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.

The Swedish capital Stockholm is at the forefront of biogas gas use, especially when it comesto biogas used for vehicle gas. This technology has the potential of being a fuel with veryhigh environmental performance, but in order to realize the full potential publicenvironmental management must be optimized. Environmental objectives are anenvironmental management is one tool that is used to strive for the desired development. Theaim of this study is to explain the dynamics within the biogas system in Stockholm, with aparticular emphasis on which factors that affects the amount of biogas available for vehiclegas upgrading on the market in Stockholm. The study has been conducted using modelingsessions with key stakeholders involved in the biogas system. The study concludes that theformulation of environmental objectives has a profound impact on how the variousstakeholders act, and thus how the system behaves. The trade off of how much fossil naturalgas that can be mixed into the renewable biogas based vehicle gas is at the very pinnacle ofcomplex matter. A conclusion that is of vital importance for the local planning process andwhen the experiences of Stockholm’s environmental planning are communicated out to therest of the world.

Slope processes are important to understand if we are to protect fragile environments. Every year slope development in weak soils put nearby infrastructure in risk zones of sliding and ravine erosion takes away field areal from farmers as they grow even larger. Many methods for doing a risk analysis of a slope and its soil are complicated and require a lot of equipment. A simple way to do a slope investigation is explained in this report, along with its advantages and disadvantages. The authors construct a shear ring, an apparatus to measure peak shear stress of soils before fracturing. LIDAR scanning of two small ravines are also made to illustrate how laser scanning can be used to accurately measure denudation in slopes. The results vary, the shear ring is mostly a success aside from errors caused by difficulty in taking representative samples and disturbance. Some of the laboratory work made to determine material properties fail at giving good results, often a result of bad samples or disturbance in the tests. The LIDAR is determined to be a good instrument when working with slope development. / Sluttningsprocesser är viktiga att förstå och studera om vi ska kunna skydda känsliga områden. Varje år så sätter svaga jordar i sluttningar närliggande infrastruktur i riskzonen för att ligga på ett glidplan som snabbt kan släppa om jorden blir för blöt eller om för mycket tyngd läggs ovanpå. Samtidigt så tar ravinerosion bort åkerareal från bönder varje år medan ravinerna blir större och större. Många metoder för att göra riskanalyser av sluttningar är komplicerade och kräver mycket utrustning. I denna rapport så testas ett enkelt sätt att göra en sluttningsanalys med tillhörande diskussion kring dess fördelar och nackdelar. Författarna konstruerar en shear ring, en apparat som används för att testa jordens möjlighet att motstå en applicerad kraft. Två sidoraviner scannas även med LIDAR som en bas för att studera denudation i sluttningar. Resultaten varierar, shear ring-apparaturen bestäms som väl fungerande med undantag från vissa utförda tester, där svårigheter uppstod då jordproverna var störda eller mindre representativa. Vissa av laborationerna på jorden misslyckas med att ge bra värden, vilket ofta är ett resultat av dåliga eller störda prover. Laserscanningar av raviner med LIDAR bestäms som ett bra sätt att studera utvecklingen i sluttningar samt att mäta erosion.

Future sea level rise associated to global warming is one of the greatest societal and environmental challenges of tomorrow. A large part of the contribution comes from glaciers and ice sheets discharging ice and meltwater into the ocean and the recent worldwide increase is worrying. Future predictions of sea level rise try to encompass the complex processes of ice dynamics through glacier modelling but there are still large uncertainties due to the lack of observations or too coarse parameterisation, particularly for processes occurring at the glacier interfaces with the bed (sliding) and with the ocean (calving). This thesis focuses on modelling these processes from two marine-terminating glaciers in Svalbard, Kronebreen and Tunabreen. By inverting three years of high temporal resolution time-series of surface velocities on Kronebreen, basal properties are retrieved with the ice flow model Elmer/Ice in Paper I. Results suggest that surface melt during the summer greatly influences the dynamics of the following season and that sliding laws for such glaciers should be adapted to local and global processes changing in space and time. The subglacial drainage system, fed by the surface melt, is modelled in Paper II during two melting seasons. Results show different configurations of efficient and inefficient drainage systems between years and the importance of using a sliding law dependent on spatio-temporal changes in effective pressure. The interaction with the ocean is incorporated in Paper III by combining a series of models, including an ice flow model, a plume model and a particle model for discrete calving and compares the output with observations. Results show the importance of glacier geometry, sliding and undercutting on calving rate and location. However, more observations and analytic methods are needed. Time-lapse imagery placed in front of Tunabreen have been deployed and a method of automatic detection for iceberg calving is presented in Paper IV. Results show the influence of the rising plume in calving and the front destabilisation of the local neighbourhood.

Lithological core logging is a subjective and time consuming endeavour which could possibly be automated, the question is if and to what extent this automation would affect the resulting core logs. This study presents a case from the Zinkgruvan Zn-Pb-Ag mine, Bergslagen, Sweden; in which Classification and Regression Trees and K-means Clustering on the Self Organising Map were applied to X-Ray Flourescence lithogeochemistry data derived from automated core scan technology. These two methods are assessed through comparison to manual core logging. It is found that the X-Ray Fluorescence data are not sufficiently accurate or precise for the purpose of automated full lithological classification since not all elements are successfully quantified. Furthermore, not all lithologies are possible to distinquish with lithogeochemsitry alone furter hindering the success of automated lithological classification. This study concludes that; 1) K-means on the Self Organising Map is the most successful approach, however; this may be influenced by the method of domain validation, 2) the choice of ground truth for learning is important for both supervised learning and the assessment of machine learning accuracy and 3) geology, data resolution and choice of elements are important parameters for machine learning. Both the supervised method of Classification and Regression Trees and the unsupervised method of K-means clustering applied to Self Organising Maps show potential to assist core logging procedures.

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. / För att begränsa städers negativa påverkan på global hållbarhet förordas ofta kompakta stadsmiljöer. För att säkra stadsbors välbefinnande krävs emellertid stora och tillgängliga naturområden. Denna konflikt måste lösas för att nå en stadsutveckling som bidrar till både lokal och global hållbarhet. Denna avhandling består av två studier av Stockholm som tillämpar rumslig analys av människors upplevelser, då dessa är viktiga indikatorer för välbefinnande. Den undersöker hur tillgänglighet till olika miljöfaktorer är relaterade till positiva och negativa upplevelser. Vidare tillämpar den resiliensprinciper för att undersöka vilka upplevelser som samexisterar på områdesskala. Stadsmiljön har betydande påverkan på människors upplevelser. Vissa vanliga indikatorer inom stadsplanering visar svaga samband med upplevelser, medan andra mindre vanliga har större effekter. Sammansättningar av upplevelser på områdesskala uppvisar genomgående mönster, både rumsligt och i förhållande till resiliensprinciper. Många områden innehåller en mångfald av positiva upplevelser, medan ett fåtal domineras av negativa upplevelser. Resultaten visar att relationer mellan människa och miljö bör ta en mer central plats i stadsplaneringen, då detta erbjuder möjligheter att förbättra stadsbors upplevelser. Resiliensprinciper kan fungera som tumregler inom stadsplaneringen för en stadsutveckling som inte äventyrar människors upplevelser. Metoden som utvecklats här kan appliceras i andra städer, då den kan identifiera specifika platser för omvandling, men också leda till djupare förståelse för samspelet mellan stadsmiljöer och människors upplevelser i olika sammanhang.

We are currently speeding towards significant changes in the climate of the earth which, if ignored, will lead to severely altered climatic conditions with serious consequences for several species and ecosystems. The polar regions especially are very sensitive to climate changes, and the changes these regions undergo affect the climate on a global scale. To slow the global warming, it is crucial that we understand earth’s climatic and environmental history, and how it responds to changes in the climate. Palaeoclimatic archives hold much information of past climate variations stored in proxies that can be analysed to understand past environments. This study focuses on loess as one such proxy to analyse grain sizes, carbon storage and organic matter in a sequence from Adventdalen, Svalbard. The study has been conducted using grain size analysis and loss on ignition (LOI) as main methods to reconstruct late Holocene climate changes in the region. The results have provided an overview of temperature oscillations, many of which coincide with main climatic events of the past, and have been used to estimate the depositional ages of the different layers of the sequence. / Dagens klimatförändringar går allt snabbare mot en framtid med svårt omkastade klimatförhållanden som medför allvarliga konsekvenser för flera arter och ekosystem. Polarområdena är särskilt känsliga för klimatförändringar, och de förändringar som sker här påverkar klimatet på global nivå. En avgörande faktor för att bromsa den globala uppvärmningen är att vi förstår jordens klimathistoria och hur jorden reagerar på förändringar i klimatet. Paleoklimatiska arkiv innehåller mycket information om klimatvariationer förr. Sådan information finns lagrad i material som kan analyseras för att vidare förstå miljöer från förr. Den här studien fokuserar på lössjord som ett sådant material för att analysera kornstorlekar och organiskt material i en lössekvens från Adventdalen i Svalbard. Studien har genomförts genom att använda en kornstorleksanalysator och loss on ignition (LOI) som huvudsakliga metoder för att rekonstruera klimatförändringar under yngre Holocen i området. Resultaten har givit en överblick av temperaturförändringar, av vilka flera sammanfaller med större förflutna klimathändelser, och har använts för att göra en uppskattning av åldrar på de olika lagren av sekvensen.

Mars’ climate has undergone many massive changes over the course of it’s lifetime. In order toestablish how Mars lost the vast majority of its water, we must be able to understand how Marsis losing its atmosphere today. By understanding the current escape rates of H and D and theprocesses that control them, we can extrapolate back in time to model the escape rates under pastconditions. By using the Exospheric General Model (EGM) developed by researchers at LATMOS,Sorbonne University, I have simulated the density profiles and escape rates of H, D, related isotopesand particles due to collisions with hot oxygen particles in the Martian exosphere at the currentepoch at mean solar activity. By adding H and D to the model and implementing changes to theprogram between simulations, I have improved the accuracy of the escape rate of these particlesfrom Mars in the EGM. While my results for H, H2 and HD reflect what has been observed fromin-situ Martian Satellite, MAVEN, future work is needed to include the solar wind interaction for Din the model, as it has been shown to be significant and has been left out of this work.

Multitemporal SAR images have been used successfully for the detection of different types of environmental changes. The detection of urban change using SAR images is complicated due to the special characteristics of SAR images—for example, the existence of speckle and the complex mixture of the urban environment. This thesis investigates the detection of urban changes using SAR images with the following specific objectives: (1) to investigate unsupervised change detection, (2) to investigate reduction of the speckle effect and (3) to investigate spatio-contextual change detection. Beijing and Shanghai, the largest cities in China, were selected as study areas. Multitemporal SAR images acquired by ERS-2 SAR (1998~1999) and Envisat ASAR (2008~2009) sensors were used to detect changes that have occurred in these cities. Unsupervised change detection using SAR images is investigated using the Kittler-Illingworth algorithm. The problem associated with the diversity of urban changes—namely, more than one typology of change—is addressed using the modified ratio operator. This operator clusters both positive and negative changes on one side of the change-image histogram. To model the statistics of the changed and the unchanged classes, four different probability density functions were tested. The analysis indicates that the quality of the resulting change map will strongly depends on the density model chosen. The analysis also suggests that use of a local adaptive filter (e.g., enhanced Lee) removes fine geometric details from the scene. Speckle suppression and geometric detail preservation in SAR-based change detection, are addressed using the nonlocal means (NLM) algorithm. In this algorithm, denoising is achieved through a weighted averaging process, in which the weights are a function of the similarity of small image patches defined around each pixel in the image. To decrease the computational complexity, the PCA technique is used to reduce the dimensionality of the neighbourhood feature vectors. Simple methods to estimate the dimensionality of the new space and the required noise variance are proposed. The experimental results show that the NLM algorithm outperformed traditional local adaptive filters (e.g., enhanced Lee) in eliminating the effect of speckle and in maintaining the geometric structures in the scene. The analysis also indicates that filtering the change variable instead of the individual SAR images is effective in terms of both the quality of the results and the time needed to carry out the computation. The third research focuses on the application of Markov random field (MRF) in change detection using SAR images. The MRF-based change detection algorithm shows limited capacity to simultaneously maintain fine geometric detail in urban areas and combat the effect of speckle noise. This problem has been addressed through the introduction of a global constraint on the pixels’ class labels. Based on NLM theory, a global probability model is developed. The iterated conditional mode (ICM) scheme for the optimization of the MAP-MRF criterion function is extended to include a step that forces the maximization of the global probability model. The experimental results show that the proposed algorithm is better at preserving the fine structural detail, effective in reducing the effect of speckle, less sensitive to the value of the contextual parameter, and less affected by the quality of the initial change map compared with traditional MRF-based change detection algorithm. / <p>QC 20130610</p>

Global warming is widely reported to be a cause of water scarcity and increased water con-sumption. As a consequence, it becomes harder for water suppliers to be prepared for increaseddemands. It is possible to predict the upcoming demand with the help of machine learningtools, however, a preliminary analysis of water consumption patterns is important for a goodprediction. This work focuses on water consumption patterns and studies their change withtime as well as the effects of meteorological factors on it.In order to aid the investigation and scrutinization of the patterns, a new semi-automatedtool was developed. Its algorithm is based on the Mann-Whitney U statistical test and performsgrouping of the weeks with similar sets of hourly water consumption. It helps to frame off theseasons of the year within which the patterns are similar. Along with that, K-means clusteringwas applied to the data to retrieve the patterns and to compare the performance with the newlydeveloped algorithm. On top of that, the effects of the population growth and meteorologicalvariables on water consumption were studied.K-means clustering showed more robust performance than the newly developed algorithmand therefore the ways of improvement were discussed along with the significance of gooddata quality and thorough data pre-processing. It was detected that municipalities with thedifferent housing situation had different persistent summer patterns of water consumption. Ingeneral municipalities with prevailing individual housing tend to consume more water duringthe summer per capita than others. Furthermore, municipalities with prevailing individualhousing were observed to be less robust against temperature growth and humidity decreasethan those with prevailing apartment housing as the latter increase their water consumptionless significantly in response to mentioned meteorological variables change. Therefore, consid-ering the population growth, the benefits of planning new multi-apartment dwelling areas inpreference to individual housing were discussed in the context of sustainable water use andclimate change. / Global uppvärmning kan orsaka både vattenbrist och ökad vattenförbrukning. Som en kon-sekvens blir det svårare för vattenförsörjningsföretag att förberedda sig på de ökande kraven.Det är möjligt att förutsäga den kommande efterfrågan med hjälp av verktyg för maskininlärn-ing, men det är viktigt att analysera vattenförbrukningsmönster för att få en bra förutsägelse.Detta arbete fokuserar därför på att analysera, samt studerar effekterna av meteorologiskafaktorer och hur semesterperioden påverkar vattenförbrukningen.Ett nytt halvautomatiskt verktyg utformades för att extrahera dagliga vattenförbrukn-ingsmönster från förbrukningstidserier. Algoritmen anger vilka veckor på året som har liknandemönster och grupperar dem i så kallade konsumtionssäsonger. För att utvärdera prestandan förverktyget användes en grupperingsmetod den så kallade K-means clustering på samma data.Utöver det studerades även effekterna av befolkningstillväxten och meteorologiska variabler påvattenförbrukningen.K-means klustring visade sig ha en mer robust prestanda än den nya framtagna utveckladealgoritmen och därför diskuterades olika sätt att förbättra algoritmen samt vikten av god rå-datakvalitet. Det upptäcktes att kommuner med olika bostadssituation reagerade olika på varmtoch torrt väder samt vissa semesterhändelser. I allmänhet brukar kommuner med enbostadshu-sområden förbruka mer vatten under sommaren per capita än andra. Fördelar med att planeranya flerbostadsområden som ett mer hållbart alternativ till enbostadshusområden diskuteradesi kontexten av befolkningstillväxt och klimatförändringar.