International Journal of Image and Data Fusion

International Journal of Image and Data Fusion
影响因子:
1.8
ISSN:
print: 1947-9832
on-line: 1947-9824
研究领域:
REMOTE SENSING
自引率:
0.00%
Gold OA文章占比:
7.84%
原创研究文献占比:
100.00%
SCI收录类型:
Emerging Sources Citation Index (ESCI) || Scopus (CiteScore)
期刊介绍英文:
International Journal of Image and Data Fusion provides a single source of information for all aspects of image and data fusion methodologies, developments, techniques and applications. Image and data fusion techniques are important for combining the many sources of satellite, airborne and ground based imaging systems, and integrating these with other related data sets for enhanced information extraction and decision making. Image and data fusion aims at the integration of multi-sensor, multi-temporal, multi-resolution and multi-platform image data, together with geospatial data, GIS, in-situ, and other statistical data sets for improved information extraction, as well as to increase the reliability of the information. This leads to more accurate information that provides for robust operational performance, i.e. increased confidence, reduced ambiguity and improved classification enabling evidence based management. The journal welcomes original research papers, review papers, shorter letters, technical articles, book reviews and conference reports in all areas of image and data fusion including, but not limited to, the following aspects and topics: • Automatic registration/geometric aspects of fusing images with different spatial, spectral, temporal resolutions; phase information; or acquired in different modes • Pixel, feature and decision level fusion algorithms and methodologies • Data Assimilation: fusing data with models • Multi-source classification and information extraction • Integration of satellite, airborne and terrestrial sensor systems • Fusing temporal data sets for change detection studies (e.g. for Land Cover/Land Use Change studies) • Image and data mining from multi-platform, multi-source, multi-scale, multi-temporal data sets (e.g. geometric information, topological information, statistical information, etc.).
CiteScore:
CiteScoreSJRSNIPCiteScore排名
5.00.4730.948
学科
排名
百分位
大类:Earth and Planetary Sciences
小类:General Earth and Planetary Sciences
45 / 195
77%
大类:Computer Science
小类:Computer Science Applications
312 / 817
61%
发文信息
WOS期刊分区
学科分类
Q3REMOTE SENSING
历年影响因子
2022年2.3000
2023年1.8000
历年发表
2012年23
2013年25
2014年22
2015年25
2016年19
2017年21
2018年16
2019年18
2020年26
2021年26
2022年10
投稿信息
出版国家(地区):
United Kingdom
出版商:
Taylor & Francis

International Journal of Image and Data Fusion - 最新文献

CNN-based plant disease recognition using colour space models

Pub Date : 2024-01-05 DOI: 10.1080/19479832.2023.2300335 Shubham Nain, Neha Mittal, Madasu Hanmandlu

Building classification extraction from remote sensing images combining hyperpixel and maximum interclass variance

Pub Date : 2024-01-04 DOI: 10.1080/19479832.2023.2284783 Hongning Qin, Zili Li

PolSAR image classification based on TCN deep learning: a case study of greater Cairo

Pub Date : 2024-01-01 DOI: 10.1080/19479832.2023.2299476 Rabab R. Mohammad, Ahmed Hagag, E. El-Dahshan, Ahmed E. Gaber, Ashraf Yahia
查看全部
免责声明:
本页显示期刊或杂志信息,仅供参考学习,不是任何期刊杂志官网,不涉及出版事务,特此申明。如需出版一切事务需要用户自己向出版商联系核实。若本页展示内容有任何问题,请联系我们,邮箱:info@booksci.cn,我们会认真核实处理。
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信