Example of International Journal of Image and Data Fusion format
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Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format
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Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format Example of International Journal of Image and Data Fusion format
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open access Open Access

International Journal of Image and Data Fusion — Template for authors

Publisher: Taylor and Francis
Categories Rank Trend in last 3 yrs
Earth and Planetary Sciences (all) #50 of 186 down down by 29 ranks
Computer Science Applications #285 of 693 down down by 149 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 65 Published Papers | 212 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 30/06/2020
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Related Journals

open access Open Access
recommended Recommended

Taylor and Francis

Quality:  
High
CiteRatio: 6.6
SJR: 0.813
SNIP: 1.434
open access Open Access

IEEE

Quality:  
High
CiteRatio: 6.4
SJR: 0.786
SNIP: 2.027
open access Open Access

Taylor and Francis

Quality:  
High
CiteRatio: 4.1
SJR: 0.694
SNIP: 0.72
open access Open Access
recommended Recommended

Taylor and Francis

Quality:  
High
CiteRatio: 5.9
SJR: 0.972
SNIP: 1.349

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

3.3

CiteRatio for International Journal of Image and Data Fusion from 2016 - 2020
Year Value
2020 3.3
2019 3.3
2018 3.6
2017 4.4
2016 4.1
graph view Graph view
table view Table view

0.378

21% from 2019

SJR for International Journal of Image and Data Fusion from 2016 - 2020
Year Value
2020 0.378
2019 0.478
2018 0.674
2017 0.697
2016 0.836
graph view Graph view
table view Table view

0.873

4% from 2019

SNIP for International Journal of Image and Data Fusion from 2016 - 2020
Year Value
2020 0.873
2019 0.908
2018 0.955
2017 1.291
2016 1.624
graph view Graph view
table view Table view

insights Insights

  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has decreased by 21% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 4% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
International Journal of Image and Data Fusion

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Taylor and Francis

International Journal of Image and Data Fusion

Approved by publishing and review experts on SciSpace, this template is built as per for International Journal of Image and Data Fusion formatting guidelines as mentioned in Taylor and Francis author instructions. The current version was created on 29 Jun 2020 and has been used by 822 authors to write and format their manuscripts to this journal.

Earth and Planetary Sciences

i
Last updated on
29 Jun 2020
i
ISSN
1947-9832
i
Impact Factor
High - 1.625
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
Taylor and Francis Custom Citation
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Citation Type
Numbered
[25]
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Bibliography Example
Blonder GE, Tinkham M, Klapwijk TM. Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys Rev B. 1982; 25(7):4515–4532. Available from: 10.1103/PhysRevB.25.4515.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1080/19479830903561985
Multi-sensor image fusion for pansharpening in remote sensing
Manfred Ehlers1, Sascha Klonus1, Pär Johan Åstrand, Pablo Rosso1

Abstract:

The main objective of this article is quality assessment of pansharpening fusion methods. Pansharpening is a fusion technique to combine a panchromatic image of high spatial resolution with multispectral image data of lower spatial resolution to obtain a high-resolution multispectral image. During this process, the significan... The main objective of this article is quality assessment of pansharpening fusion methods. Pansharpening is a fusion technique to combine a panchromatic image of high spatial resolution with multispectral image data of lower spatial resolution to obtain a high-resolution multispectral image. During this process, the significant spectral characteristics of the multispectral data should be preserved. For images acquired at the same time by the same sensor, most algorithms for pansharpening provide very good results, i.e. they retain the high spatial resolution of the panchromatic image and the spectral information from the multispectral image (single-sensor, single-date fusion). For multi-date, multi-sensor fusion, however, these techniques can still create spatially enhanced data sets, but usually at the expense of the spectral consistency. In this study, eight different methods are compared for image fusion to show their ability to fuse multitemporal and multi-sensor image data. A series of eight multitemp... read more read less

Topics:

Image fusion (67%)67% related to the paper, Multispectral image (60%)60% related to the paper, Multispectral pattern recognition (60%)60% related to the paper, Image resolution (57%)57% related to the paper, Panchromatic film (56%)56% related to the paper
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244 Citations
Journal Article DOI: 10.1080/19479832.2016.1188860
Use of mobile LiDAR in road information inventory: a review
Haiyan Guan1, Jonathan Li2, Shuang Cao1, Yongtao Yu

Abstract:

Mobile LiDAR technology is currently one of the attractive topics in the fields of remote sensing and laser scanning. Mobile LiDAR enables a rapid collection of enormous volumes of highly dense, irregularly distributed, accurate geo-referenced data, in the form of three-dimensional (3D) point clouds. This technology has been ... Mobile LiDAR technology is currently one of the attractive topics in the fields of remote sensing and laser scanning. Mobile LiDAR enables a rapid collection of enormous volumes of highly dense, irregularly distributed, accurate geo-referenced data, in the form of three-dimensional (3D) point clouds. This technology has been gaining popularity in the recognition of roads and road-scene objects. A thorough review of available literature is conducted to inform the advancements in mobile LiDAR technologies and their applications in road information inventory. The literature review starts with a brief overview of mobile LiDAR technology, including system components, direct geo-referencing, data error analysis and geometrical accuracy validation. Then, this review presents a more in-depth description of current mobile LiDAR studies on road information inventory, including the detection and extraction of road surfaces, small structures on the road surfaces and pole-like objects. Finally, the challenges ... read more read less

Topics:

Lidar (60%)60% related to the paper
162 Citations
Journal Article DOI: 10.1080/19479832.2013.868372
Current situation and needs of change detection techniques
Dengsheng Lu1, Guiying Li1, Emilio F. Moran1

Abstract:

Research on change detection techniques has long been an active topic and many techniques have been developed. In reality, change detection is a comprehensive procedure that requires careful consideration of many factors such as the nature of change detection problems, image preprocessing, selection of suitable variables and ... Research on change detection techniques has long been an active topic and many techniques have been developed. In reality, change detection is a comprehensive procedure that requires careful consideration of many factors such as the nature of change detection problems, image preprocessing, selection of suitable variables and algorithms. This paper briefly overviews the major steps involved in a change detection, summarises major change detection methods, discusses the impacts of scales and complexity of study areas on the selection of remote-sensing data and change detection algorithms and finally discusses the needs of developing new change detection methods. As high spatial resolution images are easily available in the past decade, texture- and object-based methods become valuable to improve change detection performance. At national and global scales, coarse spatial resolution satellite images such as MODIS become important data sources for rapidly detecting land-cover change, but results have high unce... read more read less

Topics:

Change detection (64%)64% related to the paper
132 Citations
Journal Article DOI: 10.1080/19479832.2011.605397
Tracking dynamic land-use change using spatially explicit Markov Chain based on cellular automata: the case of Tehran
Jamal Jokar Arsanjani1, Wolfgang Kainz1, Alijafar Mousivand2

Abstract:

The main objective of this research is to, first, monitor urban sprawl in the metropolis of Tehran and, second, to assess the CA–Markov model in the simulation of land-use change. Land-use changes generally occur in developing countries through new building construction. The rapid pace of this development has brought forward ... The main objective of this research is to, first, monitor urban sprawl in the metropolis of Tehran and, second, to assess the CA–Markov model in the simulation of land-use change. Land-use changes generally occur in developing countries through new building construction. The rapid pace of this development has brought forward a number of research activities involving new applications for modelling this phenomenon. In this research, urban sprawl is examined in the urban fringe of Tehran and, subsequently, the CA–Markov model is implemented in order to evaluate the model. The CA–Markov model is a spatially explicit model for land-change modelling, which has not been implemented very frequently to track urban expansion. This model, however, which is an integrated module of both cellular automata and Markov Chain models, predicts forthcoming changes over time, based on the past use of land in the research area. Urban expansion between 1986 and 2006 was simulated through employing the model in the metropolis of... read more read less

Topics:

Urban sprawl (52%)52% related to the paper, Markov chain (51%)51% related to the paper
128 Citations
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12. Is International Journal of Image and Data Fusion's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for International Journal of Image and Data Fusion?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for International Journal of Image and Data Fusion. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In International Journal of Image and Data Fusion?

The 5 most common citation types in order of usage for International Journal of Image and Data Fusion are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

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Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in International Journal of Image and Data Fusion Endnote style according to Elsevier guidelines.

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