Example of Forests format
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Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format
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Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format Example of Forests format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
open access Open Access

Forests — Template for authors

Categories Rank Trend in last 3 yrs
Forestry #34 of 142 down down by 3 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 3760 Published Papers | 12260 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 04/06/2020
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Related Journals

open access Open Access

NRC Research Press

Quality:  
High
CiteRatio: 3.6
SJR: 0.677
SNIP: 0.885
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Springer

Quality:  
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CiteRatio: 3.7
SJR: 1.001
SNIP: 1.212
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Elsevier

Quality:  
High
CiteRatio: 6.5
SJR: 1.132
SNIP: 1.435
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 7.5
SJR: 1.668
SNIP: 1.908

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

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

2.221

5% from 2018

Impact factor for Forests from 2016 - 2019
Year Value
2019 2.221
2018 2.116
2017 1.956
2016 1.951
graph view Graph view
table view Table view

3.3

22% from 2019

CiteRatio for Forests from 2016 - 2020
Year Value
2020 3.3
2019 2.7
2018 2.6
2017 2.7
2016 2.3
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 5% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 22% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

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.

0.676

4% from 2019

SJR for Forests from 2016 - 2020
Year Value
2020 0.676
2019 0.652
2018 0.734
2017 0.812
2016 0.686
graph view Graph view
table view Table view

0.953

1% from 2019

SNIP for Forests from 2016 - 2020
Year Value
2020 0.953
2019 0.941
2018 0.973
2017 1.018
2016 0.912
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 4% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 1% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
Forests

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Multidisciplinary Digital Publishing Institute

Forests

Forests (ISSN 1999-4907) is an international and cross-disciplinary scholarly journal of forestry and forest ecology. It publishes research papers, short communications and review papers. There is no restriction on the length of the papers. Our aim is to encourage scientists t...... Read More

Forest engineering

i
Last updated on
03 Jun 2020
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ISSN
1999-4907
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Impact Factor
High - 1.951
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Acceptance Rate
Not provided
i
Frequency
Not provided
i
Open Access
No
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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
MDPI Custom Citation
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Citation Type
Numbered
[25]
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Bibliography Example
Blonder, G.E.; Tinkham, M.; Klapwijk, T.M. Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B 1982, 25, 4515–4532.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.3390/F7030062
Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (SfM) Point Clouds
07 Mar 2016 - Forests

Abstract:

This study investigates the potential of unmanned aerial vehicles (UAVs) to measure and monitor structural properties of forests. Two remote sensing techniques, airborne laser scanning (ALS) and structure from motion (SfM) were tested to capture three-dimensional structural information from a small multi-rotor UAV platform. A... This study investigates the potential of unmanned aerial vehicles (UAVs) to measure and monitor structural properties of forests. Two remote sensing techniques, airborne laser scanning (ALS) and structure from motion (SfM) were tested to capture three-dimensional structural information from a small multi-rotor UAV platform. A case study is presented through the analysis of data collected from a 30 × 50 m plot in a dry sclerophyll eucalypt forest with a spatially varying canopy cover. The study provides an insight into the capabilities of both technologies for assessing absolute terrain height, the horizontal and vertical distribution of forest canopy elements, and information related to individual trees. Results indicate that both techniques are capable of providing information that can be used to describe the terrain surface and canopy properties in areas of relatively low canopy closure. However, the SfM photogrammetric technique underperformed ALS in capturing the terrain surface under increasingly denser canopy cover, resulting in point density of less than 1 ground point per m2 and mean difference from ALS terrain surface of 0.12 m. This shortcoming caused errors that were propagated into the estimation of canopy properties, including the individual tree height (root mean square error of 0.92 m for ALS and 1.30 m for SfM). Differences were also seen in the estimates of canopy cover derived from the SfM (50%) and ALS (63%) pointclouds. Although ALS is capable of providing more accurate estimates of the vertical structure of forests across the larger range of canopy densities found in this study, SfM was still found to be an adequate low-cost alternative for surveying of forest stands. read more read less

Topics:

Tree canopy (57%)57% related to the paper, Terrain (51%)51% related to the paper, Canopy (51%)51% related to the paper
View PDF
542 Citations
open accessOpen access Journal Article DOI: 10.3390/F3020332
Carbon Content of Tree Tissues: A Synthesis
Sean C. Thomas1, Adam R. Martin
19 Jun 2012 - Forests

Abstract:

Assessing the potential for forest carbon (C) capture and storage requires accurate assessments of C in live tree tissues. In the vast majority of local, regional, and global assessments, C content has been assumed to be 50% of tree biomass; however, recent studies indicate that this assumption is not accurate, with substanti... Assessing the potential for forest carbon (C) capture and storage requires accurate assessments of C in live tree tissues. In the vast majority of local, regional, and global assessments, C content has been assumed to be 50% of tree biomass; however, recent studies indicate that this assumption is not accurate, with substantial variation in C content among tree species as well as among tissue types. Here we conduct a comprehensive literature review to present a global synthesis of C content in tissues of live trees. We found a total of 253 species-specific stem wood C content records in 31 studies, and an additional 34 records of species with C content values of other tissues in addition to stem wood. In all biomes, wood C content varied widely across species ranging from 41.9–51.6% in tropical species, 45.7–60.7% in subtropical/Mediterranean species, and 43.4–55.6% in temperate/boreal species. Stem wood C content varied significantly as a function of biome and species type (conifer, angiosperm). Conifer species exhibited greater wood C content than angiosperm species (50.8 ± 0.7% (95% C.I.) and 47.7 ± 0.3%, respectively), a trend that was consistent among all biomes. Although studies have documented differences in C content among plant tissues, interspecific differences in stem wood appear to be of greater importance overall: among species, stem wood C content explained 37, 76, 48, 81, and 63% respectively of the variation in bark, branch, twig, coarse root, and fine root C content values, respectively. In each case, these intraspecific patterns approximated 1:1 linear relationships. Most published stem wood C content values (and all values for other tree tissues) are based on dried wood samples, and so neglect volatile C constituents that constitute on average 1.3–2.5% of total C in live wood. Capturing this volatile C fraction is an important methodological consideration for future studies. Our review, and associated data compilation, provides empirically supported wood read more read less
View PDF
361 Citations
open accessOpen access Journal Article DOI: 10.3390/F4040922
A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery
Jonathan Lisein1, Marc Pierrot-Deseilligny, Stéphanie Bonnet1, Philippe Lejeune1
06 Nov 2013 - Forests

Abstract:

The recent development of operational small unmanned aerial systems (UASs) opens the door for their extensive use in forest mapping, as both the spatial and temporal resolution of UAS imagery better suit local-scale investigation than traditional remote sensing tools. This article focuses on the use of combined photogrammetry... The recent development of operational small unmanned aerial systems (UASs) opens the door for their extensive use in forest mapping, as both the spatial and temporal resolution of UAS imagery better suit local-scale investigation than traditional remote sensing tools. This article focuses on the use of combined photogrammetry and “Structure from Motion” approaches in order to model the forest canopy surface from low-altitude aerial images. An original workflow, using the open source and free photogrammetric toolbox, MICMAC (acronym for Multi Image Matches for Auto Correlation Methods), was set up to create a digital canopy surface model of deciduous stands. In combination with a co-registered light detection and ranging (LiDAR) digital terrain model, the elevation of vegetation was determined, and the resulting hybrid photo/LiDAR canopy height model was compared to data from a LiDAR canopy height model and from forest inventory data. Linear regressions predicting dominant height and individual height from plot metrics and crown metrics showed that the photogrammetric canopy height model was of good quality for deciduous stands. Although photogrammetric reconstruction significantly smooths the canopy surface, the use of this workflow has the potential to take full advantage of the flexible revisit period of drones in order to refresh the LiDAR canopy height model and to collect dense multitemporal canopy height series. read more read less

Topics:

Tree canopy (55%)55% related to the paper, Forest inventory (54%)54% related to the paper, Lidar (53%)53% related to the paper, Photogrammetry (53%)53% related to the paper, Elevation (52%)52% related to the paper
View PDF
325 Citations
open accessOpen access Journal Article DOI: 10.3390/F5061481
Small Drones for Community-Based Forest Monitoring: An Assessment of Their Feasibility and Potential in Tropical Areas
Jaime Paneque-Gálvez1, Michael K. McCall, Brian M. Napoletano2, Serge A. Wich, Lian Pin Koh
24 Jun 2014 - Forests

Abstract:

Data gathered through community-based forest monitoring (CBFM) programs may be as accurate as those gathered by professional scientists, but acquired at a much lower cost and capable of providing more detailed data about the occurrence, extent and drivers of forest loss, degradation and regrowth at the community scale. In add... Data gathered through community-based forest monitoring (CBFM) programs may be as accurate as those gathered by professional scientists, but acquired at a much lower cost and capable of providing more detailed data about the occurrence, extent and drivers of forest loss, degradation and regrowth at the community scale. In addition, CBFM enables greater survey repeatability. Therefore, CBFM should be a fundamental component of national forest monitoring systems and programs to measure, report and verify (MRV) REDD+ activities. To contribute to the development of more effective approaches to CBFM, in this paper we assess: (1) the feasibility of using small, low-cost drones (i.e., remotely piloted aerial vehicles) in CBFM programs; (2) their potential advantages and disadvantages for communities, partner organizations and forest data end-users; and (3) to what extent their utilization, coupled with ground surveys and local ecological knowledge, would improve tropical forest monitoring. To do so, we reviewed the existing literature regarding environmental applications of drones, including forest monitoring, and drew on our own firsthand experience flying small drones to map and monitor tropical forests and training people to operate them. We believe that the utilization of small drones can enhance CBFM and that this approach is feasible in many locations throughout the tropics if some degree of external assistance and funding is provided to communities. We suggest that the use of small drones can help tropical communities to better manage and conserve their forests whilst benefiting partner organizations, governments and forest data end-users, particularly those engaged in forestry, biodiversity conservation and climate change mitigation projects such as REDD+. read more read less
View PDF
282 Citations
open accessOpen access Journal Article DOI: 10.3390/F4030518
The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning
26 Jun 2013 - Forests

Abstract:

Airborne Laser Scanning (ALS), also known as Light Detection and Ranging (LiDAR) enables an accurate three-dimensional characterization of vertical forest structure. ALS has proven to be an information-rich asset for forest managers, enabling the generation of highly detailed bare earth digital elevation models (DEMs) as well... Airborne Laser Scanning (ALS), also known as Light Detection and Ranging (LiDAR) enables an accurate three-dimensional characterization of vertical forest structure. ALS has proven to be an information-rich asset for forest managers, enabling the generation of highly detailed bare earth digital elevation models (DEMs) as well as estimation of a range of forest inventory attributes (including height, basal area, and volume). Recently, there has been increasing interest in the advanced processing of high spatial resolution digital airborne imagery to generate image-based point clouds, from which vertical information with similarities to ALS can be produced. Digital airborne imagery is typically less costly to acquire than ALS, is well understood by inventory practitioners, and in addition to enabling the derivation of height information, allows for visual interpretation of attributes that are currently problematic to estimate from ALS (such as species, health status, and maturity). At present, there are two limiting factors associated with the use of image-based point clouds. First, a DEM is required to normalize the image-based point cloud heights to aboveground heights; however DEMs with sufficient spatial resolution and vertical accuracy, particularly in forested areas, are usually only available from ALS data. The use of image-based point clouds may therefore be limited to those forest areas that already have an ALS-derived DEM. Second, image-based point clouds primarily characterize the outer envelope of the forest canopy, whereas ALS pulses penetrate the canopy and provide information on sub-canopy forest structure. The impact of these limiting factors on the estimation of forest inventory attributes has not been extensively researched and is not yet well understood. In this paper, we review the key similarities and differences between ALS data and image-based point clouds, summarize the results of current research related to the comparative use of these data for forest inventory attribute estimation, and highlight some outstanding research questions that should be addressed before any definitive recommendation can be made regarding the use of image-based point clouds for this application. read more read less

Topics:

Forest inventory (61%)61% related to the paper, Lidar (52%)52% related to the paper, Point cloud (50%)50% related to the paper
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278 Citations
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With SciSpace, you do not need a word template for Forests.

It automatically formats your research paper to Multidisciplinary Digital Publishing Institute formatting guidelines and citation style.

You can download a submission ready research paper in pdf, LaTeX and docx formats.

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Forests format uses MDPI Custom Citation citation style.

Automatically format and order your citations and bibliography in a click.

SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

1. Can I write Forests in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Forests guidelines and auto format it.

2. Do you follow the Forests guidelines?

Yes, the template is compliant with the Forests guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Forests?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Forests citation style.

4. Can I use the Forests templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Forests.

5. Can I use a manuscript in Forests that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Forests that you can download at the end.

6. How long does it usually take you to format my papers in Forests?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Forests.

7. Where can I find the template for the Forests?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Forests's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Forests's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Forests an online tool or is there a desktop version?

SciSpace's Forests is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Forests?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Forests?”

11. What is the output that I would get after using Forests?

After writing your paper autoformatting in Forests, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Forests'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 Forests?

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 Forests. 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 Forests?

The 5 most common citation types in order of usage for Forests are:.

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

15. How do I submit my article to the Forests?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Forests's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Forests in Endnote format?

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 Forests Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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