locality-sensitive hashing (BPLSH) is designed. BPLSH preserves instances that are near the decision boundaries and eliminates nonessential ones. The performance of BPLSH is benchmarked against four approaches on different classification problems. The experimental results indicate that BPLSH outperforms the other methods in terms of classification accuracy, preservation rate, and execution time. The source code of BPLSH can be found in https://github.com/mohaslani/BPLSH. 

Rooftop photovoltaic panels (RPVs) are being increasingly used in urban areas as a promising means of achieving energy sustainability. Determining proper layouts of RPVs that make the best use of rooftop areas is of importance as they have a considerable impact on the RPVs performance in efficiently producing energy. In this study, a new spatial methodology for automatically determining the proper layouts of RPVs is proposed. It aims to both extract planar rooftop segments and identify feasible layouts with the highest number of RPVs in highly irradiated areas. It leverages digital surface models (DSMs) to consider roof shapes and occlusions in placing RPVs. The innovations of the work are twofold: (a) a new method for plane segmentation, and (b) a new method for optimally placing RPVs based on metaheuristic optimization, which best utilizes the limited rooftop areas. The proposed methodology is evaluated on two test sites that differ in urban morphology, building size, and spatial resolution. The results show that the plane segmentation method can accurately extract planar segments, achieving 88.7% and 99.5% precision in the test sites. In addition, the results indicate that complex rooftops are adequately handled for placing RPVs, and overestimation of solar energy potential is avoided if detailed analysis based on panel placement is employed.