Recently, there is a tremendous amount of high resolution imagery that wasn’t available years ago, mainly because of the advancement of the technology in capturing such images. Most of the very high resolution (VHR) imagery comes in three bands only the red, green and blue (RGB), whereas, the importance of using such imagery in remote sensing studies has been only considered lately, despite that, there are no enough studies examining the usefulness of these imagery in urban applications. This research proposes a method to investigate high resolution imagery to analyse an urban area using UAV imagery for land use and land cover classification. Remote sensing imagery comes in various characteristics and format from different sources, most commonly from satellite and airborne platforms. Recently, unmanned aerial vehicles (UAVs) have become a very good potential source to collect geographic data with new unique properties, most important asset is the VHR of spatiotemporal data structure. UAV systems are as a promising technology that will advance not only remote sensing but GIScience as well. UAVs imagery has been gaining popularity in the last decade for various remote sensing and GIS applications in general, and particularly in image analysis and classification. One of the concerns of UAV imagery is finding an optimal approach to classify UAV imagery which is usually hard to define, because many variables are involved in the process such as the properties of the image source and purpose of the classification. The main objective of this research is evaluating land use / land cover (LULC) classification for urban areas, whereas the data of the study area consists of VHR imagery of RGB bands collected by a basic, off-shelf and simple UAV. LULC classification was conducted by pixel and object-based approaches, where supervised algorithms were used for both approaches to classify the image. In pixel-based image analysis, three different algorithms were used to create a final classified map, where one algorithm was used in the object-based image analysis. The study also tested the effectiveness of object-based approach instead of pixel-based in order to minimize the difficulty in classifying mixed pixels in VHR imagery, while identifying all possible classes in the scene and maintain the high accuracy. Both approaches were applied to a UAV image with three spectral bands (red, green and blue), in addition to a DEM layer that was added later to the image as ancillary data. Previous studies of comparing pixel-based and object-based classification approaches claims that object-based had produced better results of classes for VHR imagery. Meanwhile several trade-offs are being made when selecting a classification approach that varies from different perspectives and factors such as time cost, trial and error, and subjectivity.

      Classification based on pixels was approached in this study through supervised learning algorithms, where the classification process included all necessary steps such as selecting representative training samples and creating a spectral signature file. The process in object-based classification included segmenting the UAV’s imagery and creating class rules by using feature extraction. In addition, the incorporation of hue, saturation and intensity (IHS) colour domain and Principle Component Analysis (PCA) layers were tested to evaluate the ability of such method to produce better results of classes for simple UAVs imagery. These UAVs are usually equipped with only RGB colour sensors, where combining more derived colour bands such as IHS has been proven useful in prior studies for object-based image analysis (OBIA) of UAV’s imagery, however, incorporating the IHS domain and PCA layers in this research did not provide much better classes. For the pixel-based classification approach, it was found that Maximum Likelihood algorithm performs better for VHR of UAV imagery than the other two algorithms, the Minimum Distance and Mahalanobis Distance. The difference in the overall accuracy for all algorithms in the pixel-based approach was obvious, where the values for Maximum Likelihood, Minimum Distance and Mahalanobis Distance were respectively as 86%, 80% and 76%. The Average Precision (AP) measure was calculated to compare between the pixel and object-based approaches, the result was higher in the object-based approach when applied for the buildings class, the AP measure for object-based classification was 0.9621 and 0.9152 for pixel-based classification. The results revealed that pixel-based classification is still effective and can be applicable for UAV imagery, however, the object-based classification that was done by the Nearest Neighbour algorithm has produced more appealing classes with higher accuracy. Also, it was concluded that OBIA has more power for extracting geographic information and easier integration within the GIS, whereas the result of this research is estimated to be applicable for classifying UAV’s imagery used for LULC applications.

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.

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.

Gravimetric methods applied for Moho recovery in areas with sparse and irregular distribution of seismic data often assume only a constant crustal density. Results of latest studies, however, indicate that corrections for crustal density heterogeneities could improve the gravimetric result, especially in regions with a complex geologic/tectonic structure. Moreover, the isostatic mass balance reflects also the density structure within the lithosphere. The gravimetric methods should therefore incorporate an additional correction for the lithospheric mantle as well as deeper mantle density heterogeneities. Following this principle, we solve the Vening Meinesz-Moritz (VMM) inverse problem of isostasy constrained by seismic data to determine the Moho depth of the South American tectonic plate including surrounding oceans, while taking into consideration the crustal and mantle density heterogeneities. Our numerical result confirms that contribution of sediments significantly modifies the estimation of the Moho geometry especially along the continental margins with large sediment deposits. To account for the mantle density heterogeneities we develop and apply a method in order to correct the Moho geometry for the contribution of the lithospheric thermal state (i.e., the lithospheric thermal-pressure correction). In addition, the misfit between the isostatic and seismic Moho models, attributed mainly to deep mantle density heterogeneities and other geophysical phenomena, is corrected for by applying the non-isostatic correction. The results reveal that the application of the lithospheric thermal-pressure correction improves the RMS fit of the VMM gravimetric Moho solution to the CRUST1.0 (improves ∼ 1.9 km) and GEMMA (∼1.1 km) models and the point-wise seismic data (∼0.7 km) in South America.

Direct georeferencing of airborne mobile mapping systems is developing with unprecedented speed using GNSS/INSintegration. Removal of systematic errors is required for achieving a high accurate georeferenced product in mobile mappingplatforms with integrated GNSS/INS sensors. It is crucial to consider the deflection of verticals (DOV) in direct georeferencing dueto the recently improved INS sensor accuracy. This study determines the DOV using Sweden’s EGM2008 model and gravity data.The influence of the DOVs on horizontal and vertical coordinates and considering different flight heights is assessed. The resultsconfirm that the calculated DOV components using the EGM2008 model are sufficiently accurate for aerial photogrammetrypurposes except for the mountainous areas because the topographic signal is not modeled correctly.

Residents of high-risk flood areas are often unaware and unprepared for extreme flood events. In order to raise awareness and improve preventative measures, methods of communicating the potential hazards, vulnerabilities, and risks associated with flood events need to enhanced. Geovisualizations that incorporate three-dimensional (3D) models of urban environments are being applied more frequently to improve communication of potential flood events to members of the lay-public. Recent studies suggest that the interactive and explorable environments provided by 3D geovisualization tools allow users to visualize complex geospatial data in a manner that is more easily understood than traditional 2D maps. The aim of this study was to examine the use of a 3D model for the purpose of communicating predicted flood levels in residential areas. An exploratory case study was conducted to construct and evaluate a 3D model of previously calculated data from the Testebo River in Gävle, Sweden. Methods for creating the model were developed with information obtained from in-depth literature reviews, and consultations with GIS professionals. To evaluate the communicative ability of the model, usability tests were conducted on a small sample size of participants. Through these processes, an explorable 3D model that represented the 100-year and highest probable flood scenarios in the residential areas of Varva, Strömsbro, Forsby and Stigslund was created. The results of the usability tests indicated the model was an effective visualization and provided appropriate tools for exploration. Although the study identified some limitations of the model and 3D models in general that should be considered, it also provides a valuable foundation on which to develop further studies of 3D models for flood communication purposes along the Testebo River and in other flood-prone areas. 

Dams are man-made structures that in order to keep functioning and to be considered structurally healthy need constant monitoring. Assessing the deformation of dams can be time consuming and economically costly.

Recently, the technique of Interferometric Synthetic Aperture Radar (InSAR) has proved its potential to measure ground and structural deformation. This geodetic method represents a cost-effective way to monitor millimetre-level displacements and can be used as supplemental analysis to detect movements in the structure and its surroundings.

The objective of this work is to assess the practicality of the method through the analysis of the surface deformation of the Ajaure dam located in northern Sweden, in the period 2014-2017, using the freely available Sentinel-1A images. The scenes, 51 in ascending and 47 in descending mode, were processed exploiting the Persistent Scatterer (PS) technique and deformation trends, and time series were produced.

Built in the 60’s, the Ajaure embankment dam is considered as high consequence, meaning that a failure would cause socio-economic damages to the communities involved and, for this reason, the dam needs constant attention. So far, a program of automatic measurements in situ has been collecting data, which have been used partly to compare with InSAR results.

Results of the multi temporal analysis of the limited PS points on/around the dam show that the dam has been subsiding more intensely toward the centre, where maximum values are of approximately 5 ± 1.25 mm/year (descending) and 2 ± 1.27 mm/year (ascending) at different locations (separated of approximately 70 m). Outermost points instead show values within -0.7 and 0.9 mm/year, describing a stable behaviour. The decomposition of the rate has furthermore revealed that the crest in the observation period has laterally moved toward the reservoir.

It has been observed that the operation of loading and unloading the reservoir influence the dam behaviour. The movements recorded by the PS points on the dam also correlate with the air temperature (i.e. seasonal cycle).

The research revealed that the snow cover and the vegetation could have interfered with the signal, that resulted in a relative low correlation. Therefore, the number of PS points on and around the dam is limited, and comparison with the geodetic data is only based on a few points. The comparison shows general agreement, showing the capacities of the InSAR method.

The study constitutes a starting point for further improvements, for example observation in longer period when more Sentinel1 images of the study area are collected. Installation of corner reflectors at the dam site and/or by use of high resolution SAR data is also suggested.

This study evaluates the accuracy of Microsoft HoloLens (Version 1) for small-scale industrial activities, comparingits measurements to ground truth data from a Kuka Robotics arm. Two experiments were conducted to assess its positiontracking capabilities, revealing that the HoloLens device is effective for measuring the position of dynamic objects with smalldimensions. However, its precision is affected by the velocity of the trajectory and its position within the device's field of view.While the HoloLens device may be suitable for small-scale tasks, its limitations for more complex and demanding applicationsrequiring high precision and accuracy must be considered. The findings can guide the use of HoloLens devices in industrialapplications and contribute to the development of more effective and reliable position-tracking systems.

Space-geodetic techniques such as Global Navigation Satellite Systems (GNSS) and Syntenic Aperture Radar interferometry (InSAR) are powerful tools to measure and monitor ground surface motion. InSAR has widely been used for the detection and quantification of slow mass movements over the past three decades mainly at the local and regional scales. The high performance and millimeter-level measurement accuracy of radar satellite to provide a dense deformation map at different spatial and temporal resolutions are the key factors to think of using SAR data and InSAR technique as an efficient tool for geohazards motoring system at the nationwide scale.Sweden has recently joined to the countries having InSAR Ground Motion Service (GMS) at a nationwide scale. The InSAR service of Sweden, which will soon be freely available for users, provides the displacement time-series of measurement points for the entire country. The Swedish GMS project was started last year and is an ongoing collaboration between the Geological Survey of Norway (NGU) and several Swedish organizations (led by the Swedish National Space Agency (SNSA)). The InSAR-based GMS of Sweden has been generated by NGU using Sentinel-1 data (2015–2020) and the Persistent Scatterer Interferometry (PSI) technique. The web-based GMS of Sweden consists of ~1,5 billion time-series measurement points obtained from both descending and ascending satellite orbital modes.Currently, the Swedish GMS is under evaluation and validation phase and the given plan has been designed to assess the quality or validate the GMS products. We plan to conduct the data validation through two main phases: 1) a cross-comparison between InSAR measurement points and ancillary data such as GNSS, Corner Reflectors (CR), Electronic Corner Reflectors (ECR) and leveling data, and 2) assessment of tropospheric and ionospheric effects on InSAR measurement points. Specifically, we will evaluate different approaches and data for the InSAR tropospheric corrections, such as Very-Long-Baseline Interferometry (VLBI), Water Vapour Radiometry (WVR), and GNSS data at the Onsala Space Observatory (OSO).

In the first phase of validation, leveling data collected in Gothenburg and Stockholm cities, mainly over the residential areas and public transport infrastructures compared to the corresponding InSAR measurements points (vertically converted) for a five-year period. The initial results present a high correlation between two sets of the vertical displacements. The same procedure will be performed for the Kiruna city where the mining activities resulted in a drastic urban land subsidence. Since the CRs and ECRs have recently been installed in different parts of Sweden, we do not have them as PS points in the current version of the GMS. Therefore, those CR-based measurement points will be used in future accuracy assessments.

As the InSAR-based GMS can be used to monitor and identify the potential risk of geo-related hazards in Sweden, the society will directly benefit from the outcomes of this project. This open access product will help the stakeholders with decision support for prioritization of risk-reducing measures, and identification of the need for further investigations for areas in danger. The service could also assist municipalities and county administrative boards to have an update information regarding urban areas which are more prone to land subsidence and disruption urban infrastructure.

The Kattegat sea region between Denmark and Sweden is identified as a region both economically and environmentally sensitive. Statistics indicate that over two thousand vessels per day navigate in the region. Navigation route optimization for the region is vital for efficient transportation. Optimized routes allow a vessel to carry the maximum amount of goods per course leading to efficient fuel consumption, which can greatly benefit in an economical and environmental aspect. Such optimization requires a highly accurate and reliable vertical reference surface for efficient transportation. In the Baltic Sea and Kattegat, a geoid is now used as such a surface. For geoid modelling, homogenous and reliable gravity measurements are required over a larger area surrounding the computation point. The Kattegat region consists of gravity data mainly from the Swedish Fyrbyggaren marine campaign 2019, Kattegat airborne campaign 2018 and several older datasets from the Nordic Geodetic Commission (NKG) database. These gravity data over Kattegat region have been measured using different instruments in various time epochs that inherit them with uncertainties depending on the platform type, instrument sensor type, filter type, corrections applied, processing software and many other parameters. In this study, the data uncertainty of gravity measurements from various sensors in the Kattegat region was studied through statistical and graphical evaluations. It was found out that the data from Kattegat airborne campaign 2018 deviate systematically with from the more reliable Fyrbyggaren marine campaign 2019 and other marine datasets. The airborne campaign was therefore tentatively corrected by the estimated shift +1.46 mGal before further analysis was made of the other datasets. It is found that NKG publication numbers 29, 42, 44, 610, 611 and 616 from the NKG gravity database have a standard uncertainty of around 2-3 mGal. Which is within the range of allowable uncertainty for future applications. These datasets may thus positively contribute to NKG database along with data from the Swedish Fyrbyggaren marine campaign 2019 and the shifted Kattegat airborne campaign 2018. These datasets should be used to model the geoid over the region in the future.

Traditionally, sea level is observed at tide gauge stations, which usually also serve as height reference stations for national leveling networks and therefore define a height system of a country. Thus, sea level research across countries is closely linked to height system unification and needs to be regarded jointly. One of the main deficiencies to use tide gauge data for geodetic sea level research and height systems unification is that only a few stations are connected to permanent GNSS receivers next to the tide gauge in order to systematically observe vertical land motion. As a new observation technique, absolute positioning by SAR using active transponders on ground can fill this gap by systematically observing time series of geometric heights at tide gauge stations. By additionally knowing the tide gauge geoid heights in a global height reference frame, one can finally obtain absolute sea level heights at each tide gauge. With this information the impact of climate change on the sea level can be quantified in an absolute manner and height systems can be connected across the oceans.The paper presents the results of a project, which was conducted in the years 2019 to 2021 in the frame of ESA´s Baltic+ initiative. Within this project a test network of electronic corner reflectors (ECR) as targets for Sentinel-1 was realized in the Baltic Sea area. The ECR locations were either co-located with tide gauges or with permanent GNSS stations in order to observe systematically the ellipsoidal heights of the tide gauges and possibly also any vertical land motion at the stations. Data for the year 2020 were collected at 10 stations in Estonia, Finland, Poland and Sweden and jointly analyzed with GNSS data, tide gauge records and regional geoid height estimates. The obtained results are promising, but also exhibit some problems related to the ECR´s and their performance. At co-located GNSS stations the estimated ellipsoidal heights agree in a range between about 2 and 50 cm between both observation systems. From the results it could be identified that most likely variable systematic electronic instrument delays of the ECR´s are the main reason for these differences and that each instrument needs to be calibrated individually. Nevertheless, the project provides a valuable data set, which offers the possibility to enhance methods and procedures in order to develop the geodetic SAR positioning technique towards operability. All data and reports are accessible at the following web site: https://www.asg.ed.tum.de/iapg/baltic/

This paper describes national cooperation in Sweden launched by its universities and authorities, aimed at improving geodata education. These initiatives have been focused upon providing common access to geodata, the production of teaching materials in Swedish and organizing annual meetings for teachers. We argue that this type of cooperation is vital to providing high quality education for a poorly recognized subject in a country with a relatively small population.

The SWEREF 99 national geodetic reference frame has been used in Sweden since 2007 and it was adopted by EUREF in 2000 as the national realisation of ETRS89 in Sweden [Jivall and Lidberg, 2000]. The SWEREF 99 reference frame is defined by an active approach through the 21 original (fundamental) SWEPOS GNSS stations, hence relying on positioning services such as the network real time kinematic (NRTK) and post processing services. The SWEREF 99 coordinates are assumed to be fixed in time and no temporal variations are expected. However, the stability of the stations and their coordinates can be altered due to equipment change or software as well as local movements at the reference stations.To be able to check all alterations mentioned above and having a backup national network of GNSS points, approximately 300 passive so-called consolidation points are used. The consolidation points are a subset (the main part) of the so-called SWEREF points established from 1996 and onwards. All 300 points are remeasured with static GNSS for 2x24 hours using choke ring antennas on a yearly basis with 50 points each year. The original data processing was done with the Bernese GNSS software in a regular basis and the reprocessing was carried out with both the Bernese and the GAMIT-GLOBK software packages during 2017-2018.The resulting coordinates in SWEREF 99 from GAMIT and Bernese processing are equal at 1–2 mm level for the horizontal and 4 mm for the vertical components (1 sigma) when using almost the same models and processing strategy. The result from the original processing, which partly is based on other models and parameters, differs slightly more for the north component compared to the reprocessing results (RMS of 2 mm compared to 1 mm).Our analysis both of Bernese and GAMIT results shows that the standard uncertainties for a single SWEREF 99 coordinate determination (with 2x24 hrs observation) is about 2 mm for the horizontal components and 6 mm in height. It is interesting to note that the coordinate repeatability is on the same level also for the original processing, where we have differences in models and parameters used during the years. This indicates that our concept for determining SWEREF 99 coordinates has worked well on the mentioned uncertainty level.We performed trend analysis and statistical tests for the points having minimum three observations to investigate the stability of the estimated SWEREF 99 coordinates. The low rate of redundancy (just one redundant observation in case of three observations) was a problem so a modified version of the F-test was developed which gave good agreement with visual interpretation of the time series. This strategy showed that about 10% of the points had trends (with notable movements), but we should be aware of the low redundancy. With more observations in the future, we can determine trends more reliably.We will continue to analyse the point coordinate repeatability and trends when we get more data. Further on, some reprocessing is needed to be compatible with the SWEREF 99 update 2021 at SWEPOS. We will also study the effect of using different satellite systems and finally prepare for the publication of updated coordinates in the Digital Geodetic Archive (DGA) provided by Lantmäteriet.

In this study, three different procedures: checkpoint RMS of residuals, statistical evaluation of AT results using t-test, and comparison of a photogrammetric digital surface model (DSM) and LiDAR data are used to analyse the effect of IMU and GNSS uncertainties on the final adjusted results. The outcome suggests that the method of block-wise GNSS shift correction is the better method for aerial triangulation and one should use appropriate observable weights in AT. The comparison of checkpoint RMS residuals between the two methods shows that the block-wise solution is on average 6cm more accurate than the strip-wise solution.

Previous investigation of seismic anisotropy indicates the presence of a simple mantle flow regime beneath the Turkish-Anatolian Plateau and Arabian Plate. Numerical modeling suggests that this simple flow is a component of a large-scale global mantle flow associated with the African superplume, which plays a key role in the geodynamic framework of the Arabia-Eurasia continental collision zone. However, the extent and impact of the flow pattern farther east beneath the Iranian Plateau and Zagros remains unclear. While the relatively smoothly varying lithospheric thickness beneath the Anatolian Plateau and Arabian Plate allows progress of the simple mantle flow, the variable lithospheric thickness across the Iranian Plateau is expected to impose additional boundary conditions on the mantle flow field. In this study, for the first time, we use an unprecedented data set of seismic waveforms from a network of 245 seismic stations to examine the mantle flow pattern and lithospheric deformation over the entire region of the Iranian Plateau and Zagros by investigation of seismic anisotropy. We also examine the correlation between the pattern of seismic anisotropy, plate motion using GPS velocities and surface strain fields. Our study reveals a complex pattern of seismic anisotropy that implies a similarly complex mantle flow field. The pattern of seismic anisotropy suggests that the regional simple mantle flow beneath the Arabian Platform and eastern Turkey deflects as a circular flow around the thick Zagros lithosphere. This circular flow merges into a toroidal component beneath the NW Zagros that is likely an indicator of a lateral discontinuity in the lithosphere. Our examination also suggests that the main lithospheric deformation in the Zagros occurs as an axial shortening across the belt, whereas in the eastern Alborz and Kopeh-Dagh a belt-parallel horizontal lithospheric deformation plays a major role.

The location selection of a coffee shop is crucial for its success or failure. It should be decided in a strategical and comprehensive way. Geographic Information System (GIS) technology has rapidly become a popular tool for complicated location decision problems, because of its remarkable function for handling spatial and non-spatial data. In this particular project, based on GIS softwares, a spatial interaction model, the Huff model, and a decision making model, the Analytic Hierarchy Process (AHP), a multi-criteria model, were used to determine the most promising area for opening a new coffee shop in San Francisco, United States. By using two GIS softwares, ArcMap and ERDAS, to analyze different kinds of criteria, which can be classified as socioeconomic and demographic, three customized optimizing location maps, the optimized location for Huff capture, the optimized location for AHP-based multi-criteria model and the optimized location map for both Huff and AHP, were obtained. When these three maps were compared with the actual situation, the commercial district and the area that was surrounded by a university and parks were evaluated as the most suitable location for establishing a new coffee shop in San Francisco. The result shows that visitor flow rate was a primary factor that influences the operation of coffee shops.

Urban forms, as a physical proxy of human mobility and activity, are crucial for understanding the mechanisms and factors behind urban dynamics. The rapid expansion of urban sensors and big data has significantly advanced our comprehension of cities and societies. Currently, the development of complexity sciences has led to more sophisticated simulation models, presenting new opportunities for understanding complex urban phenomena. This dissertation integrates fractal geometry theory, deep learning models, and agent-based modelling (ABM) to enhance the understanding and future generative design of sustainable urban forms. Three models were developed in this dissertation based on: Graph-based fractality index (GFI), Spatio-structural self-similarity, Simple agents–complex emergent path systems (SACP), as well as a model and web-based tool for road evaluation by desire path system (RED-PaSS). (1) The GFI model, grounded in fractal theory and deep learning techniques, is capable to characterize the complexity of building groups; (2) the spatio-structural self-similarity model examines self-similarity from a spatial and structural perspective, correcting long-standing misinterpretations in classical statistical fractal theories. The spatio-structural self-similarity model is capable to understand historical urban forms through validation with data from London building groups and US street networks; (3) the SACP model is based on ABM and simulates pedestrian movement based on visibility parameters and simple principles of global destination awareness and local environmental adaptation. The findings of SACP indicate that the angle of vision is crucial for path pattern emergence; and (4) the RED-PaSS model and tool that evaluates road networks by simulating optimal pedestrian paths based on the SACP model. Case studies of 708 US neighbourhood-scale road networks demonstrate RED-PaSS's potential to evaluate, rank, and enhance road networks, improving pedestrian mobility and convenience. This dissertation's holistic approach not only aids in the characterization of current urban patterns but also in generative design of future urban landscapes that are sustainable and resilient. The integration of advanced computational techniques, such as deep learning and ABM, enables exploration of urban dynamics at unprecedented scales and resolutions. The continuous advancement of these models is crucial for addressing urbanization challenges and fostering sustainable, liveable cities.

In well-planned open and semi-open urban areas, it is common to observe desire paths on the ground, which shows how pedestrians themselves enhance the walkability and affordance of road systems. To better understand how these paths are formed, we present an agent-based modelling approach that simulates real pedestrian movement to generate complex path systems. By using heterogeneous ground affordance and visit frequency of hotspots as environmental settings and by modelling pedestrians as agents, path systems emerge from collective interactions between agents and their environment. Our model employs two visual parameters, angle and depth of vision, and two guiding principles, global conception and local adaptation. To examine the model’s visual parameters and their effects on the cost-efficiency of the emergent path systems, we conducted a randomly generated simulation and validated the model using desire paths observed in real scenarios. The results show that (1) the angle (found to be limited to a narrow range of 90–120°) has a more significant impact on path patterns than the depth of vision, which aligns with Space Syntaxtheories that also emphasize the importance of angle for modelling pedestrian movement; (2) the depth of vision is closely related to the scale-invariance of path patterns on different map scales; and(3) the angle has a negative exponential correlation with path efficiency and a positive correlation with path costs. Our proposed model can help urban planners predict or generate cost-efficient path installations in well- and poorly designed urban areas and may inspire further approaches rooted in generative science for future cities.

Examining the complexity of urban form may help to understand human behavior in urban spaces, thereby improving the conditions for sustainable design of future cities. Metrics, such as fractal dimension, ht-index, and cumulative rate of growth (CRG) index have been proposed to measure this complexity. However, as these indicators are statistical rather than spatial, they result in an inability to characterize the spatial complexity of urban forms, such as building footprints. To overcome this problem, this paper proposes a graph-based fractality index (GFI), which is based on a hybrid of fractal theory and deep learning techniques. First, to quantify the spatial complexity, several fractal variants were synthesized to train a deep graph convolutional neural network. Next, building footprints in London were used to test the method, where the results showed that the proposed framework performed better than the traditional indices, i.e., the index is capable of differentiating complex patterns. Another advantage is that it seems to assure that the trained deep learning is objective and not affected by potential biases in empirically selected training datasets Furthermore, the possibility to connect fractal theory and deep learning techniques on complexity issues opens up new possibilities for data-driven GIS science.

The way of representing Earth has changed; two dimensional (2D) maps have turned into three Dimensional (3D) representations. There are many studies in order to create 3D city maps as well as areas where these are applied such as 3D cadastral, 3D visualization and flood simulation, etc. These can be created with the aid of different data sources using photogrammetric Digital Surface Model (DSM) derived from image matching and from Light Detection and Ranging (LiDAR) point clouds or both of them combining orthophotos and building footprints. Several software has been developed to ease and speed up this process.

In this study, a current state-of-the art in the 3D city modeling with particular interest to commercial software was analyzed. DSMs from image matching (Satellite and Airborne) were used in order to create a 3D city model of Trento, Italy. The objectivewas to examine the degree of automation and the computation time of two available software: Feature Manipulation Engine (FME) and Building Reconstruction (BREC). Other problem such as the quality of the DSM needed would be discussed for each software and the results would be compared to those achieved using LiDAR data. Recommendations and possible problems would also be addressed.

In order to create a 3D city model, the ALDPAT software (Airborne LiDAR Data Processing and Analysis Tool) has been used to separate the ground regions (Digital Terrain Model, DTM) from the man-made objects and trees (Normal Digital Surface Model, nDSM). FME and BREC software have been used to reconstruct the 3D city model.

The output results from FME and BREC have been analyzed qualitatively and quantitatively. The comparison between the models generated from photogrammetric and LiDAR DSMs have been performed. The results show that buildings generated by satellite images have poorest quality compared with buildings from LiDAR and airborne data.

In particular, the performed tests will be shown that among the Level of Details (LoD), a LoD1 and LoD2 3D city models can be generated using a DSM by image matching. A deeper study should be done in order to analyze the level of detail qualitatively.

Landslides and floods are the two most important geohazards in Sweden. Due to the climate change effects, it is believed that the risk of occurring these geohazards will increase in Sweden causing for example the land to become more prone to landslides. Additionally, due to the isostatic uplift caused by the retreating of the ice sheet, approximately 10,000 years ago, marine sediments involving marine clays have become exposed above sea level in Scandinavia. Infiltration of fresh water has (and is) leached the salt from the pores within the marine clays leading to the formation a special kind of clay known as the quick clay in the northern countries. These glacial clays and postglacial silts cause more ground surface instability and slopes become more prone to trigger landslides, which is the case for concentration of the most landslides in the southwest of Sweden. Hence, quick-clay landslides are common geohazards in Nordic countries, which potentially could cause a considerable economical and live cost. The most recent Gjerdurm landslide in Norway was of this kind quick-clay related. In recent years, an area close to the Göta River of southeast of Sweden has been the subject of numerous surface and airborne geophysical surveys for detailed subsurface mapping and delineation of the quick-clay and sediments hosting them including the very undulating the crystalline bedrock. These existing studies including access to bore hole observations and geotechnical studies motivated us to study also long-term surface deformation in order to study climate effects, erosion, precipitation and underlying quick-clay presence in this area and neighboring regions. We employed radar data with Syntenic Aperture Radar (SAR) interferometry techniques. To this end, Sentinel-1 data from 2015 to 2019 were processed with the Small BAslineSubset (SBAS) technique to estimate time-series displacements and to generate deformation map for that region. The initial results show that the heterogenous deformation observed in the study area with maximum subsidence rate of -22 mm/yr. The deforming areas appear to be located on regions with the thickest column of the clay near the river where we anticipate also thicker quickclay layers present. The quick-clays in this region overlie a thick (ca. 20 m) coarse-grained layer interpreted from the surface geophysical measurements to be associated with the formation and triggering of quick-clays in the area. With such a large surface deformation and the underling geology, we observe two phenomena in the study. A possible sudden risk of quick-clay landslide but also a long-term creeping of clays and destabilizing effect that may accelerate erosion at the river bank causing more landslides in the future. The cause of the large deformation is still unclear and will be investigated together with hydrogeological and geophysical data available in the study.This study however provides compelling evidence of major surface deformation that should be considered for long-term risk mitigation and planning.

Long-term monitoring of temporal gravity field and ground water level changes in Iran and its associated ground subsidence seen by geodetic methods are important for water source and hazard management.The high-rate (cm to dm/year) ground subsidence in Iran has been widely investigated by using different geodetic techniques such as precise leveling, GPS and interferometric synthetic aperture radar (InSAR). The previous individual SAR sensors (e.g. ERS, ENVISAT and ALOS) or multi-sensors approach have successfully shown localized subsidence in different parts of Iran. Now, thanks to freely available new SAR sensor Sentinel-1A data, we aim at investigate further the subsidence problem in this region.

In this ongoing research, firstly, we use a series of Sentinel-1A SAR Images, acquired between 2014 to 2017 to generate subsidence-rate maps in different parts of the country. Then, we correlate the InSAR results with the monthly observations of the Gravity Recovery and Climate Experiment (GRACE) satellite mission in this region. The monthly GRACE data computed at CNES from 2002 to 2017 are used to compute the time series for total water storage changes. The Global Land Data Assimilation System( GLDAS) hydrological model (i.e. soil moisture, snow water equivalent and surface water) is used to estimate Groundwater changes from total water storage changes obtiaend from GRACE data.

So far, we have generated a few interferograms, using Sentinel-1A data and SNAP software, which shows a few cm subsidence in western Tehran in last 2 years. We will try more Sentinel images for this area to better constrain the rate and extent of deformation and will continue InSAR processing for the rest of the country to localize the deformation zones and their rates. We will finally comapre the rates of subsidence obtained from InSAR and the rate of groundwater changes estimated from GRACE data.

These proceedings reflect on the content of FIG’s (International Federation of Surveyors) 11th International FIG Workshop on the Land Administration Domain Model & 3D Land Administration (LADM & 3D LA), 11-13 October 2023, Gävle, Sweden.

The global temperature is at an all-time high, the polar ice is melting, the sea levels are rising and the associated disasters are a time bomb. These variations in temperature are thought to trace roots to anthropogenic sources. In order to mitigate these changes and slow down the rate of warming, several efforts have been made locally and internationally. One of the agreed up-on way to do this is by using forests as reservoirs for carbon since carbon is one of those greenhouses gasses responsible for the warming. Mau forest, in Kenya, is one of those ecosystems where degradation has happened tremendously, though still viewed as a potential site for reclamation.

Using GIS and remote sensing analysis of Landsat images, the study sought to compare various change detection techniques, find the amount of biomass lost or gained in the forest and the possible income accrued in case the forest is placed under the Kyoto protocol’s Clean Development Mechanism (CDM). Various vegetation ratios were used in the study ranging from NDVI, NDII to RSR. The results obtained from these ratios were not quite convincing as setting threshold for the ratios to separate dense forest from other forms of vegetation was not straightforward. As a consequence, the three ratios NDVI, NDII and RSR were combined and substituted for RGB bands respectively. A classification was done using this combination and the results compared to classifications based on tasselled cap and principal component analysis (PCA).

The results of the various methods showed that the forest has lost its biomass over time. The methods indicated that the section of the forest studied lost between 8088 ha and 9450 ha of dense forest land between 1986 and 2010. This is between 29% and 35% of forest cover lost depending on the various methods of change detection used. This acreage when converted into forest biomass at a rate of 236 Mg.ha-1 gives a value of between 1908768 tons and 2230200 tons of carbon. If the Mau forest were registered as Kyoto compliant, then in the carbon market, this would have been a loss of between $24.1m and $ 28.2m according to California carbon dashboard (28th, May 2015). This is a huge sum of money if paid to a rural community as benefits from carbon sequestration via forestry. Such are the amounts that a community can earn by protecting a forest for the purposes of carbon sequestration and trading.

With the economic growth, the number of motor vehicles has increased rapidly for the last decades, especially in developing countries like China and India. Availability of more vehicles makes it more convenient for people to travel and merchandise transport. The increase of the number of vehicles also brings stresses to public traffic and pollution to the environment. When the number of vehicles on the road is over the available space, it results in traffic congestion. The problem is being studied and there are several solutions to it, like building more roads, rebuilding the existing streets and enlarging the cities. Based on the traffic reason and the environment reason, the government and the institute of environmental protection appeal to the public to take public transport means instead of private cars. But the measure affects the utilization ofmotor vehicles.

Global Positioning System (GPS) provides autonomous geo-spatial positioningand navigation service. Once the user enters the destination, the navigation service will show the shortest path from the location of the user to the destination. Following the guide makes the vehicles running purposively, and it is also favorable for traffic control and management.

Theoretically, if the diver keeps the same driving mode, the shortest path will cost the shortest time, but in reality, the traffic environment is complex and the driving speed is variable thus the shortest path is probably not the fastest path. In this study, the hinder factors of the speed and traffic are fixed constructions on the road, like: turnings, hospitals, schools, residential areas, traffic lights and the user-controlled factor (sites of traffic jams, accidents, and temporary construction on the road). We take the hinderfactors of traffic and driving speed into consideration while providing the route plan, finding the shortest-time path, and showing the result as an online map via the web Geographic Information System (GIS) application. We show that reducing the travelling time of motor vehicles, makes the traffic flow more rapid and efficient. Alsoreducing the emission time of motor vehicles, diminishes the greenhouse effect.

Beside these, the achievement of our study also shows that the public can take advantage of open source tools and data to build their GIS application to do spatial and data analysis.

We used satellite images, earthquake catalogues and field observations to study several active fault systems and their interactions in Sabzevaran Area in SE Iran. The focus of this study is to verify the link between the active faults, their kinematics and seismic activity. Field observations and geomorphological analysis highlight the interaction of the active faults. Moreover, most of the tectonic activity is observed in the area, related to the Chahmazrae- North Faryab shear zone. Most of the earthquakes in this shear zone are reverse and occur in the deeper crust while aftershocks dominantly occur in the shallower crust. The Main Zagros Reverse Fault (MZRF) is the source of reverse events and the Chahmazrae- North Faryab shear zone is source of left-lateral, oblique reverse faulting events, and strike-slip events. These types of the earthquakes in the study area confirm the idea of tectonic proximity of the root faults and shear zone. In the interaction area, minor fractures begin to develop and are progressively linked to the main faults. In the en échelon arrangement of the faults, the minor faults have grown and linked the en échelon segments of the faults. It seems that the earthquake ruptures can spontaneously propagate across both extensional and the compressional fault steps. This propagation occurs along strike-slip faults such as Sabzevaran fault and its branches.

Scale is an essential notion in geography and geographic information science (GIScience). However, the complex concepts of scale and traditional Euclidean geometric thinking have created tremendous confusion and uncertainty. Traditional Euclidean geometry uses absolute size, regular shape and direction to describe our surrounding geographic features. In this context, different measuring scales will affect the results of geospatial analysis. For example, if we want to measure the length of a coastline, its length will be different using different measuring scales. Fractal geometry indicates that most geographic features are not measurable because of their fractal nature. In order to deal with such scale issues, the topological and scaling analyses are introduced. They focus on the relationships between geographic features instead of geometric measurements such as length, area and slope. The scale change will affect the geometric measurements such as length and area but will not affect the topological measurements such as connectivity.

This study uses three case studies to demonstrate the scale issues of geographic features though fractal analyses. The first case illustrates that the length of the British coastline is fractal and scale-dependent. The length of the British coastline increases with the decreased measuring scale. The yardstick fractal dimension of the British coastline was also calculated. The second case demonstrates that the areal geographic features such as British island are also scale-dependent in terms of area. The box-counting fractal dimension, as an important parameter in fractal analysis, was also calculated. The third case focuses on the scale effects on elevation and the slope of the terrain surface. The relationship between slope value and resolution in this case is not as simple as in the other two cases. The flat and fluctuated areas generate different results. These three cases all show the fractal nature of the geographic features and indicate the fallacies of scale existing in geography. Accordingly, the fourth case tries to exemplify how topological and scaling analyses can be used to deal with such unsolvable scale issues. The fourth case analyzes the London OpenStreetMap (OSM) streets in a topological approach to reveal the scaling or fractal property of street networks. The fourth case further investigates the ability of the topological metric to predict Twitter user’s presence. The correlation between number of tweets and connectivity of London named natural streets is relatively high and the coefficient of determination r² is 0.5083.

Regarding scale issues in geography, the specific technology or method to handle the scale issues arising from the fractal essence of the geographic features does not matter. Instead, the mindset of shifting from traditional Euclidean thinking to novel fractal thinking in the field of GIScience is more important. The first three cases revealed the scale issues of geographic features under the Euclidean thinking. The fourth case proved that topological analysis can deal with such scale issues under fractal way of thinking. With development of data acquisition technologies, the data itself becomes more complex than ever before. Fractal thinking effectively describes the characteristics of geographic big data across all scales. It also overcomes the drawbacks of traditional Euclidean thinking and provides deeper insights for GIScience research in the big data era. 

Geographic space is not neutral or lifeless, but an intricate living structure composed of numerous small features and a few large ones across all scales. The living structure is crucial for comprehending how geographic space shapes human activities. With the emerging geospatial big data, researchers now have unprecedented opportunities to study the relationship between geographic space and human behaviour at a finer spatial resolution. This thesis leverages multisource geospatial big data, including Twitter check-in locations, street networks from OpenStreetMap, building footprints, and night-time light images, to explore the fundamental mechanisms of human activities that underlie geographic space. To overcome the limitations of conventional analytics in this era of big data, we propose the topological representation and living structure based on Christopher Alexander's conception of space.

We utilize scaling and topological analyses to reveal the underlying living structure of geographic space with various big datasets. Our results demonstrate that tweet locations or human activities at different scales can be accurately predicted by the underlying living structure of street nodes. We also capture and characterize human activities using big data and find that building footprints and tweets show similar scaling patterns in terms of sizes of their spatial clusters. We also propose an improved spatial clustering method to increase the processing speed of geospatial big data. Finally, we adopt topological representation to identify urban centres by the fusion of multi-source geospatial big data. The living structure, together with its topological representation can help us better understand human activities patterns in the geographic space at both city and country levels.

With the advent of satellite altimetry in 1973, new scientific applications became available in oceanography, climatology, and marine geosciences. Moreover, satellite altimetry provides a significant source of information facilitated in the geoid determination with a high accuracy and spatial resolution. The information from this approach is a sufficient alternate for marine gravity data in the high-frequency modeling of the marine gravity field quantities. The gravity gradient tensor, consisting of the second-order partial derivatives of the gravity potential, provides more localized information than gravity measurements. Marine gravity observations always carry a high noise level due to environmental effects. Moreover, it is not possible to model the high frequencies of the Earth's gravity field in a global scale using these observations. In this article, we introduce a novel approach for a determination of the gravity gradient tensor at sea level using satellite altimetry. Two numerical techniques are applied and compared for this purpose. In particular, we facilitate the radial basis functions (RBFs) and the harmonic splines. As a case study, the gravitational gradient tensor is determined and results presented in the Persian Gulf. Validation of results reveals that the solution of the harmonic spline approach has a better agreement with a theoretical zero-value of the trace of the Marussi gravitational gradient tensor. However, the data-adaptive technique in the RBF approach allows more efficient selection of the parameters and 3-D configuration of RBFs compared to a fixed parameterization by the harmonic splines.

A geomorphological map is probably the most comprehensive way of illustrating the landform distribution, surface form, material, age, and the processes responsible for the landscape look. As such geomorphological maps are invaluable in the fields of geoconservation assessment, evaluation and management. It is therefore an oddity, as well as an inconvenience, that there is no systematic landform inventory or mapping of the geomorphology that is comparable to the surveys undertaken for geology or soils in the UK. For that purpose the project of “Developing a Geomorphological Map of Wales” was initiated by the Countryside Council for Wales (CCW) as part of a PhD project investigating the Quaternary glaciations of Wales.

To develop a mapping methodology suitable for the Welsh landscape, three contrasting areas were selected to provide a wide range of geomorphological features. Aerial photography, satellite imagery, digital elevation models, and field investigations of landform/sediment associations, formed the foundation for landform interpretation, which were compiled in a GIS.

Geomorphological maps of Cadair Idris, and the Central and North Cambrian Mountains were produced, scale 1:10 000 – 1:25 000. The maps form an extensive inventory of the geomorphological geodiversity, and were used for providing data to palaeoglaciological reconstructions and making geoconservation recommendations to the CCW. The recommended sites are of regional interest; their rareness, distinct morphology, interesting research and educational value makes them worthy of RIGS (Regional Important Geodiversity Sites) protection.

A Geomorphological Map of Wales has the potential for wider practical, scientific and educational benefits, such as for governmental bodies, local authority planners, tourism, researchers, teachers, landowners and land managers. Without a full account of all the geomorphological components of a landscape, there can be no full understanding of the landscape history or the various landforming processes. Important geodiversity sites may be overlooked, badly managed or lost before their full potential are realised.

Coastal valleys in the west part of Mid-Wales, such as the Mawddach, Dysynni, Tal-y-llyn and Dyfi, are believed to have acted as corridors for ice which drained the Welsh Ice Cap during the Devensian. Connectivity analyses of valley patterns from detailed digital elevation models, and interpretation of satellite images and aerial photographs show the existence of large variations in the amount of glacial modification between these valleys. Although all the valleys are glacially over-deepened along Silurian fault lines, only the Dyfi basin exhibits a dendritic pattern, with V-shaped cross profiles and valley spurs typical of valleys formed by fluvial processes.

The connectivity analyses show that the Dyfi basin exhibits a purely dendritic pattern with little glacial modification of the preglacial fluvial valley pattern in form of valley breaching. It is proposed here that the general river valley morphology of the Dyfi basin is of a pre-Late Devensian age. This suggests a complex glacial drainage history, where cold-based ice was not only confined to the interior uplands, but also covered low-altitude areas previously believed to be a major drainage conduit for the Welsh Ice Cap. This indicates that Late Devensian glacial erosion was not as intense as previously believed and larger areas might have been overlain by cold-based ice.

Coastal valleys in the west part of mid-Wales, such as the Mawddach, Dysynni, Tal-y-llyn and Dyfi, are believed to have acted as corridors for ice which drained the Welsh Ice Cap during the Devensian. Analysis of detailed digital elevation models and interpretation of satellite images and aerial photographs show the existence of large variations in the amount of glacial modification between these valleys. Although all the valleys are glacially over-deepened along Silurian fault lines, only the Dyfi basin exhibits a dendritic pattern, with V-shaped cross profiles and valley spurs typical of valleys formed by fluvial processes. Connectivity analysis of the Dyfi basin shows that it exhibits a nearly dendritic pattern with connectivity α and β values of 0.74 and 1.01 respectively, with little glacial modification of the preglacial fluvial valley pattern in the form of valley breaching. It is proposed that the general river valley morphology of the Dyfi basin is of a pre-Late Devensian age. Several examples have been identified of glacial meltwater incision into a well-developed pre-existing river valley system, causing river capture across watersheds. The degree of preservation of the pre-glacial fluvial valley system within the Dyfi basin indicates limited modification by glacial processes, despite the area being subjected to Late Devensian glacier activity. It is possible that major parts of the basin were covered by cold-based or slow-moving ice close to or under a migrating ice divide, with the major ice drainage occurring along the weaker zone of the Pennal Fault, causing minor adjustments to the surrounding interfluves and uplands.

Limiting cities’ negative impact for global sustainability suggests compact city development. However, extensive and accessible urban nature is important for urban dwellers’ wellbeing. Aligning efforts to make cities locally and globally sustainable means resolving this conflict.

This thesis applies spatial analysis of urban dwellers’ regularly occurring experiences, as these are important wellbeing indicators, looking specifically at Stockholm, Sweden. The aim is to contribute to a nuanced understanding of urban environments’ influence on urban dwellers’ experiences. Paper I investigates how accessibility to various environment features impact the probability that people have positive or negative experiences. Paper II applies resilience principles to investigate what experiences exist together in neighbourhoods.

The environment have considerable influence on people’s experiences. Some common indicators in urban planning display weak relationships with experiential outcome, while other less common ones have larger effects. Neighbourhood compositions of experiences display consistent patterns, both spatially across Stockholm and with respect to resilience principles. Many neighbourhoods harbour diverse positive experiences, while a few are dominated by negative ones.

The results suggest that human-environment relations should be given more consideration in urban discourse and urban planning. A relational approach could improve urban dweller’s experiences, and positively influence their wellbeing. For urban planning to be able to handle the complexity of such an approach, I suggest that resilience principles can be heuristics for an urban development that does not compromise people’s experiences. The methodological framework developed here can be applied in other cities, as it can identify specific places for transformation, but also increase knowledge of the interplay between urban environments and people’s experiences across different contexts.

An unresolved issue in creating resilient cities is how to obtain sustainability benefits from densification while not eroding the capacity of social-ecological systems to generate wellbeing for urban dwellers. To understand how different relationships between urban form and wellbeing together play out, we analysed geocoded experiential data (1460 experiences from 780 respondents) together with variables of the physical environment. Through statistical and spatial analysis, we operationalised resilience principles to assess what urban environments provide “resilience at eye level” – a diversity of experiences and a level of connectivity between them that limit adverse outcomes. We found 8 typologies of experiential landscapes – distinct compositions of 11 categories of experiences. Our analysis shows that typologies with experiences supportive of wellbeing are diverse and exist in environments that balance residents and workplaces, avoid extreme spatial integration and/or density and have accessible nature. Typologies with many experiences hindering wellbeing fail in one or several of these respects. Our findings suggest that resilience principles can act as a guiding heuristic for urban densification that does not compromise human wellbeing.

Non-stationary flooding of oil-saturated reservoirs has a long-standing and durable place as the main secondary method of oil production and maintenance of reservoir pressure in the development of most oil reservoirs. The water injection into the reservoir creates a delayed problem - the inevitable, often catastrophic flooding of oil production wells, provoked by a sudden and irreversible change in water saturation. The theory of two-phase flow filtration created by Buckley and Leverett does not take into account the loss of stability of the displacement front, which provokes an abrupt change and a triplicity of the water saturation value. Therefore, a mathematically simplified approach was proposed at one time, a repeatedly differentiable approximation to exclude a “jump” in water saturation. Such a simplified solution led to well-known negative consequences of the waterflooding practice, which experts call the “viscous instability of the displacement front”, the “fingering displacement front”. This work has presented a novel approach to formulation decisive rules for the first time allowing timely detection and prevention of the consequences of loss of stability of the displacement front and targeted control of the flooding system by stopping, forcing, limiting operating modes, assigning workover solutions of producing and injection wells. It is possible to quickly solve important short-term practical tasks passing traditional labor- intensive incorrect deterministic tasks and complex methods of solution mobilizing the injected water and controlling the fluid production rate, more precisely water and oil on the basis of the discriminant criterion.

Precise gravity measurements have been repeatedly observed in Fennoscandia since the 1960-ties, first by relative gravimeters, then by absolute gravimeters, for studying the temporal change of gravity related with the on-going glacial isostatic adjustment (GIA). The results of such studies are vital for understanding GIA processes and tuning GIA and Earth structure models.

This study uses monthly repeated data from the twin satellite mission GRACE for 164 months between 2003 and 2016 for estimating the temporal change of surface gravity, its ratio (f) to the land uplift rate as well as the upper mantle density related with the viscous mass flow in the mantle. The maximum negative change of gravity is estimated to −1.8 μGal/yr, and f is estimated to −0.172 ± 0.018 μGal/mm.

The solutions for f from the three independent techniques (relative, absolute and satellite gravity observations) were found to agree statistically without significant biases, and they were merged in a joint solution to −0.166 ± 0.004 μGal/mm, corresponding to a mean upper mantle mass flow density of 3402.5 ± 95 kg/m³, which decreases towards the uplift center.

Streets provide the framework of a city and they are necessary for human life. Some underlying patterns of street networks cannot be directly recognized by people. In this study, topological analysis of urban street networks was adopted to build up new insight into urban morphology. Space syntax, which has been integrated into GIS, was applied for the analysis of spatial configuration, and fifty Swedish cities were chosen as samples to uncover various urban patterns. Street connectivity was the focus of the analysis and axial lines were the main analytical tools. The aim of this study was to hierarchically represent the cities’ streets and classify the sample cities into different types by urban morphology.

Street data for Swedish cities were collected from OpenStreetMap. ArcGIS 10, with the Axwoman extension, provided a platform to carry out the topological analysis. Natural roads, axial lines and space syntax parameters were generated automatically with the functions of Axwoman. Hierarchical levels of streets were visually represented and the underlying pattern of each city was gotten from the hierarchical representation. Based on street hierarchy, the fifty sample cities were classified into nine groups, wherein cities of the same group had uniform hierarchical levels. Using the hierarchical pattern of each group’s axial lines, the nine city groups were further reclassified into three types.

It was found that, for the street network of most sample cities represented with axial lines, not more than 40% of their streets have connectivity larger than the average value. The hierarchical representation also revealed that streets with high connectivity, which provide greater accessibility, were only minorities in the sample cities. Moreover, minor streets with high connectivity were almost distributed in city centers.

In some of the studied cities, axial lines made better representation of the hierarchical patterns of streets, while in others, it did not provide a suitable way of uncovering urban patterns compared to natural roads. A limitation of axial lines manifested in this study was that it chopped curved roads into several segments, thus, disrupting the continuity of streets.

In general, axial lines can provide a way to uncover urban patterns. They have meaningful effect to city residents and these patterns can help people gain better understanding of the urban structure. In addition, the hierarchical patterns of streets can be used to model pedestrian and traffic flows, predict crime occurrences, and make spatial plans. The hierarchical representation of streets can also contribute to people’s wayfinding performance.

This thesis examines the urban morphology of fifty cities using spatial syntax analysis. The analysis compares the urban street networks of European, USA, Islamic and East Asian cities. Street connectivity was the main metric and natural roads were the basis for the analysis. The aim of the study was to analyze determine how sensitive space syntax methods are for uncovering the hierarchical patterns of urban street networks and examining their scale-free and small-world properties.

Street data was collected from OpenStreetMap. ArcGIS 10 with the Axwoman extension was used to study the hierarchical levels of street networks. Matlab provided the platform to examine the scale-free property of street data. Pajek software was used to measure the small-world behavior. Based on the hierarchical representation, the fifty sample cities were classified into different groups and their scale-free and small-world properties were studied.

From a traditionally morphological perspective, it was found that some cities in Europe have a close-knit cellular and organic urban morphology. Cities in the USA exhibit gridiron patterns on the whole. Some Islamic cities have special urban structure with houses grouped around the cul-de-sac lanes. Several of the East Asian cities studied also have grid forms. According to the space syntax analysis, urban street networks that have a connectivity value greater than the average value were less than 40%. The results showed that for most cities, the street connectivity distribution follows a power-law distribution and exhibits scale-free properties. Urban street networks of all sample cities were found to have a small-world property.

Space syntax cannot detect all of the morphological patterns recognized in traditional morphological studies. The method can, however, efficiently quantify the spatial configuration of a large sample. Space syntax’s topological and scaling metrics thus provide a way to compare urban street networks. These metrics can thus help classify cities according to their street patterns but also contribute to an understanding of human behavior within and thus the design of urban spaces. For example, an urban street network with a small-world property could have high efficiency for traffic flows at local and global levels and should be considered in further study.

Branches of complexity theory have been widely employed in geographic information systems (GIS) to explore phenomena that appear in urban environments. Among these, space syntax, as an urban morphological application of complexity theory, has attracted increasing attention in recent years.

Accordingly, many computer-based tools have been developed to realize related analysis spatially, especially those that can be integrated as functions with GIS. In this thesis, a space syntax tool – Axwoman – is redeveloped and tested as an extension of ESRI ArcGIS Desktop in order to fulfill certain specific needs in urban morphological analysis. It is primarily used to calculate all space syntax measures for several urban systems and to explore the relationships between these measures. To meet the needs for this new version of Axwoman, several functions have been updated and changed, for drawing, coloring, and classifying axial lines as maps for visual thinking; ticking overpasses and excluding them from computing space syntax parameters; and integrating AxialGen and Axwoman.

In accordance with this, several case studies have been performed on the urban street networks in large cities. In this paper, Stockholm was chosen as the study object at both the urban level and the building level. After the scaling analysis and time efficiency analysis, the results are also interpreted from a structural point of view and in terms of how the function of space is subject to its morphological structure. Finally, the connectivity of axial lines (a spatial measurement in space syntax theory) was found to follow a power-law distribution.

Through this work, the new edition of Axwoman generating satisfactory outputs, the research have proved that the connectivity of axial lines follows a lognormal distribution or a power-law-like distribution, which is one of the heavy-tailed distributions. In addition, it was have found that axial lines better for capture the underlying urban morphologies showed in their study on redefining the generated axial lines from street center lines. Moreover, fewer longest axial lines will show up on the maps, just as coincidental as the shape of mental maps, which proved that the axial line representations can be a powerful tool for urban studies.

China has the largest population and the fastest growing economy in the world. The general public's demand for health is rising promptly with the improvement of the living standard. However, the limited and unbalanced medical resource have caused the prominent problem of the society, even in the capital city of Beijing, the new hospital constructions with rational allocation is iminent and significant. Along with the technology development and Internet popularization, GIS approaches and related products has been widely used in the people's daily life. The main focus of this paper is to select a site for building a new hospital in Haidian District of Beijing using GIS-based Multi-Criteria Analysis (MCA). With Analytical Hieraichy Process(AHP) and Rank Order Method (ROM) for the weight setting on factor criteria, necessity tests and sensitivity tests are applied to check which criteria are really necessary and how the results are sensitive to their weight change. The optimal site located in Wenquan Town (E: 116.182, N:40.039) is screened from several candidate sites usin Google Earth maps, which makes the ultimate result more convincing and practical. It can be concluded that GIS-based MCA with necessity and sensitivity tests proposes a novel and useful reference to other site selection decision makers, and also provides constructive tools for the public asministration to set up efficent databases for decision makers to carry out spatial analyses. To make it more maneuverable and practical, a further research on th improvement of this method will have a promising future. 

Abstract

A wildfire is an uncontrollable fire in an area of combustible fuel that occurs in the wild or countryside area. Wildfires are becoming a deadly and frequent event in Europe due to extreme weather conditions. In 2018, wildfires profoundly affected Sweden, Finland, and Norway, which were not big news before. In Norway, although there is well–organized fire detection, warning, and mitigation systems, mapping wildfire risk areas before the fire occurrence with georeferenced spatial information, are not yet well-practiced. At this moment, there are freely available remotely sensed spatial data and there is a good possibility that analysing wildfire hazard areas with geographical information systems together with multicriteria decision analysis (GIS–MCDA) and frequency ratio models in advance so that subsequent wildfire warning, mitigation, organizational and post resilience activities and preparations can be better planned. 

This project covers eight counties of Norway: Oslo, Akershus, Østfold, Vestfold, Telemark, Buskerud, Oppland, and Hedmark. These are the counties with the highest wildfire frequency for the last ten years in Norway. In this study, GIS-MCDA integrated with analytic hierarchy process (AHP), and frequency ratio models (FR) were used with selected sixteen–factor criteria based on their relative importance to wildfire ignition, fuel load, and other related characteristics. The produced factor maps were grouped under four main clusters (K): land use (K1), climate (K2), socioeconomic (K3), and topography (K4) for further analysis.

The final map was classified into no hazard, low, medium, and high hazard level rates. The comparison result showed that the frequency ratio model with MODIS satellite data had a prediction rate with 72% efficiency, followed by the same model with VIIRS data and 70% efficiency. The GIS-MCDA model result showed 67% efficiency with both MODIS and VIIRS data. Those results were interpreted in accordance with Yesilnacar’s classifications such as the frequency ratio model with MODIS data was considered a good predictor, whereas the GIS-MCDA model was an average predictor. When testing the model on the dependent data set, the frequency ratio model showed 72% with MODIS & VIIRS data, and the GIS-MCDA model showed 67% and 68% performance with MODIS and VIIRS data, respectively. In the hazard maps produced, the frequency ratio models for both MODIS and VIIRS showed that Hedmark and Akershus counties had the largest areas with the highest susceptibility to wildfires, while the GIS-MCDA method resulted to Østfold and Vestfold counties.

Through this study, the best independent wildfire predictor criteria were selected from the highest to the lowest of importance; wildfire constraint and criteria maps were produced; wildfire hazard maps with high-resolution georeferenced data using three models were produced and compared; and the best, reliable, robust, and applicable model alternative was selected and recommended. Therefore, the aims and specific objectives of this study should be considered and fulfilled.

This paper describes a unique method for the semi-automatic detection of historic charcoal production sites in LiDAR-derived digital elevation models. Intensified iron production in the early 17th century has remarkably influenced ways of how the land in Sweden was managed. Today, the abundance of charcoal kilns embedded in the landscape survives as cultural heritage monuments that testify about the scale forest management for charcoal production has contributed to the uprising iron manufacturing industry. An arbitrary selected study area (54 km2) south west of Gävle city served as an ideal testing ground, which is known to consist of already registered as well as unsurveyed charcoal kiln sites. The proposed approach encompasses combined morphometric classification methods being subjected to analytical image processing, where an image that represents refined terrain morphology was segmented and further followed by Hough Circle transfer function applied in seeking to detect circular shapes that represent charcoal kilns. Sites that have been identified manually and using the proposed method were only verified within an additionally established smaller validation area (6 km2). The resulting outcome accuracy was measured by calculating harmonic mean of precision and recall (F1-Score). Along with indication of previously undiscovered site locations, the proposed method showed relatively high score in recognising already registered sites after post-processing filtering. In spite of required continual fine-tuning, the described method can considerably facilitate mapping and overall management of cultural resources.