Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

Satellite remote sensing (RS) is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e.g., intra-urban). In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolution-enhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well in detail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics

The voices of experience: teacher educators articulate their thoughts and concerns about current and future education policy and practice

This research addressed the neglect of teacher educators’ voices in the discourses surrounding teaching and teacher education. In this study, five Queensland university teacher educators articulated, through the narratives of their professional lived experience, their thoughts and concerns about current and future education policy and practice. Evidence of the neglect of teacher educator voices was found by a search of the literature on teaching and teacher education. A number of reports were found that scrutinised classroom teaching and teacher education in Australia and the United Kingdom and across Europe. These reports make comment on and recommendations about the current and future practice in teacher education but do not indicate the ways in which teacher educators have or have not been involved in the discussion of and preparation of the reports. Narrative Inquiry (NI) was used as both methodology and method in the study. Multiple conversations between the researcher and each participant led to the final five co-constructed narratives of the participants. The narratives told of the professional lived experience of the participants and how that experience has led them to articulate their thoughts and concerns about education today and in the future. Five common themes emerged from the analysis of the narratives: the way in which initial teacher education (ITE) students are recruited; the influence of government policy on the ways in which the curriculum and testing are delivered in schools; the qualifications and experience of teacher educators; the need for a closer working relationship between schools and universities; and the process of transition from teaching in school to teaching in the university. These themes formed the basis of how the researcher made meaning of the participants’ narratives. The nature of NI is such that the researcher becomes a partner in the research and this results in participation in a personal learning journey that leads to the articulation of the researcher’s own lived experience. In the thesis, my learning journey is evidenced in the prologue and the epilogue. There are also personal reflections at points throughout the study. The study adds to our knowledge and understanding of the theoretical and methodological underpinnings of NI. A new dimension, the generative space, was added to enhance the understanding of how the commonplaces of NI work together to enable deep reflection on the past, present and possible future lived experience. Policy and practice in teacher education were scrutinised through the lenses of the teacher educators’ narratives and led to the development of the recommendations regarding the role and status of teacher educators, made in the final chapter. In essence, this study has evolved into being about the things that matter to the five participants. Each is a highly qualified and experienced professional expressing the positives, negatives and frustrations that they experience in their current professional lives. They are five individuals with a passion for education as a whole and for the education of teachers in particular

Population estimation mining from satellite imagery

The collection of census data is an important task with respect to providing support for decision makers. However, the collection of census data is also resource intensive. This is especially the case in areas which feature poor communication and transport networks. In this thesis a number of methods are proposed for collecting census data by applying prediction techniques to relevant satellite imagery. The test site for the work is a collection of villages lying some 300km to the northwest of Addis Ababa in Ethiopia. The idea is to build a predictor that can label households according to “family” size. To this end training data has been obtained by collecting “on ground” census data and matching this up with satellite imagery. The fundamental idea is to segment satellite images so as to obtain satellite sub-images describing individual households and representing these segmentations using a number of proposed representations: graph-based, histogram based and texture based. By pairing each represented household with the collated census data, namely family size, a predictor can be constructed to predict household sizes according to the nature of each representation. The generated predictor can then be used to provide a quick and easy mechanism for the approximate collection of census data that does not require significant resource