The use of context in the classification of urban aerial imagery

Urban regions present some of the most challenging areas for the remote sensing community. Many different types of land cover have similar spectral responses, making them difficult to distinguish from one another. Traditional per-pixel classification techniques suffer particularly badly because they only use these spectral properties to determine a class, and no other properties of the image, such as context. This project presents the results of the classification of a deeply urban area of Dudley, West Midlands, using 4 methods: Supervised Maximum Likelihood, SMAP, ECHO and Unsupervised Maximum Likelihood. An accuracy assessment method is then developed to allow a fair representation of each procedure and a direct comparison between them. Subsequently, a classification procedure is developed that makes use of the context in the image, though a per-polygon classification. The imagery is broken up into a series of polygons extracted from the Marr-Hildreth zero-crossing edge detector. These polygons are then refined using a region-growing algorithm, and then classified according to the mean class of the fine polygons. The imagery produced by this technique is shown to be of better quality and of a higher accuracy than that of other conventional methods. Further refinements are suggested and examined to improve the aesthetic appearance of the imagery. Finally a comparison with the results produced from a previous study of the James Bridge catchment, in Darleston, West Midlands, is made, showing that the Polygon classified ATM imagery performs significantly better than the Maximum Likelihood classified videography used in the initial study, despite the presence of geometric correction errors.

An evaluation of aerial photography as a source of environmental information

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A methodology, using aerial photographs, for mapping urban land-use in Nigeria

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A survey of urban open space using colour infra-red aerial photographs

There has been a dramatic change in the U.K. government policy regarding the establishment of new towns. The emphasis is now on the redevelopment of existing cities rather than on building new ones. This has created an urgent need to carry out detailed surveys and inventories of many aspects of urban land use in metropolitan areas: this study concentrates on just one aspect - urban open space. In the first stage a comparison was made between 1:10,000 scale black and white and 1:10,000 scale colour infra-red aerial photographs, to compare the type and amount of open space information which could be obtained from these two sources. The advantages of using colour infra-red photography were clearly demonstrated in this comparison. The second stage was the use of colour infra-red photography as the sole source of data to survey and map the urban open space of a sample area in Merseyside Metropolitan County. This sample area comprised eleven 1/4km2 squares, on each of which a 20m x 20m grid cell was placed to record, directly from the photography, 625 sets of data. Each set of data recorded the type and amount of open space, its surface cover, maintenance status and management. The data recorded were fed into a computer and a suite of programs was developed to provide output in both computer map and statistical form, for each of the eleven -1/4km2 -sample areas. The third stage involved a comparison of open space data with socio-economic status. Merseyside County Planning Authority had previously conducted a socio-economic survey of the county, and this information was used to identify ' the socio-economic status of the population in the eleven ilkm2 areas of this project. This comparison revealed many interesting and useful relationships between the provision of urban open space and socio-economic status.

Land use monitoring in the Nigerian savanna using aerial photographs

Aerial photography was used to determine the land use in a test area of the Nigerian savanna in 1950 and 1972. Changes in land use were determined and correlated with accessibility, appropriate low technology methods being used to make it easy to extend the investigation to other areas without incurring great expense. A test area of 750 sq km was chosen located in Kaduna State of Nigeria. The geography of the area is summarised together with the local knowledge which is essential for accurate photo interpretation. A land use classification was devised and tested for use with medium scale aerial photography of the savanna. The two sets of aerial photography at 1:25 000 scale were sampled using systematic dot grids. A dot density of 8 1/2 dots per sq km was calculated to give an acceptable estimate of land use. Problems of interpretation included gradation between categories, sample position uncertainty and personal bias. The results showed that in 22 years the amount of cultivated land in the test area had doubled while there had been a corresponding decrease in the amount of uncultivated land particularly woodland. The intensity of land use had generally increased. The distribution of land use changes was analysed and correlated with accessibility. Highly significant correlations were found for 1972 which had not existed in 1950. Changes in land use could also be correlated with accessibility. It was concluded that in the 22 year test period there had been intensification of land use, movement of human activity towards the main road, and a decrease in natural vegetation particularly close to the road. The classification of land use and the dot grid method of survey were shown to be applicable to a savanna test area.

The application of robotics to the turbine blade encapsulation process

A survey of the existing state-of-the-art of turbine blade manufacture highlights two operations that have not been automated namely that of loading of a turbine blade into an encapsulation die, and that of removing a machined blade from the encapsulation block. The automation of blade decapsulation has not been pursued. In order to develop a system to automate the loading of an encapsulation die a prototype mechanical handling robot has been designed together with a computer controlled encapsulation die. The robot has been designed as a mechanical handling robot of cylindrical geometry, suitable for use in a circular work cell. It is the prototype for a production model to be called `The Cybermate'. The prototype robot is mechanically complete but due to unforeseen circumstances the robot control system is not available (the development of the control system did not form a part of this project), hence it has not been possible to fully test and assess the robot mechanical design. Robot loading of the encapsulation die has thus been simulated. The research work with regard to the encapsulation die has focused on the development of computer controlled, hydraulically actuated, location pins. Such pins compensate for the inherent positional inaccuracy of the loading robot and reproduce the dexterity of the human operator. Each pin comprises a miniature hydraulic cylinder, controlled by a standard bidirectional flow control valve. The precision positional control is obtained through pulsing of the valves under software control, with positional feedback from an 8-bit transducer. A test-rig comprising one hydraulic location pin together with an opposing spring loaded pin has demonstrated that such a pin arrangement can be controlled with a repeatability of +/-.00045'. In addition this test-rig has demonstrated that such a pin arrangement can be used to gauge and compensate for the dimensional error of the component held between the pins, by offsetting the pin datum positions to allow for the component error. A gauging repeatability of +/- 0.00015' was demonstrated. This work has led to the design and manufacture of an encapsulation die comprising ten such pins and the associated computer software. All aspects of the control software except blade gauging and positional data storage have been demonstrated. Work is now required to achieve the accuracy of control demonstrated by the single pin test-rig, with each of the ten pins in the encapsulation die. This would allow trials of the complete loading cycle to take place.

The application of aerial photography to surveys of potential disposal sites

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Dynamic Bayesian network for semantic place classification in mobile robotics

In this paper, the problem of semantic place categorization in mobile robotics is addressed by considering a time-based probabilistic approach called dynamic Bayesian mixture model (DBMM), which is an improved variation of the dynamic Bayesian network. More specifically, multi-class semantic classification is performed by a DBMM composed of a mixture of heterogeneous base classifiers, using geometrical features computed from 2D laserscanner data, where the sensor is mounted on-board a moving robot operating indoors. Besides its capability to combine different probabilistic classifiers, the DBMM approach also incorporates time-based (dynamic) inferences in the form of previous class-conditional probabilities and priors. Extensive experiments were carried out on publicly available benchmark datasets, highlighting the influence of the number of time-slices and the effect of additive smoothing on the classification performance of the proposed approach. Reported results, under different scenarios and conditions, show the effectiveness and competitive performance of the DBMM.