Geometric spectral accuracy of airborne remote sensing

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The geometric correction and registration of airborne line-scanned imagery for temporal thermal studies

This thesis begins by providing a review of techniques for interpreting the thermal response at the earth's surface acquired using remote sensing technology. Historic limitations in the precision with which imagery acquired from airborne platforms can be geometrically corrected and co-registered has meant that relatively little work has been carried out examining the diurnal variation of surface temperature over wide regions. Although emerging remote sensing systems provide the potential to register temporal image data within satisfactory levels of accuracy, this technology is still not widely available and does not address the issue of historic data sets which cannot be rectified using conventional parametric approaches. In overcoming these problems, the second part of this thesis describes the development of an alternative approach for rectifying airborne line-scanned imagery. The underlying assumption that scan lines within the imagery are straight greatly reduces the number of ground control points required to describe the image geometry. Furthermore, the use of pattern matching procedures to identify geometric disparities between raw line-scanned imagery and corresponding aerial photography enables the correction procedure to be almost fully automated. By reconstructing the raw image data on a truly line-by-line basis, it is possible to register the airborne line-scanned imagery to the aerial photography with an average accuracy of better than one pixel. Providing corresponding aerial photography is available, this approach can be applied in the absence of platform altitude information allowing multi-temporal data sets to be corrected and registered.

Evaluation of remote sensing for the detection of landfill gas and leachate in an urban environment

The technique of remote sensing provides a unique view of the earth's surface and considerable areas can be surveyed in a short amount of time. The aim of this project was to evaluate whether remote sensing, particularly using the Airborne Thematic Mapper (ATM) with its wide spectral range, was capable of monitoring landfill sites within an urban environment with the aid of image processing and Geographical Information Systems (GIS) methods. The regions under study were in the West Midlands conurbation and consisted of a large area in what is locally known as the Black Country containing heavy industry intermingled with residential areas, and a large single active landfill in north Birmingham. When waste is collected in large volumes it decays and gives off pollutants. These pollutants, landfill gas and leachate (a liquid effluent), are known to be injurious to vegetation and can cause stress and death. Vegetation under stress can exhibit a physiological change, detectable by the remote sensing systems used. The chemical and biological reactions that create the pollutants are exothermic and the gas and leachate, if they leave the waste, can be warmer than their surroundings. Thermal imagery from the ATM (daylight and dawn) and thermal video were obtained and used to find thermal anomalies on the area under study. The results showed that vegetation stress is not a reliable indicator of landfill gas migration, as sites within an urban environment have a cover too complex for the effects to be identified. Gas emissions from two sites were successfully detected by all the thermal imagery with the thermal ATM being the best. Although the results were somewhat disappointing, recent technical advancements in the remote sensing systems used in this project would allow geo-registration of ATM imagery taken on different occasions and the elimination of the effects of solar insolation.

The investigation of vegetation change using remote sensing to detect and monitor migration of landfill gas

Decomposition of domestic wastes in an anaerobic environment results in the production of landfill gas. Public concern about landfill disposal and particularly the production of landfill gas has been heightened over the past decade. This has been due in large to the increased quantities of gas being generated as a result of modern disposal techniques, and also to their increasing effect on modern urban developments. In order to avert diasters, effective means of preventing gas migration are required. This, in turn requires accurate detection and monitoring of gas in the subsurface. Point sampling techniques have many drawbacks, and accurate measurement of gas is difficult. Some of the disadvantages of these techniques could be overcome by assessing the impact of gas on biological systems. This research explores the effects of landfill gas on plants, and hence on the spectral response of vegetation canopies. Examination of the landfill gas/vegetation relationship is covered, both by review of the literature and statistical analysis of field data. The work showed that, although vegetation health was related to landfill gas, it was not possible to define a simple correlation. In the landfill environment, contribution from other variables, such as soil characteristics, frequently confused the relationship. Two sites are investigated in detail, the sites contrasting in terms of the data available, site conditions, and the degree of damage to vegetation. Gas migration at the Panshanger site was dominantly upwards, affecting crops being grown on the landfill cap. The injury was expressed as an overall decline in plant health. Discriminant analysis was used to account for the variations in plant health, and hence the differences in spectral response of the crop canopy, using a combination of soil and gas variables. Damage to both woodland and crops at the Ware site was severe, and could be easily related to the presence of gas. Air photographs, aerial video, and airborne thematic mapper data were used to identify damage to vegetation, and relate this to soil type. The utility of different sensors for this type of application is assessed, and possible improvements that could lead to more widespread use are identified. The situations in which remote sensing data could be combined with ground survey are identified. In addition, a possible methodology for integrating the two approaches is suggested.