An exploratory analysis of usability of Flickr tags for land use/land cover attribution
This study explored the land use/land cover (LULC) separability by the machine-generated and user-generated Flickr photo tags (i.e. the auto-tags and the user-tags, respectively), based on an authoritative LULC dataset for San Diego County in the United States. Ten types of LULCs were derived from t...
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| Main Authors: | , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
08 Jan 2019
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| In: |
Geo-spatial information science
Year: 2019, Volume: 22, Issue: 1, Pages: 12-22 |
| ISSN: | 1993-5153 |
| DOI: | 10.1080/10095020.2018.1560044 |
| Online Access: | Resolving-System, kostenfrei, Volltext: https://doi.org/10.1080/10095020.2018.1560044 Verlag, kostenfrei, Volltext: https://www.tandfonline.com/doi/full/10.1080/10095020.2018.1560044 
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| Author Notes: | Yingwei Yan, Michael Schultz and Alexander Zipf |
| Summary: | This study explored the land use/land cover (LULC) separability by the machine-generated and user-generated Flickr photo tags (i.e. the auto-tags and the user-tags, respectively), based on an authoritative LULC dataset for San Diego County in the United States. Ten types of LULCs were derived from the authoritative dataset. It was observed that certain types of the reclassified LULCs had abundant tags (e.g. the parks) or a high tag density (e.g. the commercial lands), compared with the less populated ones (e.g. the agricultural lands). Certain highly weighted terms of the tags derived based on a term frequency-inverse document frequency weighting scheme were helpful for identifying specific types of the LULCs, especially for the commercial recreation lands (e.g. the zoos). However, given the 10 sets of tags retrieved from the corresponding 10 types of LULCs, one set of tags (all the tags located at one specific type of the LULCs) could not fully delineate the corresponding LULC due to semantic overlaps, according to a latent semantic analysis. |
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| Item Description: | Gesehen am 19.02.2026 |
| Physical Description: | Online Resource |
| ISSN: | 1993-5153 |
| DOI: | 10.1080/10095020.2018.1560044 |