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Digital image pre-processing and processing, including advanced processing techniques. Field data collection, image classification, and image enhancement. Students will produce a resource map and critically evaluate its accuracy based upon literature searches and field checks.
The increasing number of imaging sensors and platforms offer new exiting capabilities to observe and characterise our environment. Dealing with imagery requires a specific set of skills that are addressed in this paper. This paper also provides an opportunity to gain practical experience with various types of imagery and to complete of a comprehensive research project involving the use of images.
|Paper title||Resource Mapping and Image Processing|
|Teaching period||Not offered in 2021, expected to be offered in 2022 (On campus)|
|Domestic Tuition Fees (NZD)||$1,247.55|
|International Tuition Fees (NZD)||$5,305.26|
- SURV 309 or SURV 318
- SURV 413, SURV 424
- Suitable for graduates and professionals of all disciplines with initial knowledge
of remote sensing technologies and interested in getting advanced knowledge and experience
in image processing techniques
This paper is offered at the 500-level specifically to support postgraduate students aiming at using remote sensing in their research, as well as professionals seeking to gain new skills in geospatial sciences.
- More information link
- View more information about remote sensing and photogrammetry on the School of Surveying's website
- Teaching staff
- Convenor and Lecturer: Dr Pascal Sirguey
- Paper Structure
- Generally based in the context of remote sensing, this paper is aimed at providing
an extended knowledge of image processing techniques used for the mapping of earth
resources. It includes classic methods of pre-processing (e.g. gap-filling, calibration,
geometric and radiometric correction), image enhancement (e.g. radiometric, spatial,
multispectral enhancement, principal component analysis) and image classification
(unsupervised and supervised), as well as advanced processing techniques (e.g. multispectral
image fusion, spectral unmixing, fuzzy and object-orientated classification). The
methodology for fieldwork, sampling, ground-truthing and accuracy assessment of the
final resource maps is addressed to provide students with sufficient knowledge towards
the completion of deliverables with a high-quality standard.
Image enhancement and manipulation techniques will be applied and analysed by the student to produce a resource map and critically evaluate its accuracy based upon a literature review and personal experiences.
- Teaching Arrangements
- The theoretical content of this paper is addressed over two hours of lectures weekly.
Practical experience is gained during 11 practical sessions in a well-equipped computer laboratory, whereby students will be asked to carry out a research-led project that relies on imagery and image processing techniques. This is a major component of the paper.
- Richards and Jia (2006). Remote sensing digital image analysis. An introduction. 4th Edition, Springer-Verlag, 363pp. (electronic edition available online from the Dunedin Campus; older editions are available at the library)
- Graduate Attributes Emphasised
- Global perspective, Interdisciplinary perspective, Lifelong learning, Scholarship,
Communication, Critical thinking, Environmental literacy, Information literacy, Research,
View more information about Otago's graduate attributes.
- Learning Outcomes
- Students who successfully complete the paper will
- Develop an extended understanding of image processing techniques
- Gain the capacity to design an appropriate image processing protocol according to a specific problematic
- Produce a thematic map from imagery
- Be able to evaluate critically the accuracy of mapping outputs
- Be able to deliver the results in a professional manner