Enhanced processing of SPOT multispectral satellite imagery for environmental monitoring and modelling

The Taita Hills in southeastern Kenya form the northernmost part of Africa’s Eastern Arc Mountains, which have been identified by Conservation International as one of the top ten biodiversity hotspots on Earth. As with many areas of the developing world, over recent decades the Taita Hills have experienced significant population growth leading to associated major changes in land use and land cover (LULC), as well as escalating land degradation, particularly soil erosion. Multi-temporal medium resolution multispectral optical satellite data, such as imagery from the SPOT HRV, HRVIR, and HRG sensors, provides a valuable source of information for environmental monitoring and modelling at a landscape level at local and regional scales. However, utilization of multi-temporal SPOT data in quantitative remote sensing studies requires the removal of atmospheric effects and the derivation of surface reflectance factor. Furthermore, for areas of rugged terrain, such as the Taita Hills, topographic correction is necessary to derive comparable reflectance throughout a SPOT scene. Reliable monitoring of LULC change over time and modelling of land degradation and human population distribution and abundance are of crucial importance to sustainable development, natural resource management, biodiversity conservation, and understanding and mitigating climate change and its impacts. The main purpose of this thesis was to develop and validate enhanced processing of SPOT satellite imagery for use in environmental monitoring and modelling at a landscape level, in regions of the developing world with limited ancillary data availability. The Taita Hills formed the application study site, whilst the Helsinki metropolitan region was used as a control site for validation and assessment of the applied atmospheric correction techniques, where multiangular reflectance field measurements were taken and where horizontal visibility meteorological data concurrent with image acquisition were available. The proposed historical empirical line method (HELM) for absolute atmospheric correction was found to be the only applied technique that could derive surface reflectance factor within an RMSE of < 0.02 ps in the SPOT visible and near-infrared bands; an accuracy level identified as a benchmark for successful atmospheric correction. A multi-scale segmentation/object relationship modelling (MSS/ORM) approach was applied to map LULC in the Taita Hills from the multi-temporal SPOT imagery. This object-based procedure was shown to derive significant improvements over a uni-scale maximum-likelihood technique. The derived LULC data was used in combination with low cost GIS geospatial layers describing elevation, rainfall and soil type, to model degradation in the Taita Hills in the form of potential soil loss, utilizing the simple universal soil loss equation (USLE). Furthermore, human population distribution and abundance were modelled with satisfactory results using only SPOT and GIS derived data and non-Gaussian predictive modelling techniques. The SPOT derived LULC data was found to be unnecessary as a predictor because the first and second order image texture measurements had greater power to explain variation in dwelling unit occurrence and abundance. The ability of the procedures to be implemented locally in the developing world using low-cost or freely available data and software was considered. The techniques discussed in this thesis are considered equally applicable to other medium- and high-resolution optical satellite imagery, as well the utilized SPOT data.

Mining Sequential Data – in Search of Segmental Structures

Segmentation is a data mining technique yielding simplified representations of sequences of ordered points. A sequence is divided into some number of homogeneous blocks, and all points within a segment are described by a single value. The focus in this thesis is on piecewise-constant segments, where the most likely description for each segment and the most likely segmentation into some number of blocks can be computed efficiently. Representing sequences as segmentations is useful in, e.g., storage and indexing tasks in sequence databases, and segmentation can be used as a tool in learning about the structure of a given sequence. The discussion in this thesis begins with basic questions related to segmentation analysis, such as choosing the number of segments, and evaluating the obtained segmentations. Standard model selection techniques are shown to perform well for the sequence segmentation task. Segmentation evaluation is proposed with respect to a known segmentation structure. Applying segmentation on certain features of a sequence is shown to yield segmentations that are significantly close to the known underlying structure. Two extensions to the basic segmentation framework are introduced: unimodal segmentation and basis segmentation. The former is concerned with segmentations where the segment descriptions first increase and then decrease, and the latter with the interplay between different dimensions and segments in the sequence. These problems are formally defined and algorithms for solving them are provided and analyzed. Practical applications for segmentation techniques include time series and data stream analysis, text analysis, and biological sequence analysis. In this thesis segmentation applications are demonstrated in analyzing genomic sequences.

Affektiivisuuden laskennallinen määritteleminen

One of the most tangled fields of research is the field of defining and modeling affective concepts, i. e. concepts regarding emotions and feelings. The subject can be approached from many disciplines. The main problem is lack of generally approved definitions. However, e.g. linguists have recently started to check the consistency of their theories with the help of computer simulations. Definitions of affective concepts are needed for performing similar simulations in behavioral sciences. In this thesis, preliminary computational definitions of affects for a simple utility-maximizing agent are given. The definitions have been produced by synthetizing ideas from theories from several fields of research. The class of affects is defined as a superclass of emotions and feelings. Affect is defined as a process, in which a change in an agent's expected utility causes a bodily change. If the process is currently under the attention of the agent (i.e. the agent is conscious of it), the process is a feeling. If it is not, but can in principle be taken into attention (i.e. it is preconscious), the process is an emotion. Thus, affects do not presuppose consciousness, but emotions and affects do. Affects directed at unexpected materialized (i.e. past) events are delight and fright. Delight is the consequence of an unexpected positive event and fright is the consequence of an unexpected negative event. Affects directed at expected materialized (i.e. past) events are happiness (expected positive event materialized), disappointment (expected positive event did not materialize), sadness (expected negative event materialized) and relief (expected negative event did not materialize). Affects directed at expected unrealized (i.e. future) events are fear and hope. Some other affects can be defined as directed towards originators of the events. The affect classification has also been implemented as a computer program, the purpose of which is to ensure the coherence of the definitions and also to illustrate the capabilities of the model. The exact content of bodily changes associated with specific affects is not considered relevant from the point of view of the logical structure of affective phenomena. The utility function need also not be defined, since the target of examination is only its dynamics.

Functional imaging of peripheral vision and dorsal stream function in the human cerebral cortex

Visual information processing in brain proceeds in both serial and parallel fashion throughout various functionally distinct hierarchically organised cortical areas. Feedforward signals from retina and hierarchically lower cortical levels are the major activators of visual neurons, but top-down and feedback signals from higher level cortical areas have a modulating effect on neural processing. My work concentrates on visual encoding in hierarchically low level cortical visual areas in human brain and examines neural processing especially in cortical representation of visual field periphery. I use magnetoencephalography and functional magnetic resonance imaging to measure neuromagnetic and hemodynamic responses during visual stimulation and oculomotor and cognitive tasks from healthy volunteers. My thesis comprises six publications. Visual cortex forms a great challenge for modeling of neuromagnetic sources. My work shows that a priori information of source locations are needed for modeling of neuromagnetic sources in visual cortex. In addition, my work examines other potential confounding factors in vision studies such as light scatter inside the eye which may result in erroneous responses in cortex outside the representation of stimulated region, and eye movements and attention. I mapped cortical representations of peripheral visual field and identified a putative human homologue of functional area V6 of the macaque in the posterior bank of parieto-occipital sulcus. My work shows that human V6 activates during eye-movements and that it responds to visual motion at short latencies. These findings suggest that human V6, like its monkey homologue, is related to fast processing of visual stimuli and visually guided movements. I demonstrate that peripheral vision is functionally related to eye-movements and connected to rapid stream of functional areas that process visual motion. In addition, my work shows two different forms of top-down modulation of neural processing in the hierachically lowest cortical levels; one that is related to dorsal stream activation and may reflect motor processing or resetting signals that prepare visual cortex for change in the environment and another local signal enhancement at the attended region that reflects local feed-back signal and may perceptionally increase the stimulus saliency.

Cyclosporine population pharmacokinetics in pediatric renal transplant recipients

Cyclosporine is an immunosuppressant drug with a narrow therapeutic index and large variability in pharmacokinetics. To improve cyclosporine dose individualization in children, we used population pharmacokinetic modeling to study the effects of developmental, clinical, and genetic factors on cyclosporine pharmacokinetics in altogether 176 subjects (age range: 0.36–20.2 years) before and up to 16 years after renal transplantation. Pre-transplantation test doses of cyclosporine were given intravenously (3 mg/kg) and orally (10 mg/kg), on separate occasions, followed by blood sampling for 24 hours (n=175). After transplantation, in a total of 137 patients, cyclosporine concentration was quantified at trough, two hours post-dose, or with dose-interval curves. One-hundred-four of the studied patients were genotyped for 17 putatively functionally significant sequence variations in the ABCB1, SLCO1B1, ABCC2, CYP3A4, CYP3A5, and NR1I2 genes. Pharmacokinetic modeling was performed with the nonlinear mixed effects modeling computer program, NONMEM. A 3-compartment population pharmacokinetic model with first order absorption without lag-time was used to describe the data. The most important covariate affecting systemic clearance and distribution volume was allometrically scaled body weight i.e. body weight**3/4 for clearance and absolute body weight for volume of distribution. The clearance adjusted by absolute body weight declined with age and pre-pubertal children (< 8 years) had an approximately 25% higher clearance/body weight (L/h/kg) than did older children. Adjustment of clearance for allometric body weight removed its relationship to age after the first year of life. This finding is consistent with a gradual reduction in relative liver size towards adult values, and a relatively constant CYP3A content in the liver from about 6–12 months of age to adulthood. The other significant covariates affecting cyclosporine clearance and volume of distribution were hematocrit, plasma cholesterol, and serum creatinine, explaining up to 20%–30% of inter-individual differences before transplantation. After transplantation, their predictive role was smaller, as the variations in hematocrit, plasma cholesterol, and serum creatinine were also smaller. Before transplantation, no clinical or demographic covariates were found to affect oral bioavailability, and no systematic age-related changes in oral bioavailability were observed. After transplantation, older children receiving cyclosporine twice daily as the gelatine capsule microemulsion formulation had an about 1.25–1.3 times higher bioavailability than did the younger children receiving the liquid microemulsion formulation thrice daily. Moreover, cyclosporine oral bioavailability increased over 1.5-fold in the first month after transplantation, returning thereafter gradually to its initial value in 1–1.5 years. The largest cyclosporine doses were administered in the first 3–6 months after transplantation, and thereafter the single doses of cyclosporine were often smaller than 3 mg/kg. Thus, the results suggest that cyclosporine displays dose-dependent, saturable pre-systemic metabolism even at low single doses, whereas complete saturation of CYP3A4 and MDR1 (P-glycoprotein) renders cyclosporine pharmacokinetics dose-linear at higher doses. No significant associations were found between genetic polymorphisms and cyclosporine pharmacokinetics before transplantation in the whole population for which genetic data was available (n=104). However, in children older than eight years (n=22), heterozygous and homozygous carriers of the ABCB1 c.2677T or c.1236T alleles had an about 1.3 times or 1.6 times higher oral bioavailability, respectively, than did non-carriers. After transplantation, none of the ABCB1 SNPs or any other SNPs were found to be associated with cyclosporine clearance or oral bioavailability in the whole population, in the patients older than eight years, or in the patients younger than eight years. In the whole population, in those patients carrying the NR1I2 g.-25385C–g.-24381A–g.-205_-200GAGAAG–g.7635G–g.8055C haplotype, however, the bioavailability of cyclosporine was about one tenth lower, per allele, than in non-carriers. This effect was significant also in a subgroup of patients older than eight years. Furthermore, in patients carrying the NR1I2 g.-25385C–g.-24381A–g.-205_-200GAGAAG–g.7635G–g.8055T haplotype, the bioavailability was almost one fifth higher, per allele, than in non-carriers. It may be possible to improve individualization of cyclosporine dosing in children by accounting for the effects of developmental factors (body weight, liver size), time after transplantation, and cyclosporine dosing frequency/formulation. Further studies are required on the predictive value of genotyping for individualization of cyclosporine dosing in children.

Towards the Use of Radar Winds in Numerical Weather Prediction

Numerical weather prediction (NWP) models provide the basis for weather forecasting by simulating the evolution of the atmospheric state. A good forecast requires that the initial state of the atmosphere is known accurately, and that the NWP model is a realistic representation of the atmosphere. Data assimilation methods are used to produce initial conditions for NWP models. The NWP model background field, typically a short-range forecast, is updated with observations in a statistically optimal way. The objective in this thesis has been to develope methods in order to allow data assimilation of Doppler radar radial wind observations. The work has been carried out in the High Resolution Limited Area Model (HIRLAM) 3-dimensional variational data assimilation framework. Observation modelling is a key element in exploiting indirect observations of the model variables. In the radar radial wind observation modelling, the vertical model wind profile is interpolated to the observation location, and the projection of the model wind vector on the radar pulse path is calculated. The vertical broadening of the radar pulse volume, and the bending of the radar pulse path due to atmospheric conditions are taken into account. Radar radial wind observations are modelled within observation errors which consist of instrumental, modelling, and representativeness errors. Systematic and random modelling errors can be minimized by accurate observation modelling. The impact of the random part of the instrumental and representativeness errors can be decreased by calculating spatial averages from the raw observations. Model experiments indicate that the spatial averaging clearly improves the fit of the radial wind observations to the model in terms of observation minus model background (OmB) standard deviation. Monitoring the quality of the observations is an important aspect, especially when a new observation type is introduced into a data assimilation system. Calculating the bias for radial wind observations in a conventional way can result in zero even in case there are systematic differences in the wind speed and/or direction. A bias estimation method designed for this observation type is introduced in the thesis. Doppler radar radial wind observation modelling, together with the bias estimation method, enables the exploitation of the radial wind observations also for NWP model validation. The one-month model experiments performed with the HIRLAM model versions differing only in a surface stress parameterization detail indicate that the use of radar wind observations in NWP model validation is very beneficial.

Geant4 Hadronic Cascade Models and CMS Data Analysis : Computational Challenges in the LHC era

This work belongs to the field of computational high-energy physics (HEP). The key methods used in this thesis work to meet the challenges raised by the Large Hadron Collider (LHC) era experiments are object-orientation with software engineering, Monte Carlo simulation, the computer technology of clusters, and artificial neural networks. The first aspect discussed is the development of hadronic cascade models, used for the accurate simulation of medium-energy hadron-nucleus reactions, up to 10 GeV. These models are typically needed in hadronic calorimeter studies and in the estimation of radiation backgrounds. Various applications outside HEP include the medical field (such as hadron treatment simulations), space science (satellite shielding), and nuclear physics (spallation studies). Validation results are presented for several significant improvements released in Geant4 simulation tool, and the significance of the new models for computing in the Large Hadron Collider era is estimated. In particular, we estimate the ability of the Bertini cascade to simulate Compact Muon Solenoid (CMS) hadron calorimeter HCAL. LHC test beam activity has a tightly coupled cycle of simulation-to-data analysis. Typically, a Geant4 computer experiment is used to understand test beam measurements. Thus an another aspect of this thesis is a description of studies related to developing new CMS H2 test beam data analysis tools and performing data analysis on the basis of CMS Monte Carlo events. These events have been simulated in detail using Geant4 physics models, full CMS detector description, and event reconstruction. Using the ROOT data analysis framework we have developed an offline ANN-based approach to tag b-jets associated with heavy neutral Higgs particles, and we show that this kind of NN methodology can be successfully used to separate the Higgs signal from the background in the CMS experiment.

Investigations of planetary boundary layer processes and particle formation in the atmosphere of planet Mars

The planet Mars is the Earth's neighbour in the Solar System. Planetary research stems from a fundamental need to explore our surroundings, typical for mankind. Manned missions to Mars are already being planned, and understanding the environment to which the astronauts would be exposed is of utmost importance for a successful mission. Information of the Martian environment given by models is already now used in designing the landers and orbiters sent to the red planet. In particular, studies of the Martian atmosphere are crucial for instrument design, entry, descent and landing system design, landing site selection, and aerobraking calculations. Research of planetary atmospheres can also contribute to atmospheric studies of the Earth via model testing and development of parameterizations: even after decades of modeling the Earth's atmosphere, we are still far from perfect weather predictions. On a global level, Mars has also been experiencing climate change. The aerosol effect is one of the largest unknowns in the present terrestrial climate change studies, and the role of aerosol particles in any climate is fundamental: studies of climate variations on another planet can help us better understand our own global change. In this thesis I have used an atmospheric column model for Mars to study the behaviour of the lowest layer of the atmosphere, the planetary boundary layer (PBL), and I have developed nucleation (particle formation) models for Martian conditions. The models were also coupled to study, for example, fog formation in the PBL. The PBL is perhaps the most significant part of the atmosphere for landers and humans, since we live in it and experience its state, for example, as gusty winds, nightfrost, and fogs. However, PBL modelling in weather prediction models is still a difficult task. Mars hosts a variety of cloud types, mainly composed of water ice particles, but also CO2 ice clouds form in the very cold polar night and at high altitudes elsewhere. Nucleation is the first step in particle formation, and always includes a phase transition. Cloud crystals on Mars form from vapour to ice on ubiquitous, suspended dust particles. Clouds on Mars have a small radiative effect in the present climate, but it may have been more important in the past. This thesis represents an attempt to model the Martian atmosphere at the smallest scales with high resolution. The models used and developed during the course of the research are useful tools for developing and testing parameterizations for larger-scale models all the way up to global climate models, since the small-scale models can describe processes that in the large-scale models are reduced to subgrid (not explicitly resolved) scale.

Local numerical modelling of magnetoconvection and turbulence - implications for mean-field theories

During the last decades mean-field models, in which large-scale magnetic fields and differential rotation arise due to the interaction of rotation and small-scale turbulence, have been enormously successful in reproducing many of the observed features of the Sun. In the meantime, new observational techniques, most prominently helioseismology, have yielded invaluable information about the interior of the Sun. This new information, however, imposes strict conditions on mean-field models. Moreover, most of the present mean-field models depend on knowledge of the small-scale turbulent effects that give rise to the large-scale phenomena. In many mean-field models these effects are prescribed in ad hoc fashion due to the lack of this knowledge. With large enough computers it would be possible to solve the MHD equations numerically under stellar conditions. However, the problem is too large by several orders of magnitude for the present day and any foreseeable computers. In our view, a combination of mean-field modelling and local 3D calculations is a more fruitful approach. The large-scale structures are well described by global mean-field models, provided that the small-scale turbulent effects are adequately parameterized. The latter can be achieved by performing local calculations which allow a much higher spatial resolution than what can be achieved in direct global calculations. In the present dissertation three aspects of mean-field theories and models of stars are studied. Firstly, the basic assumptions of different mean-field theories are tested with calculations of isotropic turbulence and hydrodynamic, as well as magnetohydrodynamic, convection. Secondly, even if the mean-field theory is unable to give the required transport coefficients from first principles, it is in some cases possible to compute these coefficients from 3D numerical models in a parameter range that can be considered to describe the main physical effects in an adequately realistic manner. In the present study, the Reynolds stresses and turbulent heat transport, responsible for the generation of differential rotation, were determined along the mixing length relations describing convection in stellar structure models. Furthermore, the alpha-effect and magnetic pumping due to turbulent convection in the rapid rotation regime were studied. The third area of the present study is to apply the local results in mean-field models, which task we start to undertake by applying the results concerning the alpha-effect and turbulent pumping in mean-field models describing the solar dynamo.

Modeling of Surface UV Radiation Using Satellite Data

Solar UV radiation is harmful for life on planet Earth, but fortunately the atmospheric oxygen and ozone absorb almost entirely the most energetic UVC radiation photons. However, part of the UVB radiation and much of the UVA radiation reaches the surface of the Earth, and affect human health, environment, materials and drive atmospheric and aquatic photochemical processes. In order to quantify these effects and processes there is a need for ground-based UV measurements and radiative transfer modeling to estimate the amounts of UV radiation reaching the biosphere. Satellite measurements with their near-global spatial coverage and long-term data conti-nuity offer an attractive option for estimation of the surface UV radiation. This work focuses on radiative transfer theory based methods used for estimation of the UV radiation reaching the surface of the Earth. The objectives of the thesis were to implement the surface UV algorithm originally developed at NASA Goddard Space Flight Center for estimation of the surface UV irradiance from the meas-urements of the Dutch-Finnish built Ozone Monitoring Instrument (OMI), to improve the original surface UV algorithm especially in relation with snow cover, to validate the OMI-derived daily surface UV doses against ground-based measurements, and to demonstrate how the satellite-derived surface UV data can be used to study the effects of the UV radiation. The thesis consists of seven original papers and a summary. The summary includes an introduction of the OMI instrument, a review of the methods used for modeling of the surface UV using satellite data as well as the con-clusions of the main results of the original papers. The first two papers describe the algorithm used for estimation of the surface UV amounts from the OMI measurements as well as the unique Very Fast Delivery processing system developed for processing of the OMI data received at the Sodankylä satellite data centre. The third and the fourth papers present algorithm improvements related to the surface UV albedo of the snow-covered land. Fifth paper presents the results of the comparison of the OMI-derived daily erythemal doses with those calculated from the ground-based measurement data. It gives an estimate of the expected accuracy of the OMI-derived sur-face UV doses for various atmospheric and other conditions, and discusses the causes of the differences between the satellite-derived and ground-based data. The last two papers demonstrate the use of the satellite-derived sur-face UV data. Sixth paper presents an assessment of the photochemical decomposition rates in aquatic environment. Seventh paper presents use of satellite-derived daily surface UV doses for planning of the outdoor material weathering tests.

Designing a blended learning model for primary school language learning

In Finland, there is a desperate need for flexible, reliable and functional multi-e-learning settings for pupils aged 11-13. Southern Finland has several ongoing e-learning projects, but none that develop a multiple setting, with learning and teaching occurring between more than two schools. In 2006, internet connections were not broadband and data transfer was mainly audio data. Connections and technical problems occurred, which were an obstacle to multi-e-learning. Internet connections today enable web-based learning in major parts of
Lapland and by 2015, broadband will reach even the remotest villages up north. Therefore, it is important to research the possibilities of multi-e-learning and to build collaborative, learner-centred, versatile network models for primary school-aged pupils. The resulting model will facilitate distance learning to extend education to rural, sparsely populated areas, and it will give a model of using mobile devices in language portfolios. This will promote regional equality and prevent exclusion. Working with portfolios provides the opportunity to develop mobility from a pedagogical point of view. It is important to study the pros and cons of mobile devices in producing artefacts on portfolios in e-learning and language learning settings.
The current study represents a design-based research approach. The design research approach includes two important aspects concerning the current research: ‘a teacher as researcher’ aspect, which means there is the possibility to be strongly involved in developing processes and an obstacle-aspect, which means that problems while developing, are seen as a
promoter in evolving the designed model, as apposed to negative results.

Designing a blended learning model for primary school language learning

In Finland, there is a desperate need for flexible, reliable and functional multi-e-learning settings for pupils aged 11-13. Southern Finland has several ongoing e-learning projects, but none that develop a multiple setting, with learning and teaching occurring between more than two schools. In 2006, internet connections were not broadband and data transfer was mainly audio data. Connections and technical problems occurred, which were an obstacle to multi-e-learning. Internet connections today enable web-based learning in major parts of Lapland and by 2015, broadband will reach even the remotest villages up north. Therefore, it is important to research the possibilities of multi-e-learning and to build collaborative, learner-centred, versatile network models for primary school-aged pupils. The resulting model will facilitate distance learning to extend education to rural, sparsely populated areas, and it will give a model of using mobile devices in language portfolios. This will promote regional equality and prevent exclusion. Working with portfolios provides the opportunity to develop mobility from a pedagogical point of view. It is important to study the pros and cons of mobile devices in producing artefacts on portfolios in e-learning and language learning settings. The current study represents a design-based research approach. The design research approach includes two important aspects concerning the current research: ‘a teacher as researcher’ aspect, which means there is the possibility to be strongly involved in developing processes and an obstacle-aspect, which means that problems while developing, are seen as a promoter in evolving the designed model, as apposed to negative results.

Perspectives on knowledge creating inquiry in higher education

Higher education is faced with the challenge of strengthening students competencies for the constantly evolving technology-mediated practices of knowledge work. The knowledge creation approach to learning (Paavola et al., 2004; Hakkarainen et al., 2004) provides a theoretical tool to address learning and teaching organized around complex problems and the development of shared knowledge objects, such as reports, products, and new practices. As in professional work practices, it appears necessary to design sufficient open-endedness and complexity for students teamwork in order to generate unpredictable and both practically and epistemologically challenging situations. The studies of the thesis examine what kinds of practices are observed when student teams engage in knowledge creating inquiry processes, how the students themselves perceive the process, and how to facilitate inquiry with technology-mediation, tutoring, and pedagogical models. Overall, 20 student teams collaboration processes and productions were investigated in detail. This collaboration took place in teams or small groups of 3-6 students from multiple domain backgrounds. Two pedagogical models were employed to provide heuristic guidance for the inquiry processes: the progressive inquiry model and the distributed project model. Design-based research methodology was employed in combination with case study as the research design. Database materials from the courses virtual learning environment constituted the main body of data, with additional data from students self-reflections and student and teacher interviews. Study I examined the role of technology mediation and tutoring in directing students knowledge production in a progressive inquiry process. The research investigated how the scale of scaffolding related to the nature of knowledge produced and the deepening of the question explanation process. In Study II, the metaskills of knowledge-creating inquiry were explored as a challenge for higher education: metaskills refers to the individual, collective, and object-centered aspects of monitoring collaborative inquiry. Study III examined the design of two courses and how the elaboration of shared objects unfolded based on the two pedagogical models. Study IV examined how the arranged concept-development project for external customers promoted practices of distributed, partially virtual, project work, and how the students coped with the knowledge creation challenge. Overall, important indicators of knowledge creating inquiry were the following: new versions of knowledge objects and artifacts demonstrated a deepening inquiry process; and the various productions were co-created through iterations of negotiations, drafting, and versioning by the team members. Students faced challenges of establishing a collective commitment, devising practices to co-author and advance their reports, dealing with confusion, and managing culturally diverse teams. The progressive inquiry model, together with tutoring and technology, facilitated asking questions, generating explanations, and refocusing lines of inquiry. The involvement of the customers was observed to provide a strong motivation for the teams. On the evidence, providing team-specific guidance, exposing students to models of scientific argumentation and expert work practices, and furnishing templates for the intended products appear to be fruitful ways to enhance inquiry processes. At the institutional level, educators do well to explore ways of developing collaboration with external customers, public organizations or companies, and between educational units in order to enhance educational practices of knowledge creating inquiry.