Abstract
This paper studies the concepts of city-country combinative area (CCCA), and how to apply data cleaning, and data mining in land use control in CCCA. A new data cleaning method named as Vectorizing Character-string and Matching Number (VCMN) is advanced, which can integrates multi-origin data. It is suggested that the control points be acquired with GPS-supported aerial triangulation, CCCA images be dealt with digital photogrammetry system before image databases come into being. Then all related land databases can be rebuilt up a data warehouse after data cleaning. In the network, online data mining is carried out in the light of constraint conditions. Finally, some Wuhan City CCCA knowledge is discovered with rough set.
| Original language | English |
|---|---|
| Pages (from-to) | 1677-1683 |
| Number of pages | 7 |
| Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Volume | 33 |
| Publication status | Published - 2000 |
| Externally published | Yes |
| Event | 19th International Congress for Photogrammetry and Remote Sensing, ISPRS 2000 - Amsterdam, Netherlands Duration: 16 Jul 2000 → 23 Jul 2000 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 15 Life on Land
Keywords
- City-country combinative area
- Data cleaning
- Data mining
- Land use control
- Photogrammetry
- Rough set
- Vectorizing character-string and matching number
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