Joanne Poon

Spatial Information Generation from High-resolution Satellite Imagery

JoannePoon sq
University
University of Melbourne
Supervisor (Academic)
Prof Clive Fraser, University of Melbourne et al
Supervisor (Industry)
John Cazanis, Spatial Division, SKM
Projects
mysite
Employment
Senior Spatial Consultant, Technical Leader, Jacobs.
Thesis Abstract

Interest in new-generation high-resolution satellite imagery (HRSI) has surfaced due to recent developments in satellite technology and the potential attractive benefits for mapping. There are a number of HRSI characteristics ideally suited to topographic mapping applications, which were not previously available to medium-resolution satellite imagery (MRSI). These include improved interpretation of features based on shape and texture, as well as benefits of an agile sensor and subsequent along-track stereo acquisition aiding stereo interpretation. By determining the image resolution and quality of HRSI and the achievable accuracy of derived products we can infer its utility for topographic mapping applications.

The initial challenge of appropriate sensor orientation of HRSI has largely been solved in previous research. However, despite the positive reinforcements regarding the geopositioning potential of HRSI using various rigorous and non-rigorous sensor orientation models, the validation of these models does not extend past isolated point positioning. There are few comprehensive accuracy evaluations on the generation of metric HRSI products.

The resolution of and discernible detail within an image are critical factors involved in producing an image product that is fit for purpose, yet there are currently no comprehensive and widely accepted orthoimage resolution standards. There are numerous factors influencing image resolution and quality which must be considered. An image rating system standard which provides an assessment of image resolution and quality based on image content is proposed. This allows communication of resolution in an accessible way through image content and interpretability and provides a uniform reference for assessing image resolution; thus the utility of an image product can be inferred. The image rating standard proposed in this thesis is interoperable, independent of any imaging system or platform, and is sustainable to adapt to new technologies as they emerge.

The extent to which HRSI can contribute to metrically accurate geospatial information collection is tested by using orthoimages and single and multiple stereo-imagery to extract points, buildings and surfaces. The accuracy of the extracted features is compared to existing technologies, such as global positioning system (GPS), interferometric synthetic radar (InSAR) and light detection and ranging (LIDAR). Four test fields are used to assess the attainable accuracy in HRSI derived geospatial information products. Each test field possesses its own unique characteristic and they differ in sensor, product type, land cover, terrain features or elevation.

The attainment of 1:5000 ground measurement accuracy is possible with entry-level HRSI products; however, the image resolution and quality of the features may not be ideal for urban mapping, but rather semi-urban mapping. Developed countries with established mapping agencies focus on change detection and map updating. Aided by incessant advances in technology, they are spoilt with a range of data sources. Thus, HRSI can be used as a complementary tool in a suite of measurement technologies for ad hoc applications. 

However, HRSI may be of more practical consequence in remote areas of the world, where high costs associated with acquiring spatial information often translate to existing maps being either out-of-date or non existent. Therefore, we need to look towards information sources which can provide low cost and quick-delivery land information products, without compromising metric accuracy. HRSI allows generation of numerous spatial information products, such as geopositioning, surface models, orthoimages and feature extraction. While HRSI can be costly, particularly the acquisition of stereopairs, it does not assume existing infrastructure, such as equipment, mobilisation or complex processing abilities. Even with limited ground control, satellite imagery has the potential to vastly enhance mapping prospects.