Active Collection of Land Cover Sample Data from Geo-Tagged Web Texts Article Swipe
Dongyang Hou
,
Jun Chen
,
Hao Wu
,
Songnian Li
,
Feifei Chen
,
Weiwei Zhang Zhang
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.32920/14640141
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.32920/14640141
Sample data plays an important role in land cover (LC) map validation. Traditionally, they are collected through field survey or image interpretation, either of which is costly, labor-intensive and time-consuming. In recent years, massive geo-tagged texts are emerging on the web and they contain valuable information for LC map validation. However, this kind of special textual data has seldom been analyzed and used for supporting LC map validation. This paper examines the potential of geo-tagged web texts as a new cost-free sample data source to assist LC map validation and proposes an active data collection approach. The proposed approach uses a customized deep web crawler to search for geo-tagged web texts based on land cover-related keywords and string-based rules matching. A data transformation based on buffer analysis is then performed to convert the collected web texts into LC sample data. Using three provinces and three municipalities directly under the Central Government in China as study areas, geo-tagged web texts were collected to validate artificial surface class of China’s 30-meter global land cover datasets (GlobeLand30-2010). A total of 6283 geo-tagged web texts were collected at a speed of 0.58 texts per second. The collected texts about built-up areas were transformed into sample data. User’s accuracy of 82.2% was achieved, which is close to that derived from formal expert validation. The preliminary results show that geo-tagged web texts are valuable ancillary data for LC map validation and the proposed approach can improve the efficiency of sample data collection.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.32920/14640141
- https://rshare.library.torontomu.ca/articles/journal_contribution/Active_Collection_of_Land_Cover_Sample_Data_from_Geo-Tagged_Web_Texts/14640141/1/files/28116570.pdf
- OA Status
- gold
- References
- 49
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4246344628
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4246344628Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.32920/14640141Digital Object Identifier
- Title
-
Active Collection of Land Cover Sample Data from Geo-Tagged Web TextsWork title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2021Year of publication
- Publication date
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2021-05-21Full publication date if available
- Authors
-
Dongyang Hou, Jun Chen, Hao Wu, Songnian Li, Feifei Chen, Weiwei Zhang ZhangList of authors in order
- Landing page
-
https://doi.org/10.32920/14640141Publisher landing page
- PDF URL
-
https://rshare.library.torontomu.ca/articles/journal_contribution/Active_Collection_of_Land_Cover_Sample_Data_from_Geo-Tagged_Web_Texts/14640141/1/files/28116570.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://rshare.library.torontomu.ca/articles/journal_contribution/Active_Collection_of_Land_Cover_Sample_Data_from_Geo-Tagged_Web_Texts/14640141/1/files/28116570.pdfDirect OA link when available
- Concepts
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Web crawler, Sample (material), Computer science, Field (mathematics), Information retrieval, Land cover, Data collection, World Wide Web, Database, Data mining, Engineering, Land use, Civil engineering, Statistics, Chromatography, Pure mathematics, Mathematics, ChemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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49Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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