Thèses sur le sujet « Object Use »

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2007.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 139-146).
This thesis presents the Object Schema Model (OSM) for grounded language interaction. Dynamic representations of objects are used as the central point of coordination between actions, sensations, planning, and language use. Objects are modeled as object schemas -- sets of multimodal, object-directed behavior processes -- each of which can make predictions, take actions, and collate sensations, in the modalities of touch, vision, and motor control. This process-centered view allows the system to respond continuously to real-world activity, while still viewing objects as stabilized representations for planning and speech interaction. The model can be described from four perspectives, each organizing and manipulating behavior processes in a different way. The first perspective views behavior processes like thread objects, running concurrently to carry out their respective functions. The second perspective organizes the behavior processes into object schemas. The third perspective organizes the behavior processes into plan hierarchies to coordinate actions. The fourth perspective creates new behavior processes in response to language input.
(cont.) Results from interactions with objects are used to update the object schemas, which then influence subsequent plans and actions. A continuous planning algorithm examines the current object schemas to choose between candidate processes according to a set of primary motivations, such as responding to collisions, exploring objects, and interacting with the human. An instance of the model has been implemented using a physical robotic manipulator. The implemented system is able to interpret basic speech acts that relate to perception of, and actions upon, objects in the robot's physical environment.
by Kai-yuh Hsiao.
Ph.D.

Recent research suggests that by 4 months of age infants are able to individuate objects using form features, such as shape and size, but surface features, such as pattern and color, are not used until later in the first year (Wilcox, 1999). The current study sought to investigate two possible explanations for this developmental hierarchy. The visual maturation hypothesis suggests that the order in which infants use features to individuate objects corresponds to the order in which they are most readily processed by the developing visual system. A second hypothesis, the information processing biases hypothesis, suggests that infants are biased to attend to form features because form features provide information that is relevant to reasoning about object interactions. One way to test these hypotheses is to investigate infants' ability to individuate objects based on luminance. Luminance is detected at birth, so, according to the visual maturation hypothesis, luminance, like shape and size, will be used to individuate objects early in the first year. However, luminance is a surface property, so according to the information processing biases hypothesis, luminance, like pattern and color, will be used to individuate objects late in the first year. In the current study, 7-month-old (Experiment 1) and 11-month-old (Experiment 2) infants' use of luminance information in an object individuation task was investigated. The narrow-screen event-monitoring paradigm developed by Wilcox and Baillargeon (1998a) was used. Infants saw an event in which a ball moved behind a screen and a second ball emerged from behind the opposite edge of the screen. In one condition, the balls were identical, suggesting the presence of one object (same-luminance condition), and in another condition, the balls differed in luminance, suggesting the presence of two objects (different-luminance condition). The screen was either too narrow (narrow-screen event) or sufficiently wide (wide-screen event) to occlude two objects simultaneously. Seven-month-olds looked equally at each event, whereas 11.5-month-old's looked longer at the narrow-screen event in the different-luminance condition. These results suggest that 11.5-month-olds, but not 7.5-month-olds used luminance information to conclude that two distinct objects were involved in the event, thus supporting the information processing biases hypothesis.

How do infants initially determine whether a novel object word labels a specific individual (e.g. Madonna) or an instance of a category (e.g., a person)? The research in this dissertation tested the hypothesis that infants assume words for objects from some categories (e.g., people) label individuals (are proper names) but words for objects from other categories (e.g., artifacts) label instances of the category (are count nouns). This assumption could help infants to identify proper names and count nouns in their language, and thereby facilitate the learning of the linguistic proper name/count noun distinction. In a preferential looking task, 16- and 17-month-olds heard a novel word for a target person (a face) or artifact, and their willingness to generalize the word to a non-target object was assessed. In Experiment 1, infants restricted the word to the target object when it was paired with a non-target object from a different category, providing evidence that infants can learn a novel word for the target object in this task. In Experiment 2, infants restricted the word to the target object when both the target and non-target objects were people, but not when they were artifacts from the same category. This finding is consistent with the hypothesis that infants interpret words for people as proper names and words for artifacts as count nouns. In Experiment 3, infants were asked to find the referent of a second novel label in a task identical to Experiment 2. Here, infants restricted their looking to the non-target object when the objects were people, but not when they were artifacts. In Experiment 4, infants did not restrict the novel label to a person (a face) when it was inverted. This result provides evidence that infants’ tendency in Experiment 2 to restrict a label to a particular person was not simply due to the greater perceptual complexity of faces. Together, the findings reveal that infants interpret words for people and words for artifacts differently, raising the possibility that object category distinctions help infants to identify proper names and count nouns in their language and to learn how they are expressed linguistically.

Object recognition has been one of the main areas of research into computer vision in the last 20-30 years. Until recently most of this research has been performed on scenes taken using static monocular, binocular or even trinocular cameras. It is believed, however, that by adding the ability to move the look point and concentrate on a region of interest a more robust and efficient method of vision can be achieved. Recent studies into the ability to provide human-like vision systems for a more active approach to vision have lead to the development of a number of robot controlled vision systems. In this thesis the development of one such system at the University of Surrey, the stereo robot head "Getafix" is described. The design, construction and development of the head and its control system have been undertaken as part of this project with the aim of improving current vision tasks, in particular, that of object recognition. In this thesis the design of the control systems, kinematics and control software of the stereo robot head will be discussed. A number of simple commissioning experiments are also shown, using the concepts of the robot control developed herein. Camera lens control and calibration is also described. A review of classical primitive based object recognition systems is given and the development of a novel generic cylindrical object recognition strategy is shown. The use of this knowledge source is demonstrated with other vision processes of colour and stereo. The work on the cylinder recognition strategy and the stereo robot head are finally combined within an active vision framework. A purposive active vision strategy is used to detect cylindrical structures, that would otherwise be undetectable by the cylindrical object detection algorithm alone.

This work proposes a system that utilizes both infrared and visual imagery to create a more robust object detection and classification system. The system consists of two main parts: a moving object detector and a target classifier. The first stage detects moving objects in visible and infrared spectrum using background subtraction based on Gaussian Mixture Models. Low-level fusion is performed to combine the foreground regions in the respective domain. For the second stage, a Convolutional Neural Network (CNN), pre-trained on the ImageNet dataset is used to classify the detected targets into one of the pre-defined classes; human and vehicle. The performance of the proposed object detector is evaluated using multiple video streams recorded in different areas and under various weather conditions, which form a broad basis for testing the suggested method. The accuracy of the classifier is evaluated from experimentally generated images from the moving object detection stage supplemented with publicly available CIFAR-10 and CIFAR-100 datasets. The low-level fusion method shows to be more effective than using either domain separately in terms of detection results.

Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet

Gibbons (Hylobatidae), taxonomically apes, have been largely ignored in cognitive research. This is surprising given their unique phylogenetic position, being intermediate between the monkeys and great apes, and the available diversity of extant species. They are therefore, ideally placed to study the evolution of cognitive abilities in the hominoid line; they offer the opportunity to determine how the mental capacities of primates have changed through the transition from monkey to ape. This research aimed to begin to fill the void in our knowledge regarding the cognitive abilities of this family through investigations of their object manipulation and tool-use skills, relating the findings to the evolution of the hominoid brain. In a raking-in task, where the gibbons were presented with a tool that could be used to draw in an out-of-reach food item, these apes evidenced potentially insightful comprehension of object relationships when the tool and goal object were presented in direct alignment. They also proficiently used a rake to retrieve a reward while avoiding a trap that presented an impediment to goal attainment; however, in general, they required a period of learning to perform consistently. Once the necessary relationships between the tool and goal object were not physically situated in the task layout, as in true tool-use manipulation, the gibbons performed poorly. In a raking-in task where the necessary orientation for success had to be produced by the subject, no individual evidenced foresightful comprehension of the required action. There was some suggestion of learning the correct behaviour through associative processes. This finding was also supported by evidence from dipping experiments where the gibbons were provided with a transparent box containing a liquid reward and sticks that could be used as tools to access it. No individual developed dipping behaviour. The gibbons therefore, performed well on tasks when the salient relationships between tool and goal were directly perceivable. Once they became responsible for producing that relationship, performance was poor. When the necessary orientation between the tool and goal was not provided by the experimenter, the gibbons evidenced low motivation to manipulate the objects. Given the gibbons’ requirement for direct visual feedback to comprehend the causal interactions between objects, this likely hindered their learning process. Failure therefore on the true tool-use tasks may not represent a particular cognitive limitation in these apes. A consistent finding was that the hoolock gibbons (Bunopithecus) were the most attentive and effective of the four gibbon genera. This is potentially due to the more variable natural environment experienced by these apes, driving selection for greater exploratory tendencies and flexibility of behaviour. The findings from this, and other work on primate cognition, suggest that contrary to propositions put forward by proponents of modular accounts of hominid brain evolution, the cognitive architecture of non-human primates contains neural mechanisms capable of processing technical information that may not be completely encapsulated. Suggestions that no non-human possesses specialised cognitive machinery for understanding objects as tools are also challenged.

In the present study, we tested whether prior experience of an object allows infants to segregate a display when competing cues operate against this interpretation. 4.5-month-olds were shown three exemplars of a novel object. Infants were familiarized with a test display consisting of a new exemplar of the novel object abutted against a complementary object. The infants then viewed one of two events in which 1)the objects moved together as a single entity or 2)moved independently indicating their separation. Infants looked longer at the move-together event (M=30.35 sec) than at the move-apart event (M=14.72 sec),t(17)=3.41, p.003 indicating that the novel object was segregated from its complement. Infants in a control experiment who were not familiarized with the novel object, showed no differences in looking times, (M(Move-together)=17.76 sec, M(Move-apart)=17.92 sec),t(16)=0.04, p≤.97. For the first time we show that a small amount of prior experience can exert an effect that overpowers other cues for grouping. Furthermore, 4.5- month-old infants can use a newly learned object for scene segregation despite the fact that the grouping cues in the test stimulus operate against this interpretation. Finally, we show that object learning is robust enough to transfer from 3D presentation with real objects to a video display.

Popular Object Oriented size metrics and estimation methods are examined. A case study is conducted. Five of the methods (&ldquo
LOC&rdquo
, &ldquo
OOPS&rdquo
, &ldquo
Use Case Points Method&rdquo
, &ldquo
J.Kammelar&rsquo
s Sizing Approach&rdquo
and &ldquo
Mark II FP&rdquo
) are applied to a project whose requirements are defined by means of use cases. Size and effort estimations are made and compared with the actual results of the project.

Model of Concurrency. The concurrency model is designed to be a straightforward target for mapping sequential programs onto, thus making them parallel. It aids the compilation process by providing a high level of abstraction, including a useful model of parallel behaviour which enables easy incorporation of message interchange, locking, and synchronization of objects. Further, the model is sufficient such that a compiler can and has been practically built. Model of Compilation. The compilation-model's structure is based upon an object-oriented view of grammar descriptions and capitalises on both a recursive-descent style of processing and abstract syntax trees to perform the parsing. A composite-object view with an attribute grammar style of processing is used to extract sufficient semantic information for the parallelisation (i.e. code-generation) phase. Programming Principles. The set of principles presented are based upon information hiding, sharing and containment of objects and the dividing up of methods on the basis of a command/query division. When followed, the level of potential parallelism within the presented concurrency model is maximised. Further, these principles naturally arise from good programming practice. Summary. In summary this thesis shows that it is possible to compile well-written programs, written in a subset of Eiffel, into parallel programs without any syntactic additions or semantic alterations to Eiffel: i.e. no parallel primitives are added, and the parallel program is modelled to execute with equivalent semantics to the sequential version. If the programming principles are followed, a parallelised program achieves the maximum level of potential parallelisation within the concurrency model.

Recent research makes use of biologically inspired computation and artificial intelligence as efficient means to solve real-world problems. Humans show a significant performance in extracting and interpreting visual information. In the cases where visual data is not available, or, for example, if it fails to provide comprehensive information due to occlusions, tactile exploration assists in the interpretation and better understanding of the environment. This cooperation between human senses can serve as an inspiration to embed a higher level of intelligence in computational models. In the context of this research, in the first step, computational models of visual attention are explored to determine salient regions on the surface of objects. Two different approaches are proposed. The first approach takes advantage of a series of contributing features in guiding human visual attention, namely color, contrast, curvature, edge, entropy, intensity, orientation, and symmetry are efficiently integrated to identify salient features on the surface of 3D objects. This model of visual attention also learns to adaptively weight each feature based on ground-truth data to ensure a better compatibility with human visual exploration capabilities. The second approach uses a deep Convolutional Neural Network (CNN) for feature extraction from images collected from 3D objects and formulates saliency as a fusion map of regions where the CNN looks at, while classifying the object based on their geometrical and semantic characteristics. The main difference between the outcomes of the two algorithms is that the first approach results in saliencies spread over the surface of the objects while the second approach highlights one or two regions with concentrated saliency. Therefore, the first approach is an appropriate simulation of visual exploration of objects, while the second approach successfully simulates the eye fixation locations on objects. In the second step, the first computational model of visual attention is used to determine scattered salient points on the surface of objects based on which simplified versions of 3D object models preserving the important visual characteristics of objects are constructed. Subsequently, the thesis focuses on the topic of tactile object recognition, leveraging the proposed model of visual attention. Beyond the sensor technologies which are instrumental in ensuring data quality, biological models can also assist in guiding the placement of sensors and support various selective data sampling strategies that allow exploring an object’s surface faster. Therefore, the possibility to guide the acquisition of tactile data based on the identified visually salient features is tested and validated in this research. Different object exploration and data processing approaches were used to identify the most promising solution. Our experiments confirm the effectiveness of computational models of visual attention as a guide for data selection for both simplifying 3D representation of objects as well as enhancing tactile object recognition. In particular, the current research demonstrates that: (1) the simplified representation of objects by preserving visually salient characteristics shows a better compatibility with human visual capabilities compared to uniformly simplified models, and (2) tactile data acquired based on salient visual features are more informative about the objects’ characteristics and can be employed in tactile object manipulation and recognition scenarios. In the last section, the thesis addresses the issue of transfer of learning from vision to touch. Inspired from biological studies that attest similarities between the processing of visual and tactile stimuli in human brain, the thesis studies the possibility of transfer of learning from vision to touch using deep learning architectures and proposes a hybrid CNN that handles both visual and tactile object recognition.

After the book, Design Patterns: Elements of Reusable Object-Oriented Software was published in 1994, usage of design patterns in object-oriented (OO) programming has been investigated by many researchers. However, the effects of design patterns on non-object oriented (non-OO) programming have not been analyzed too much in the literature. This study focuses on various design pattern implementations using non OO programming and investigates the benefits of design patterns upon real-time software. In order to evaluate the results, specific quality metrics were selected and performance of traditionally developed software was compared with that of software developed using design patterns.

The meanings of material culture and material objects have been studied in the academic work of Daniel Miller, Anat Hecht, Paul Smith, and others. These ideas are relevant and applicable to current artistic practice and also to the teaching of object-making in the Jewellery and Small Objects Department, Queensland College of Art, Griffith University. The objectives of this research are to investigate the inherited domestic object, and to consider its essential nature and how this influences the potential use and disuse of the object. The investigation is based around personal experience of family possessions, and the meanings ascribed to material objects as they were passed on to subsequent generations of family members. The research considers issues of mutability, where inherited objects may be modified within a cultural context to incorporate new values without loss of heritability. Design outcomes based on this research are used to inform my studio production of domestic objects of inheritable quality and value, and may be understood in the context of a personal maker’s guide. The findings of this research are expressed in a collection of made work that incorporates the quality of inheritability in a series of silver objects and adornments, as well as heritable objects to which a precious metal component has been added to ascribe and to underline value.
Thesis (Masters)
Master of Visual Arts (MVA)
Queensland College of Art
Arts, Education and Law
Full Text

This paper considers a novel method of PAHs in particular BP detection in water solutions with the use of semiconductor nanomaterials. The method constitutes a combination of electrochemical (EC) and electrochemiluminescent (ECL) analysis with the application of nanomaterials (semiconductor QDs) and nanotechnologies for sensor’s electrodes modification.

The last decade has seen the scope of digital library usage extend from data warehousing and other common library services to building quality collections of electronic resources and providing web-based information retrieval mechanisms for distributed learning. This is clear from the number of ongoing research initiatives aiming to provide dynamic learning environments. A major task in providing learning environments is to define a resource model (learning object). The flexibility of the learning object model determines the quality of the learning environment. Further, dynamic environments can be realized by changing the contents and structure of the learning object, i.e. make it mutable. Most existing models are immutable after creation and require the library to support operations that help in creating these environments. This leaves the learning object at the mercy of the parent library's functionality. This thesis work is an extension of an existing model and allows a learning object to function independent of the operational constraints of a digital library by equipping learning objects with software components called methods that influence their operation and structure even after being deployed. It provides a reference implementation of an aggregate, intelligent, self-sufficient, object-oriented, platform-independent learning object model, which is conformant to popular digital library standards. It also presents a Java-based development tool for creating and modifying smart objects. It is capable of performing content aggregation, metadata harvesting and user repository maintenance operations, in addition to supporting the addition/removal of methods to a smart object. The current smart object implementation and the development tool have been deployed successfully on two platforms (Windows and Linux) where their operation was found to be satisfactory.
Master of Science

Thesis (M.S. in Physics)-- Naval Postgraduate School, June 2009.
Thesis Advisor(s): Harkins, Richard ; Haegel, Nancy. "June 2009." Description based on title screen as viewed on July 13, 2009. Author(s) subject terms: Robotic Vision, Unmanned Ground Vehicle. Includes bibliographical references (p. 69-70). Also available in print.

The overall aim of this thesis is to explore the process of working with the Edwards claywork method with a psychotherapy client who had significant relational difficulties and feared being exposed as defective. Within this there are particular aims: Firstly, to investigate whether the distancing that art therapy can create, can help the client with relational difficulties to tolerate unexpressed disavowed feelings, in particular her sense of shame about being exposed as defective; and secondly, to examine whether material evoked through the claywork process can assist in furthering the psychological formulation of this kind of client. The research was a phenomenological-hermeneutic case study of a psychotherapy client, called Kim. Kim’s experience of therapy, including two claywork sessions, was documented. This comprises a thematic narrative of her therapy process prior to the claywork process, as well as a thematic narrative focusing on the two claywork sessions. Her clay sculpture was photographed and alphabetically labeled according to the chronological order in which she made the eight pieces comprising her sculpture. A hermeneutic reading of the narratives was conducted using theoretical perspectives including object relations, Adlerian psychology and art therapy. It was concluded that, firstly, the distancing that art therapy can create does help the client, who is afraid of being exposed as defective, to tolerate previously disavowed and unexpressed feelings; and secondly, art therapy such as the Edwards claywork method, does deepen psychological formulation of the client’s affective and relational difficulties. However, although the image may graphically symbolize unconscious aspects of a client’s psyche, the present study illustrates that a client may not always be able to enter into a relationship with the image or dialogue between conscious and unconscious states. In this respect, the present study focuses on aspects of art therapy of which there is limited literature.

The purpose of this study was to identify factors that motivate or impede faculty use of learning object repositories (LORs). The unified theory of acceptance and use of technology (UTAUT) served as the theoretical framework for this study. Both quantitative and qualitative approaches were used in the study to explore two research questions relating to factors affecting faculty use of LORs. Research subjects were faculty and instructional staff users from two LORs: Orange Grove and Wisc-Online. This study was a two-phase design study. In Phase I, I conducted 13 interviews and analyzed data by a content analysis method. Phase II of the study was designed based on the results of Phase I. I collected data by a survey instrument from 38 respondents and analyzed the data by descriptive statistics and analysis of variance in Phase II. The results of the study indicated 22 factors as motivators for faculty use of LORs and 13 factors as barriers for faculty use of LORs. The study is the first to identify factors affecting faculty use of LORs from actual faculty users’ perspectives based on UTAUT. The study’s findings contribute to understanding the reasons that faculty use or do not use LORs and provide foundations for designing strategies to increase faculty use of LORs.

This thesis studied the iron smelting technology of Southwest China. It introduces the natural and human environment of Southwest China and gives a systematic review on the important archaeological sites of Southwest China. A total of 75 iron smelting related sites of Southwest China were surveyed. Five of these sites were excavated and studied in detail including the furnace structures, smelting related materials and their smelting process. A statistical study of over 5,100 iron objects (and bronze and iron bi-metallic objects) in published excavation reports was carried out to understand the pattern and statistical distribution of iron objects excavated in Southwest China. This was followed by metallographic analysis of 66 samples taken from 42 iron objects and slags (mostly from the Lijiaba site, and from the Qiaogoutou site). The slag samples (from the Xuxiebian site) helped to identify the bowl-shaped furnaces, that discovered at the iron smelting sites of Southwest China, as refining furnaces. The results of the metallographic studies helped to characterise the range of technologies that developed in Southwest China primarily during the Han dynasty (202BC-220AD). According to these studies, some issues such as the origin and development of technology, the labourers’ identities, the origin of the blacksmiths, and the management and policy of iron production in Southwest China are discussed.

Since the early pioneering work of Rosenfeld and Sklansky, machine vision has been used successfully in a number of practical applications. In this work the areas of application have been reviewed to determine the extent to which computer vision has been utilised in industry. Its application so far has been restricted principally to the mass production field of car manufacture, in the areas of body panel inspection and to a lesser degree to unit assembly. The developnent of robots for picking unsorted components fron containers and for inspection depends upon the reliability and the speed of the vision control system employed. This project investigates a preliminary approach for fast shape recognition of randomly positioned and oriented components. The results obtained indicate that this goal can be achieved by the use of the techniques of contour tracing, Fourier and surface texture analysis and shape fron shading methods.

Research has shown that data warehouses potentially offer great investment opportunities to business. To benefit from this, business needs to invest large sums of money. Such investments are very risky, as no guarantee of the success of these ventures can be given. Object-oriented development has proved successful for developing operational systems in industry. This study researches object-oriented techniques to discover whether these techniques could be used successfully in data warehousing. A literature study focuses on the definition of an information systems development methodology and defines the components of such methodology. A further literature study on four popular object-oriented methodologies determines the commonalities of these methodologies. In conclusion, a literature study on data warehouse methodologies is done to discover the phases and techniques used in developing data warehouses. Based on the literature, a method is proposed to build a data warehouse harnessing object-oriented phases and techniques. The proposed method is applied as an interpretive experiment, followed by an evaluation of the data warehouse implemented.
Thesis (M.Sc. (Computer Science))--North-West University, Potchefstroom Campus, 2009.

Includes bibliographical references.
The purpose of this study was to explore the value of a particular theoretical framework in terms of several issues relating to clinical social work practice. The selected theoretical framework was that of Object Relations theory, specifically the works of Melanie Klein and Margaret Mahler. The method of inquiry was that of a single case study. The investigation centred around the theories' usefulness in clinical social work practice regarding: assessment, particularly in terms of the development of insight into and understanding of human psychological development, and guiding practice and informing intervention. The selected theoretical framework was also evaluated according to: its sufficiency, in and of itself, and the extent to which its utilization facilitates avoidance of stereotyping and pathologizing. The study was undertaken in a psychiatric unit, run according to the principles of a therapeutic milieu, in a local hospital. The subject of the study had been admitted to the unit after a parasuicide attempt. He manifested many of the affects and behaviours associated with Borderline Personality Disorder, and was a transsexual who had undergone reassignment surgery. Ongoing assessment and intervention were undertaken in the residential unit on an individual basis and in group activities. Reference to literature, the writings of Klein and Mahler in particular, was a crucial and essential aspect of the study. The selected theoretical framework was found to be of great value in terms of the development of insight into and understanding of human psychological development, which in turn aided the assessment process. Whilst neither Klein nor Mahler wrote extensively or specifically of intervention, a model compatible with their opinions was identified in the literature and effectively used for this purpose. The approach used, both from a theoretical and a practical standpoint, encouraged expression and maintenance of individual uniqueness. The study highlighted the importance of a sound theoretical knowledge base underpinning clinical practice, particularly when practitioners are challenged by difficult cases. In addition, the need for practitioners to assume responsibility for continued dynamic learning, and the significant role of supervision were apparent. Further avenues for study and research were also identified.

What Use is Music in an Ocean of Sound? is a reflective statement upon a body of artistic work created over approximately five years. This work, which I will refer to as "object- orientated", was specifically carried out to find out how I might fill artistic spaces with art objects that do not rely upon expanded notions of art or music nor upon explanations as to their meaning undertaken after the fact of the moment of encounter with them. My drive to create these objects was fuelled by a reaction against the work of other practitioners that I felt did not fulfil these criteria and lacked the self-awareness required to appreciate the cultural context within which it is produced. The title of this thesis is metaphorical and refers to the idea that cultural production is no use if it is not distinct from that which surrounds it. My practice is an attempt to produce objects that are self-consciously and self-reliantly distinct. It is no use for anything other than that.

This research developed an ArcGIS Python model that extracts polygons from aerial imagery and assigns each polygon a vegetation type based on a modified set of landcover classes from the Southwest Regional Gap Analysis Project. The model showed an ability to generate polygons that accurately represent vegetation community boundaries across a large landscape. The model is for use by the Utah Division of Forestry, Fire, and State Lands to assist in the preparation of forest management plans. The model was judged useful because it was easy to use, it met a designated 50% threshold of useable polygons, and it met a designated 50% threshold of vegetation class assignment accuracy.

Psychoanalysis as it exists today is not constituted by a single theoretical framework describing pathology and indicating a specific set of interventions. Since Freud originally conceptualised psychoanalytic understanding of pathology and psychoanalysis as a mode of intervention, there have been many revisions and reformulations of his theory. This thesis has attempted to integrate some psychoanalytic ideas regarding personality formation, psychopathology and psychotherapeutic intervention (Fairbairn, 1952; Ogden, 1992, 1994), with interpersonal (strategic / structural) ideas regarding intervention (Minuchin, 1974; Sullivan, 1940, 1953, 1964). In order to do so, the thesis used the relational psychoanalytic perspective, as depicted by Aron (1996) and Mitchell and Aron (1999), as an overarching conceptual framework. The focus from these points of view is the patient's internalized relationship patterns and the therapist's participation in their repetition. It is held that internalized relationship patterns are not only based on, but can be changed by, lived experience. From this perspective, the goal of therapy is to enhance the patient's capacity to reflect and think about experience, and therefore, to communicate about it. This means a change in the patient's predominant mode of communication. Ogden's (1994) modes of communication were described. The thesis suggested that Ogden's modes of communication can be stretched or translated into the types of communication outlined by Langs (1978). This thesis aimed to explore the deliberate use of countertransference responses to facilitate communication in the beginning stages of therapy with patients functioning predominantly in the paranoid-schizoid mode (Ogden, 1992). Patients who operate in this mode are often unable to tolerate interpretation and therefore traditional approaches to intervention are not effective. A "strategic / structural relational psychoanalytic" approach to treatment was proposed. It was suggested that therapists utilize joining and accommodation techniques as described by Minuchin (1974) and alter their style of interaction to match that of the various object relational constellations that they have managed to identify within the patient via their countertransference responses. It was hypothesized that patients need their therapists to be similar to their original objects in order to feel safe in the therapeutic environment and that this may facilitate communication in the beginning stages of therapy. The research utilized a qualitative research approach. Qualitative research methods attempt to use data gathered phenomenologically, always acknowledging the researcher's biases when gathering the data. The data gathered is then interpreted according to various theories or hermeneutic lenses. The hypothesis mentioned above has been investigated by analyzing three cases in terms of the research questions based on Langs' (1978) classification of communication. The thesis described the difficulties inherent in collecting clinical data from psychologists working from within a psychoanalytic framework. Eventually three sets of therapy details and verbatim therapy transcripts were obtained, provided in the thesis and analyzed in terms of the research questions. However evidence for the success of the hypothesized alternate approach was not found in this research study. It was suggested that other possible methods might be useful to investigate the hypothesized approach further.

Apraxia, a high-level movement disorder, is associated with performance errors during gesture imitation, demonstrating the use of familiar objects that are present (actual object-use) or absent (pantomime), or all three scenarios. Focusing on objects, apraxia has an isolated effect on manipulation judgements regarding skilled object-use. These manipulation deficits are potentially attributed to damage to a purported ventro-dorsal stream resulting in impaired internal representations of movement (i.e. motor imagery). Instead, patients over-rely on visual affordances during object-directed motor behaviour. The cortical regions associated with the ventro-dorsal stream correspond to those damaged in apraxia, in particular the left inferior parietal lobe (IPL), adding weight to this proposal. Using a perceptual matching task with familiar objects and an action execution grasping task with novel objects, behavioural work with left hemisphere stroke patients assessed whether apraxic deficits are specific to object manipulation and whether these patients over-rely on object affordances during skilled object-manipulation. In parallel, the effect of neuromodulation technique transcranial direct current stimulation (tDCS) on motor imagery was explored with healthy populations. Performance changes during left IPL stimulation was assessed during classic motor mental rotation and the same perceptual matching task used with patients. Apraxic patients showed a selective impairment during object manipulation judgements of the perceptual matching task, which increased with apraxia severity. Despite tDCS over the left or right IPL equally affecting motor mental rotation performance in healthy populations, during the perceptual matching task only modulation of the left IPL slowed reaction times when making manipulation judgements but not functional semantic judgements regarding object-use. These results suggest that disruption of ventro-dorsal processing specifically disturbs motor representations of object-use. When repeatedly grasping novel objects of differing weight distribution, most apraxic patients consistently selected a structurally afforded grasp-point, indicating that apraxic patients over-rely on visual affordances after ventro-dorsal disruption. These results confirm that the ventro-dorsal stream, in particular the left IPL, is critical in integrating perceptual internal representations of skilled movement into context-dependent action plans based on visual information. Over-reliance on visual affordances caused by disruption to this pathway not only affects perceptual manipulation judgements of familiar objects but also experience-based learning when grasping novel objects.

Cost is one of the problems for wider adoption of Advanced Driver Assistance Systems (ADAS) in China. The objective of this research project is to develop a low-cost ADAS by the shared use of motion vectors (MVs) from a H.264/AVC video encoder that was originally designed for video recording only. There were few studies on the use of MVs from video encoders on a moving platform for moving object detection. The main contribution of this research is the novel algorithm proposed to address the problems of moving object detection when MVs from a H.264/AVC encoder are used. It is suitable for mass-produced in-vehicle devices as it combines with MV based moving object detection in order to reduce the cost and complexity of the system, and provides the recording function by default without extra cost. The estimated cost of the proposed system is 50% lower than that making use of the optical flow approach. To reduce the area of region of interest and to account for the real-time computation requirement, a new block based region growth algorithm is used for the road region detection. To account for the small amplitude and limited precision of H.264/AVC MVs on relatively slow moving objects, the detection task separates the region of interest into relatively fast and relatively slow speed regions by examining the amplitude of MVs, the position of focus of expansion and the result of road region detection. Relatively slow moving objects are detected and tracked by the use of generic horizontal and vertical contours of rear-view vehicles. This method has addressed the problem of H.264/AVC encoders that possess limited precision and erroneous motion vectors for relatively slow moving objects and regions near the focus of expansion. Relatively fast moving objects are detected by a two-stage approach. It includes a Hypothesis Generation (HG) and a Hypothesis Verification (HV) stage. This approach addresses the problem that the H.264/AVC MVs are generated for coding efficiency rather than for minimising motion error of objects. The HG stage will report a potential moving object based on clustering the planar parallax residuals satisfying the constraints set out in the algorithm. The HV will verify the existence of the moving object based on the temporal consistency of its displacement in successive frames. The test results show that the vehicle detection rate higher than 90% which is on a par to methods proposed by other authors, and the computation cost is low enough to achieve the real-time performance requirement. An invention patent, one international journal paper and two international conference papers have been either published or accepted, showing the originality of the work in this project. One international journal paper is also under preparation.

This thesis addresses three research gaps in published literature. These are, the absence of Object Based Image Analysis (OBIA) methods for urban Land Use and Land Cover (LULC) analysis in Nigeria; the inability to use Nigeriasat-1 satellite data for urban LULC analysis and monitoring urban growth in Nigeria with Shannon’s Entropy Index. Using Abuja as a case study, this research investigated the nature of land use/land cover change (LULCC). Specific objectives were: design of an object based classification method to extract urban LULC; validate a method to extract LULC in developing countries from multiple sources of remotely sensed data; apply the method to extract LULC data; use the outputs to validate an Urban Growth Model (UGM); optimise an UGM to represent patterns and trends and through this iterative process identify and prioritise the driving forces of urban change; and finally use the outputs of the land use maps to determine if planning has controlled land use development. Landsat 7 ETM (2001), Nigeriasat-1 SLIM (2003) and SPOT 5 HRG (2006) sensor data were merged with land use cadastre in OBIA, to produce land use maps. Overall classification accuracies were 92%, 89% and 96% respectively. Post classification analysis of LULCC indicated 4.43% annual urban spread. Shannon’s Entropy index for the study period were 0.804 (2001), 0.898 (2003) and 0.930 (2006). Cellular Automata/Markov analysis was also used to predict urban growth trend of 0.89% per annum. For the first time OBIA has been used for LULC analysis in Nigeria. This research has established that Nigeriasat-1 data can contribute to urban studies using innovative OBIA methods. In addition, that Shannon’s Entropy Index can be used to understand the nature of urban growth in Nigeria. Finally, the drivers of LULCC in Abuja are similar to those of planned capital cities in other developing economies. Land use developments in Abuja can provide an insight into urban dynamics in a developing country’s capital region. OBIA, Shannon’s Entropy Index and UGM can aid urban administrators and provide information for sustainable urban planning and development.

PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
A dissertação consiste numa pesquisa teórica que propõe o argumento de os ataques ao enquadre, frequentemente empreendidos pelos casos-limite, constituírem a tentativa clínica de passagem para o campo do uso do objeto. A agressividade não bem manejada pelo ambiente prejudica o reconhecimento da externalidade, resultando numa tendência à destruição que se torna característica central da clínica com estes casos. O trabalho do negativo malsucedido impossibilita a construção do espaço da ausência no psiquismo, fundamental à construção de representações, à instauração das fronteiras intrapsíquicas e intersubjetivas e ao investimento em objetos substitutos. Os prejuízos relativos à agressividade e ao trabalho do negativo redundam na precariedade das fronteiras entre o eu e o outro, sugerindo a prevalência de uma relação pautada na vertente subjetiva do objeto, logo não reconhecido em sua natureza externa. As contribuições de Winnicott e Green fundamentam nossa hipótese de que a destrutividade – expressa na clínica dos casos-limite através dos ataques ao enquadre – consiste numa tentativa atuada de passagem para o campo do uso do objeto, que consolida a unidade do self ao mesmo tempo que possibilita o reconhecimento do objeto na realidade compartilhada.
The dissertation consists of theoretical research proposing the argument that the attacks on the setting, often undertaken by borderline patients, consists on a clinical way of reaching the use of an object. The aggressiveness not well handled by the environment affects the recognition of the externality, resulting in a tendency towards destruction which becomes the central feature in the borderline clinic. The unsuccessful work of the negative precludes the construction of an absence space in the psyche, fundamental to the construction of representations, the introduction of intrapsychic and intersubjective borders, as the investment in substitute objects. Losses related to aggressiveness and the work of the negative result in precarious boundaries between self and other, suggesting the prevalence of a relationship based in the subjective aspect of the object, not just recognized in his external nature. The contributions of Winnicott and Green underlie our hypothesis that the destructiveness – expressed in borderline clinic through the attacks on the setting – consists in an actuated way to reach the use of the object, which consolidates the unity of self while enables the recognition of the object in shared reality.

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.

A robot should be able to autonomously modify and utilize its environment to assist its task completion. While mobile manipulators and humanoid robots have both locomotion and manipulation capabilities, planning systems typically just consider one or the other. In traditional motion planning the planner attempts to find a collision free path from the robot's current configuration to some goal configuration. In general, this process entirely ignores the fact that the robot has manipulation capabilities. This is in contrast to how humans naturally act - utilizing their manipulation capabilities to modify the environment to assist locomotion. If necessary, humans do not hesitate to move objects, such as chairs, out of their way or even place an object, such as a board, on the ground to reach an otherwise unreachable goal. We argue that robots should demonstrate similar behavior. Robots should use their manipulation capabilities to move or even use environment objects. This thesis aims at bringing robots closer to such capabilities. There are two primary challenges in developing practical systems that allow a real robotic system to tightly couple its manipulation and locomotion capabilities: the inevitable inaccuracies in perception as well as actuation that occur on physical systems, and the exponential size of the search space. To address these challenges, this thesis first extends the previously introduced domain of Navigation Among Movable Obstacles (NAMO), which allows a robot to move obstacles out of its way. We extend the NAMO domain to handle the underlying issue of uncertainty. In fact, this thesis introduces the first NAMO framework that allows a real robotic systems to consider sensing and action uncertainties while reasoning about moving objects out of the way. However, the NAMO domain itself has the shortcoming that it only considers a robot's manipulation capabilities in the context of clearing a path. This thesis therefore also generalizes the NAMO domain itself to the Navigation Using Manipulable Obstacles (NUMO) domain. The NUMO domain enables a robot to more generally consider the coupling between manipulation and locomotion capabilities and supports reasoning about using objects in the environment. This thesis shows the relationship between the NAMO and NUMO domain, both in terms of complexity as well as solution approaches, and presents multiple realizations of the NUMO domain. The first NUMO realization enables a robot to use its manipulation capabilities to assist its locomotion by changing the geometry of the environment for scenarios in which obstructions can be overcome through the usage of a single object. The system led a real humanoid robot to autonomously build itself a bridge to cross a gap and a stair step to get on a platform. A second NUMO realization then introduces reasoning about force constraints using knowledge about the mechanical advantages of a lever and battering ram. The discussed system allows a robot to consider increasing its effective force though the use of objects, such as utilizing a rod as a lever. Finally this thesis extends the NUMO framework for geometric constraints to scenarios in which the robot is faced with a substantial lack of initial state information and only has access to onboard sensing. In summary, this thesis enables robots to autonomously modify their environment to achieve task completion in the presence of lack of support for mobility, the need to increase force capabilities and partial knowledge.

Following the hierarchical nature of forest resource management, the present work focuses on the natural forest cover at various abstraction levels of details, i.e. categorical land use/land cover (LU/LC) level and a continuous empirical estimation of local operational level. As no single sensor presently covers absolutely all the requirements of the entire levels of forest resource assessment, multisource imagery (i.e. RapidEye, TERRA ASTER and LANDSAT TM), in addition to other data and knowledge have been examined. To deal with this structure, an object-based image analysis (OBIA) approach has been assessed in the destabilized Blue Nile region of Sudan as a potential solution to gather the required information for future forest planning and decision making. Moreover, the spatial heterogeneity as well as the rapid changes observed in the region motivates the inspection for more efficient, flexible and accurate methods to update the desired information. An OBIA approach has been proposed as an alternative analysis framework that can mitigate the deficiency associated with the pixel-based approach. In this sense, the study examines the most popular pixel-based maximum likelihood classifier, as an example of the behavior of spectral classifier toward respective data and regional specifics. In contrast, the OBIA approach analyzes remotely sensed data by incorporating expert analyst knowledge and complimentary ancillary data in a way that somehow simulates human intelligence for image interpretation based on the real-world representation of the features. As the segment is the basic processing unit, various combinations of segmentation criteria were tested to separate similar spectral values into groups of relatively homogeneous pixels. At the categorical subtraction level, rules were developed and optimum features were extracted for each particular class. Two methods were allocated (i.e. Rule Based (RB) and Nearest Neighbour (NN) Classifier) to assign segmented objects to their corresponding classes. Moreover, the study attempts to answer the questions whether OBIA is inherently more precise at fine spatial resolution than at coarser resolution, and how both pixel-based and OBIA approaches can be compared regarding relative accuracy in function of spatial resolution. As anticipated, this work emphasizes that the OBIA approach is can be proposed as an advanced solution particulary for high resolution imagery, since the accuracies were improved at the different scales applied compare with those of pixel-based approach. Meanwhile, the results achieved by the two approaches are consistently high at a finer RapidEye spatial resolution, and much significantly enhanced with OBIA. Since the change in LU/LC is rapid and the region is heterogeneous as well as the data vary regarding the date of acquisition and data source, this motivated the implementation of post-classification change detection rather than radiometric transformation methods. Based on thematic LU/LC maps, series of optimized algorithms have been developed to depict the dynamics in LU/LC entities. Therefore, detailed change “from-to” information classes as well as changes statistics were produced. Furthermore, the produced change maps were assessed, which reveals that the accuracy of the change maps is consistently high. Aggregated to the community-level, social survey of household data provides a comprehensive perspective additionally to EO data. The predetermined hot spots of degraded and successfully recovered areas were investigated. Thus, the study utilized a well-designed questionnaire to address the factors affecting land-cover dynamics and the possible solutions based on local community's perception. At the operational structural forest stand level, the rationale for incorporating these analyses are to offer a semi-automatic OBIA metrics estimates from which forest attribute is acquired through automated segmentation algorithms at the level of delineated tree crowns or clusters of crowns. Correlation and regression analyses were applied to identify the relations between a wide range of spectral and textural metrics and the field derived forest attributes. The acquired results from the OBIA framework reveal strong relationships and precise estimates. Furthermore, the best fitted models were cross-validated with an independent set of field samples, which revealed a high degree of precision. An important question is how the spatial resolution and spectral range used affect the quality of the developed model this was also discussed based on the different sensors examined. To conclude, the study reveals that the OBIA has proven capability as an efficient and accurate approach for gaining knowledge about the land features, whether at the operational forest structural attributes or categorical LU/LC level. Moreover, the methodological framework exhibits a potential solution to attain precise facts and figures about the change dynamics and its driving forces
Da das Waldressourcenmanagement hierarchisch strukturiert ist, beschäftigt sich die vorliegende Arbeit mit der natürlichen Waldbedeckung auf verschiedenen Abstraktionsebenen, das heißt insbesondere mit der Ebene der kategorischen Landnutzung / Landbedeckung (LU/LC) sowie mit der kontinuierlichen empirischen Abschätzung auf lokaler operativer Ebene. Da zurzeit kein Sensor die Anforderungen aller Ebenen der Bewertung von Waldressourcen und von Multisource-Bildmaterialien (d.h. RapidEye, TERRA ASTER und LANDSAT TM) erfüllen kann, wurden zusätzlich andere Formen von Daten und Wissen untersucht und in die Arbeit mit eingebracht. Es wurde eine objekt-basierte Bildanalyse (OBIA) in einer destabilisierten Region des Blauen Nils im Sudan eingesetzt, um nach möglichen Lösungen zu suchen, erforderliche Informationen für die zukünftigen Waldplanung und die Entscheidungsfindung zu sammeln. Außerdem wurden die räumliche Heterogenität, sowie die sehr schnellen Änderungen in der Region untersucht. Dies motiviert nach effizienteren, flexibleren und genaueren Methoden zu suchen, um die gewünschten aktuellen Informationen zu erhalten. Das Konzept von OBIA wurde als Substitution-Analyse-Rahmen vorgeschlagen, um die Mängel vom früheren pixel-basierten Konzept abzumildern. In diesem Sinne untersucht die Studie die beliebtesten Maximum-Likelihood-Klassifikatoren des pixel-basierten Konzeptes als Beispiel für das Verhalten der spektralen Klassifikatoren in dem jeweiligen Datenbereich und der Region. Im Gegensatz dazu analysiert OBIA Fernerkundungsdaten durch den Einbau von Wissen des Analytikers sowie kostenlose Zusatzdaten in einer Art und Weise, die menschliche Intelligenz für die Bildinterpretation als eine reale Darstellung der Funktion simuliert. Als ein Segment einer Basisverarbeitungseinheit wurden verschiedene Kombinationen von Segmentierungskriterien getestet um ähnliche spektrale Werte in Gruppen von relativ homogenen Pixeln zu trennen. An der kategorische Subtraktionsebene wurden Regeln entwickelt und optimale Eigenschaften für jede besondere Klasse extrahiert. Zwei Verfahren (Rule Based (RB) und Nearest Neighbour (NN) Classifier) wurden zugeteilt um die segmentierten Objekte der entsprechenden Klasse zuzuweisen. Außerdem versucht die Studie die Fragen zu beantworten, ob OBIA in feiner räumlicher Auflösung grundsätzlich genauer ist als eine gröbere Auflösung, und wie beide, das pixel-basierte und das OBIA Konzept sich in einer relativen Genauigkeit als eine Funktion der räumlichen Auflösung vergleichen lassen. Diese Arbeit zeigt insbesondere, dass das OBIA Konzept eine fortschrittliche Lösung für die Bildanalyse ist, da die Genauigkeiten - an den verschiedenen Skalen angewandt - im Vergleich mit denen der Pixel-basierten Konzept verbessert wurden. Unterdessen waren die berichteten Ergebnisse der feineren räumlichen Auflösung nicht nur für die beiden Ansätze konsequent hoch, sondern durch das OBIA Konzept deutlich verbessert. Die schnellen Veränderungen und die Heterogenität der Region sowie die unterschiedliche Datenherkunft haben dazu geführt, dass die Umsetzung von Post-Klassifizierungs- Änderungserkennung besser geeignet ist als radiometrische Transformationsmethoden. Basierend auf thematische LU/LC Karten wurden Serien von optimierten Algorithmen entwickelt, um die Dynamik in LU/LC Einheiten darzustellen. Deshalb wurden für Detailänderung "von-bis"-Informationsklassen sowie Veränderungsstatistiken erstellt. Ferner wurden die erzeugten Änderungskarten bewertet, was zeigte, dass die Genauigkeit der Änderungskarten konstant hoch ist. Aggregiert auf die Gemeinde-Ebene bieten Sozialerhebungen der Haushaltsdaten eine umfassende zusätzliche Sichtweise auf die Fernerkundungsdaten. Die vorher festgelegten degradierten und erfolgreich wiederhergestellten Hot Spots wurden untersucht. Die Studie verwendet einen gut gestalteten Fragebogen um Faktoren die die Dynamik der Änderung der Landbedeckung und mögliche Lösungen, die auf der Wahrnehmung der Gemeinden basieren, anzusprechen. Auf der Ebene des operativen strukturellen Waldbestandes wird die Begründung für die Einbeziehung dieser Analysen angegeben um semi-automatische OBIA Metriken zu schätzen, die aus dem Wald-Attribut durch automatisierte Segmentierungsalgorithmen in den Baumkronen abgegrenzt oder Cluster von Kronen Ebenen erworben wird. Korrelations- und Regressionsanalysen wurden angewandt, um die Beziehungen zwischen einer Vielzahl von spektralen und strukturellen Metriken und den aus den Untersuchungsgebieten abgeleiteten Waldattributen zu identifizieren. Die Ergebnisse des OBIA Rahmens zeigen starke Beziehungen und präzise Schätzungen. Die besten Modelle waren mit einem unabhängigen Satz von kreuz-validierten Feldproben ausgestattet, welche hohe Genauigkeiten ergaben. Eine wichtige Frage ist, wie die räumliche Auflösung und die verwendete Bandbreite die Qualität der entwickelten Modelle auch auf der Grundlage der verschiedenen untersuchten Sensoren beeinflussen. Schließlich zeigt die Studie, dass OBIA in der Lage ist, als ein effizienter und genauer Ansatz Kenntnisse über die Landfunktionen zu erlangen, sei es bei operativen Attributen der Waldstruktur oder auch auf der kategorischen LU/LC Ebene. Außerdem zeigt der methodischen Rahmen eine mögliche Lösung um präzise Fakten und Zahlen über die Veränderungsdynamik und ihre Antriebskräfte zu ermitteln

Thesis (MA)--Stellenbosch University, 2015.
ENGLISH ABSTRACT: Image classification has long been used in earth observation and is driven by the need for accurate maps to develop conceptual and predictive models of Earth system processes. Synthetic aperture radar (SAR) imagery is used ever more frequently in land cover classification due to its complementary nature with optical data. There is therefore a growing need for reliable, accurate methods for using SAR and optical data together in land use and land cover classifications. However, combining data sets inevitably increases data dimensionality and these large, complex data sets are difficult to handle. It is therefore important to assess the benefits and limitations of using multi-temporal, dual-sensor data for applications such as land cover classification. This thesis undertakes this assessment through four main experiments based on combined RADARSAT-2 and SPOT-5 imagery of the southern part of Reunion Island. In Experiment 1, the use of feature selection for dimensionality reduction was considered. The rankings of important features for both single-sensor and dual-sensor data were assessed for four dates spanning a 6-month period, which coincided with both the wet and dry season. The mean textural features produced from the optical bands were consistently ranked highly across all dates. In the two later dates (29 May and 9 August 2014), the SAR features were more prevalent, showing that SAR and optical data have complementary natures. SAR data can be used to separate classes when optical imagery is insufficient. Experiment 2 compared the accuracy of six supervised and machine learning classification algorithms to determine which performed best with this complex data set. The Random Forest classification algorithm produced the highest accuracies and was therefore used in Experiments 3 and 4. Experiment 3 assessed the benefits of using combined SAR-optical imagery over single-sensor imagery for land cover classifications on four separate dates. The fused imagery produced consistently higher overall accuracies. The 29 May 2014 fused data produced the best accuracy of 69.8%. The fused classifications had more consistent results over the four dates than the single-sensor imagery, which suffered lower accuracies, especially for imagery acquired later in the season. In Experiment 4, the use of multi-temporal, dual-sensor data for classification was evaluated. Feature selection was used to reduce the data set from 638 potential training features to 50, which produced the best accuracy of 74.1% in comparison to 71.9% using all of the features. This result validated the use of multi-temporal data over single-date data for land cover classifications. It also validated the use of feature selection to successfully inform data reduction without compromising the accuracy of the final product. Multi-temporal and dual-sensor data shows potential for mapping land cover in a tropical, mountainous region that would otherwise be challenging to map using single-sensor data. However, accuracies Stellenbosch University https://scholar.sun.ac.za iv generally remained lower than would allow for transferability and replication of the current methodology. Classification algorithm optimisation, supervised segmentation and improved training data should be considered to improve these results.
AFRIKAANSE OPSOMMING: Beeld-klassifikasie word al ‘n geruime tyd in aardwaarneming gebruik en word gedryf deur die behoefte aan akkurate kaarte om konseptuele en voorspellende modelle van aard-stelsel prosesse te ontwikkel. Sintetiese apertuur radar (SAR) beelde word ook meer dikwels in landdekking klassifikasie gebruik as gevolg van die aanvullende waarde daarvan met optiese data. Daar is dus 'n groeiende behoefte aan betroubare, akkurate metodes vir die gesamentlike gebruik van SAR en optiese data in landdekking klassifikasies. Die kombinasie van datastelle bring egter ‘n onvermydelike verhoging in data dimensionaliteit mee, en hierdie groot, komplekse datastelle is moeilik om te hanteer. Dus is dit belangrik om die voordele en beperkings van die gebruik van multi-temporale, dubbel-sensor data vir toepassings soos landdekking-klassifikasie te evalueer. Die waarde van gekombineerde (versmelte) RADARSAT-2 en SPOT-5 beelde word in hierdie tesis deur middel van vier eksperimente geevalueer. In Eksperiment 1 is die gebruik van kenmerk seleksie vir dimensionaliteit-vermindering toegepas. Die ranglys van belangrike kenmerke vir beide enkel-sensor en 'n dubbel-sensor data is beoordeel vir vier datums wat oor 'n tydperk van 6 maande strek. Die gemiddelde tekstuur kenmerke uit die optiese lae is konsekwent hoog oor alle datums geplaas. In die twee later datums (29 Mei en 9 Augustus 2014) was die SAR kenmerke meer algemeen, wat dui op die aanvullende aard van SAR en optiese data. SAR data dus gebruik kan word om klasse te onderskei wanneer optiese beelde onvoldoende daarvoor is. Eksperiment 2 het die akkuraatheid van ses gerigte en masjien-leer klassifikasie algoritmes vergelyk om te bepaal watter die beste met hierdie komplekse datastel presteer. Die random gorest klassifikasie algoritme het die hoogste akkuraatheid bereik en is dus in Eksperimente 3 en 4 gebruik. Eksperiment 3 het die voordele van gekombineerde SAR-optiese beelde oor enkel-sensor beelde vir landdekking klassifikasies op vier afsonderlike datums beoordeel. Die versmelte beelde het konsekwent hoër algehele akkuraathede as enkel-sensor beelde gelewer. Die 29 Mei 2014 data het die hoogste akkuraatheid van 69,8% bereik. Die versmelte klassifikasies het ook meer konsekwente resultate oor die vier datums gelewer en die enkel-sensor beelde het tot laer akkuraathede gelei, veral vir die later datums. In Eksperiment 4 is die gebruik van multi-temporale, dubbel-sensor data vir klassifikasie ge-evalueer. Kenmerkseleksie is gebruik om die data stel van 638 potensiële kenmerke na 50 te verminder, wat die beste akkuraatheid van 74,1% gelewer het. Hierdie resultaat bevestig die belangrikheid van multi-temporale data vir grond dekking klassifikasies. Dit bekragtig ook die gebruik van kenmerkseleksie om data vermindering suksesvol te rig sonder om die akkuraatheid van die finale produk te belemmer. Stellenbosch University https://scholar.sun.ac.za vi Multi-temporale en dubbel-sensor data toon potensiaal vir die kartering van landdekking in 'n tropiese, bergagtige streek wat andersins uitdagend sou wees om te karteer met behulp van enkel-sensor data. Oor die algemeen het akkuraathede egter te laag gebly om vir oordraagbaarheid en herhaling van die huidige metode toe te laat. Klassifikasie algoritme optimalisering, gerigte segmentering en verbeterde opleiding data moet oorweeg word om hierdie resultate te verbeter.

The subject of this thesis is to analyze and evaluate the placement of buildings under the Building Act in the microregion Litovelsko. The theoretical part will include individual division of the Construction Act, including zoning classification. In will be done analysis of specific examples and to the family house in the village Ješov, then there will be discussed at the appropriate location of the building plot in the village Hradečná and the last example is the location of the construction site in dilapidated buildings in the village Kovářov. Finally, the work will include evaluation of appropriate solutions to the location of buildings.

In response to recent declines, forested riparian wetland areas have become an increased conservation and management area of concern focusing on increasing biodiversity and promoting healthy ecosystem services. Additionally, passerine birds have also experienced a sharp global decline in that associated habitat. To mitigate further declines of both habitat and species numbers government programs and agencies have intensified conservation efforts. However, the practices employed are often assumed to be beneficial without conducting dedicated surveys to measure efficacy and practicality of current approaches. As such, visual evidence and statistics are often needed to promote or validate further support and funding for continuing with current polices or creating new focal areas and practices. This study strives to provide an inexpensive, efficient way to assess conservation areas based on a target species through a generalized and adaptive methodology. The Cypress Creek National Wildlife Refuge in southern Illinois provides an opportunity to do just that with a focus on songbirds. The methodology outlined in this study implements multiple remote sensing land use and land cover classification techniques utilizing Landsat imagery from 1984 to 2014 to create a temporal analysis of the region from pre-refuge era to current refuge designated era. Field surveys from the 2015 songbird summer breeding and fall migration seasons as well as vegetation surveys for field-truthing supplement the remote sensing results. The classification methodology incudes a combination of pan-sharpening Landsat images to a 15 m x 15 m spatial resolution, texture analysis, object based image analysis, and Random Forests to produce land use and land cover maps. For the sake of comparison the same classification process is performed with the untransformed, source images at 30 m x 30 m spatial resolution. Landscape metrics such as the interspersion and juxtaposition index and the contiguity index also provide further insight to temporal landscape patterns. At the completion of the study it was found that there was a minimal difference between the overall classification accuracy of transformed and untransformed images and that lowest overall accuracy in the study was 91% while the highest was 98%. The key survey statistics concluded that during the summer and fall observation periods songbirds in forested wetland areas had a propensity to utilize areas closest to the wetland edge as opposed to inland areas. Furthermore, during fall migration it was concluded that the mixed forest habitat type had a direct effect on observation numbers. Overall, with the aid of multiple landscape metrics, it was shown that the region was increasing in forested area, patch density, and contiguity; in response the passerines were using the area at a high rate, especially near wetland edges creating a sustainable focal area for conservation and management. The methodology and results in this study contribute to an ongoing effort to provide visual and statistical evidence that is reliable and accessible for policy making. The potential to manipulate the generalized methods used in this study to enhance any land use and land class classifications and apply to any targeted species certainly exists. Future studies will want to investigate the use of higher spatial resolution images or actively take reflectance recordings in the field and supplement the temporal maps with a multi-year dedicated species dataset for maximum benefit.