Enhancing the spatial resolution of Landsat data for mapping urban areas
Detailed land cover information is crucial for mapping and managing complex urban environments across local and regional scales (Zhou and Qiu, 2015). This thesis is based on the proposition that spatial resolution is the most influential factor when mapping complex urban environments, compared to im...
| Main Author: | |
|---|---|
| Format: | Thesis (University of Nottingham only) |
| Language: | English |
| Published: |
2017
|
| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/43462/ |
| _version_ | 1848796693514944512 |
|---|---|
| author | Momeni, Rahman |
| author_facet | Momeni, Rahman |
| author_sort | Momeni, Rahman |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Detailed land cover information is crucial for mapping and managing complex urban environments across local and regional scales (Zhou and Qiu, 2015). This thesis is based on the proposition that spatial resolution is the most influential factor when mapping complex urban environments, compared to imagery’s spectral properties and type of classifier. As such, the modern “very high resolution” sensors (i.e., WorldView-2) offer a significant advantage for mapping, however using such imagery is a costly and resource-hungry approach. The coarser resolution of Landsat data (30m) is the key limitation for using these data, yet they are free and now have a temporal legacy. This doctoral research assesses the potential of using an approach that enhances the spatial resolution of Landsat data for urban land cover mapping, namely sparse representation. Focusing on the land cover mapping of the urban area of Nottingham, UK, and after establishing the superior role of spatial resolution on the accuracy of that mapping, this research demonstrates the potential of this approach. Moreover, some parameters around its use are established, in particular, the transferability of this method over space and time. It should be noted the potential of sparse representation can be even more significant by using finer spatial resolution products (i.e., Sentinel-2 and SPOT with 10m). This reaffirmed the importance of the spatial resolution for urban land cover mapping. Then it presents the sparse representation as a successful method to enhance the spatial resolution of Landsat data for urban land cover mapping. |
| first_indexed | 2025-11-14T19:52:02Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-43462 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T19:52:02Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-434622025-02-28T13:48:33Z https://eprints.nottingham.ac.uk/43462/ Enhancing the spatial resolution of Landsat data for mapping urban areas Momeni, Rahman Detailed land cover information is crucial for mapping and managing complex urban environments across local and regional scales (Zhou and Qiu, 2015). This thesis is based on the proposition that spatial resolution is the most influential factor when mapping complex urban environments, compared to imagery’s spectral properties and type of classifier. As such, the modern “very high resolution” sensors (i.e., WorldView-2) offer a significant advantage for mapping, however using such imagery is a costly and resource-hungry approach. The coarser resolution of Landsat data (30m) is the key limitation for using these data, yet they are free and now have a temporal legacy. This doctoral research assesses the potential of using an approach that enhances the spatial resolution of Landsat data for urban land cover mapping, namely sparse representation. Focusing on the land cover mapping of the urban area of Nottingham, UK, and after establishing the superior role of spatial resolution on the accuracy of that mapping, this research demonstrates the potential of this approach. Moreover, some parameters around its use are established, in particular, the transferability of this method over space and time. It should be noted the potential of sparse representation can be even more significant by using finer spatial resolution products (i.e., Sentinel-2 and SPOT with 10m). This reaffirmed the importance of the spatial resolution for urban land cover mapping. Then it presents the sparse representation as a successful method to enhance the spatial resolution of Landsat data for urban land cover mapping. 2017-07-19 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/43462/1/R.Momeni%20Doctoral%20Thesis%20June%202017.pdf Momeni, Rahman (2017) Enhancing the spatial resolution of Landsat data for mapping urban areas. PhD thesis, University of Nottingham. spatial resolution mapping remote sensing landsat urban geography |
| spellingShingle | spatial resolution mapping remote sensing landsat urban geography Momeni, Rahman Enhancing the spatial resolution of Landsat data for mapping urban areas |
| title | Enhancing the spatial resolution of Landsat data for mapping urban areas |
| title_full | Enhancing the spatial resolution of Landsat data for mapping urban areas |
| title_fullStr | Enhancing the spatial resolution of Landsat data for mapping urban areas |
| title_full_unstemmed | Enhancing the spatial resolution of Landsat data for mapping urban areas |
| title_short | Enhancing the spatial resolution of Landsat data for mapping urban areas |
| title_sort | enhancing the spatial resolution of landsat data for mapping urban areas |
| topic | spatial resolution mapping remote sensing landsat urban geography |
| url | https://eprints.nottingham.ac.uk/43462/ |