Geospatial Information Diffusion Technology Supporting by Background Data
In this paper, we express the initial concept of geospatial information diffusion supporting by background data, which plays a role as a bridge to diffuse the information carried by the observations, obtained from observed units, to gap units. The self-learning discrete regression, based on the mult...
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| Format: | Article |
| Language: | English |
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Society for Risk Analysis - China
2019-04-01
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| Series: | Journal of Risk Analysis and Crisis Response (JRACR) |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/125905743/view |
| _version_ | 1818533815197368320 |
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| author | Chongfu Huang |
| author_facet | Chongfu Huang |
| author_sort | Chongfu Huang |
| collection | DOAJ |
| description | In this paper, we express the initial concept of geospatial information diffusion supporting by background data, which plays a role as a bridge to diffuse the information carried by the observations, obtained from observed units, to gap units. The self-learning discrete regression, based on the multivariate normal diffusion, is suggested to supplement incomplete geospatial data to be complete. The suggested method has obvious advantages over the geographic weighted regression and the artificial neural network for inferring the observations in gap units |
| first_indexed | 2024-12-11T18:03:43Z |
| format | Article |
| id | doaj.art-0e5a00483b984b05a00c3ae7058d6c81 |
| institution | Directory Open Access Journal |
| issn | 2210-8505 |
| language | English |
| last_indexed | 2024-12-11T18:03:43Z |
| publishDate | 2019-04-01 |
| publisher | Society for Risk Analysis - China |
| record_format | Article |
| series | Journal of Risk Analysis and Crisis Response (JRACR) |
| spelling | doaj.art-0e5a00483b984b05a00c3ae7058d6c812022-12-22T00:55:49ZengSociety for Risk Analysis - ChinaJournal of Risk Analysis and Crisis Response (JRACR)2210-85052019-04-019110.2991/jracr.b.190328.001Geospatial Information Diffusion Technology Supporting by Background DataChongfu HuangIn this paper, we express the initial concept of geospatial information diffusion supporting by background data, which plays a role as a bridge to diffuse the information carried by the observations, obtained from observed units, to gap units. The self-learning discrete regression, based on the multivariate normal diffusion, is suggested to supplement incomplete geospatial data to be complete. The suggested method has obvious advantages over the geographic weighted regression and the artificial neural network for inferring the observations in gap unitshttps://www.atlantis-press.com/article/125905743/viewgeographic unitbackground datainformation diffusionnormal diffusionself-learning discrete regression |
| spellingShingle | Chongfu Huang Geospatial Information Diffusion Technology Supporting by Background Data Journal of Risk Analysis and Crisis Response (JRACR) geographic unit background data information diffusion normal diffusion self-learning discrete regression |
| title | Geospatial Information Diffusion Technology Supporting by Background Data |
| title_full | Geospatial Information Diffusion Technology Supporting by Background Data |
| title_fullStr | Geospatial Information Diffusion Technology Supporting by Background Data |
| title_full_unstemmed | Geospatial Information Diffusion Technology Supporting by Background Data |
| title_short | Geospatial Information Diffusion Technology Supporting by Background Data |
| title_sort | geospatial information diffusion technology supporting by background data |
| topic | geographic unit background data information diffusion normal diffusion self-learning discrete regression |
| url | https://www.atlantis-press.com/article/125905743/view |
| work_keys_str_mv | AT chongfuhuang geospatialinformationdiffusiontechnologysupportingbybackgrounddata |