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Editorial Remote Sensing Journal of MDPI: Current Progress and Future Vision

Prasad S. Thenkabail 1,2

1 Western Geographic Center (WGSC), United States Geological Survey, 2255 N Gemini Drive, Suite 316, Flagstaff, AZ 86001, USA; [email protected] 2 Editor-in-Chief, Remote Sensing Open Access Journal of MDPI

 Received: 21 July 2020; Accepted: 22 July 2020; Published: 30 July 2020 

1. Performance Parameters of Various Remote Sensing International Journals A comparison of various remote sensing, geoscience, and Geographic Information Systems (GIS) international journals is provided in Table1. There are five critical parameters to weigh the performance of the journals. These are (Table1):

A. Journal (JIF); B. Eigen Factor Score; C. Normalized Eigen Factor Score; D. Article Influence Score; and E. Total Cites.

The performance parameters for the year 2019 are listed in Table1. The journal ranked #1 for each parameter is highlighted in green (see each column in Table1). Remote Sensing of Environment (RSE) and the ISPRS Journal of Photogrammetry and Remote Sensing continue to lead the pack with impressive Journal Impact Factor (JIF) scores of 9.085 and 7.319, respectively. The IEEE Geoscience and Remote Sensing Magazine (JRSM) has an outstanding JIF of 13, the highest amongst the pack. However, relative to whopping 62,697 citations of RSE, JRSM has just 1304 citations or 2.8% of RSE (Table1). It demonstrates flaws in comparing a journal a very large number of papers to a journal publishing very few selective papers that are cited many times. The same flaw exists across several journals. For example, Remote Sensing in Ecology and Conservation has a JIF of 5 but has a meagre 440 citations (0.7% of RSE!). This is exactly why looking at a single factor like JIF is misleading. Remote Sensing Open Access Journal (OAJ) of MDPI, which has a JIF of 4.509, has a total number of citations of 36,083. Remote Sensing OAJ of MDPI ranks #1 amongst all remote sensing journals when scores (0.06661) and normalized Eigenfactor scores (8.1265) are considered. Eigenfactors are considered a “prestige” measure. It measures [1–4]:

A. The number of times an article published in the journal in past 5 years (2014–2018) is cited in © (JCR) (2019); B. Citations by taking into consideration which journals cite it. Highly cited journals are given higher weightage and less cited journals are given lesser weightage; and C. Citations by discounting references from one article in a journal to another article from the same journal. So, the journal self-citation is excluded from the Eigenfactor.

Remote Sens. 2020, 12, 2442; doi:10.3390/rs12152442 www.mdpi.com/journal/remotesensing Remote Sens. 2020, 12, 2442 2 of 9

Table 1. Critical remote sensing international journal performance parameters.

Journal Impact Eigenfactor Normalized Article Influence Total Cites Increase in Cites in Rank Full Journal Title C Factor A Score B Eigenfactor Score Score D 2019 2018 2019 Compared to 2018 1 IEEE Geoscience and Remote Sensing Magazine 13 0.00367 0.44774 2.996 1304 952 352 2 Remote Sensing of Environment 9.085 0.05724 6.984 2.111 62697 54482 8215 3 ISPRS Journal of Photogrammetry and Remote Sensing 7.319 0.0221 2.6965 1.799 13946 11576 2370 4 GIScience & Remote Sensing 5.965 0.00209 0.25605 0.795 1447 1183 264 5 IEEE Transactions on Geoscience and Remote Sensing 5.855 0.04926 6.0106 1.371 46565 43741 2824 6 Remote Sensing in Ecology and Conservation 5 0.00137 0.16745 Not Available 440 N/A- 7 Journal of Geodesy 4.806 0.00679 0.82872 1.332 6000 5092 908 International Journal of Applied Earth Observation and 8 4.65 0.01407 1.71709 1.166 9072 7384 1688 Geoinformation 9 Remote Sensing 4.509 0.06661 8.1265 0.927 36083 23567 12516 10 IEEE Geoscience and Remote Sensing Letters 3.833 0.02523 3.07858 0.901 13781 12217 1564 IEEE Journal of Selected Topics in Applied Earth 11 3.827 0.02805 3.42246 0.965 11579 9671 1908 Observations and Remote Sensing 12 Geocarto International 3.789 0.00239 0.29276 0.515 1908 1380 528 13 GPS Solutions 3.61 0.0051 0.623 0.859 3690 2871 819 14 International Journal of Digital Earth 3.097 0.00262 0.31982 0.678 1718 1512 206 15 International Journal of Remote Sensing 2.976 0.01385 1.68975 0.568 24676 22212 2464 16 European Journal of Remote Sensing 2.808 0.00166 0.20335 0.482 889 644 245 17 Remote Sensing Letters 2.298 0.004 0.48836 0.534 2075 1636 439 18 ISPRS International Journal of Geo-Information 2.239 0.00666 0.81371 0.396 3730 2196 1534 19 Canadian Journal of Remote Sensing 2.126 0.00186 0.22761 0.678 2465 2326 139 20 Photogrammetric Record 1.867 0.00069 0.08445 0.532 821 871 50 − 21 Navigation-Journal of the Institute of Navigation 1.7 0.00086 0.10557 0.42 741 650 91 22 Survey Review 1.66 0.00091 0.11126 0.295 752 618 134 23 Spatial Statistics 1.656 0.00336 0.41055 0.991 661 504 157 24 Journal of Spatial Science 1.405 0.00057 0.07054 0.391 356 356 0 PFG-Journal of Photogrammetry Remote Sensing and 25 1.395 0.00014 0.01821 0.275 61 39 22 Geoinformation Science 26 Journal of Applied Remote Sensing 1.36 0.00447 0.54547 0.272 2753 2521 232 27 Marine Geodesy 1.322 0.00096 0.11746 0.431 1084 1042 42 28 Radio Science 1.305 0.00334 0.40796 0.445 4888 5484 596 − 29 Photogrammetric and Remote Sensing 1.265 0.00335 0.40987 0.79 7000 7002 2 − 30 Journal of the Indian Society of Remote Sensing 0.997 0.00133 0.16248 0.188 1302 1013 289 Note: A = Journal Impact Factor: Number of times all the articles that are published in the last two years (i.e., 2017 and 2018) in a journal are cited this year (i.e., 2019) by any journal in the JCR divided by the total number of articles published. B = Eigenfactor score: The Eigenfactor Score calculation is based on the number of times articles from the journal published in the past five years have been cited in the JCR year (2019), but it also considers which journals have contributed these citations so that highly cited journals will influence the network more than lesser cited journals. References from one article in a journal to another article from the same journal are removed, so that Eigenfactor Scores are not influenced by journal self-citation. C = Normalized Eigenfactor: The Normalized Eigenfactor Score is the Eigenfactor score normalized, by rescaling the total number of journals in the JCR (2019) each year, so that the average journal has a score of 1. Journals can then be compared and influence measured by their score relative to 1. For example, Remote Sensing Journal of MDPI which has a normalized eigenfactor of 8.1265, means that the journal is 8.1265 times as influencial as the average journal in the Journal Citation Report (JRC). D = Article Influence Score: Measures the average influence per article of the papers published in the journal over the first five years after publication. Green color highlight indicates the rank 1 for each performance parameter. Credits for the definitions A,B,C,D above: References [1–4]. Remote Sens. 2020, 12, 2442 3 of 9

For the normalized Eigenfactor score, an average journal has a value of 1. A normalized Eigenfactor score of 8.1265 for Remote Sensing OAJ means that the journal is 8.1265 times as influential as the average journal in the JRC year (2019). The two next best performing journals after Remote Sensing in Eigenfactor and normalized Eigenfactor measures are Remote Sensing of Environment (0.05724, 6.984) andRemoteIEE Sens. Transactions 2020, 12, x FOR of Geoscience and Remote Sensing (0.04926, 6.0106). 3 of 10 The Eigenfactor score and the normalized Eigenfactor score increase with the number of articles The Eigenfactor score and the normalized Eigenfactor score increase with the number of articles published in a year. published in a year. The article influence score measures the average influence per article of the papers published The article influence score measures the average influence per article of the papers published in in the journal over the first five years after publication [1]. The difference is that the Eigenfactor the journal over the first five years after publication [1]. The difference is that the Eigenfactor score scoremeasures measures the total the totalinfluence influence of a journal, of a journal, and the and Article the Influence Article Influence Score takes Score into takesaccount into the account size theof size the ofjournal the journal [1]. The [ 1IEEE]. The GeoscienceIEEE Geoscience and Remote and Sensing Remote Magazine Sensing has Magazine the highesthas thearticle highest influence article influencescore of score 2.996 of of 2.996all remote of all sensing remote sensingjournals. journals. Many journals Many journalspublish very publish few veryarticles, few but articles, each article but each articlehas a has higher a higher article article influence influence score. For score. example, For example, in 2019, IEEE in 2019, GeoscienceIEEE Geoscienceand Remote andSensing Remote Magazine Sensing Magazinehad a totalhad acitation total citation number number of 1304, of which 1304, whichis just is2.07% just 2.07%of the of citations the citations of Remote of Remote Sensing Sensing of of Environment (62,697(62,697 citations), citations), 2.8% 2.8% of of the the citations citations of of IEEEIEEE Transactions Transactions of ofGeoscience Geoscience and and Remote Remote SensingSensing(46,565 (46,565 citations), citations), and and 3.61% 3.61% ofof thethe citations of of RemoteRemote Sensing Sensing OAJ OAJ ofof MDPI MDPI (36,083 (36,083 citations). citations). So,So, when when a journal a journal is extremely is extremely selective selective and publishes and publishes only very only high very impact high articles,impact manyarticles, parameters many likeparameters the Journal like Impact the Journal Factor Impact and Article Factor Influenceand Article Score Influence go up Score swiftly. go up swiftly. InIn terms terms of of total total citations citations (Table (Table1) 1) during during 2019, 2019, the the three three leading leading journals journals were were Remote Sensing of Environmentof Environment(62,697), (62,697),IEEE IEEE Transactions Transactions on Geoscience on Geoscience and Remote and Remote Sensing Sensing(46,565), (46,565), and Remote and Remote Sensing (36,083).Sensing In (36,083). this regard, In thisRemote regard, Sensing Remote OAJSensing of MDPI OAJ ofincreased MDPI increased its citations its citations by 12,516 by 12,516 in 2019 in (36,083) 2019 compared(36,083) compared to 2018 (23,567). to 2018 This(23,567). is the This highest is the increasehighest increase in the number in the number of citations of citations in a single in a single year by anyyear journal by any (Table journal1). (Table 1).

2.2. Remote Remote Sensing Sensing Open Open Access Access JournalJournal PublicationsPublications InIn 2019, 2019, 8381 8381 manuscripts manuscripts were were submitted submitted to toRemote Remote Sensing Sensing Open Open Access Access Journal Journalof of MDPI MDPI and and 3047 (36.35%)3047 (36.35%) of them of were them published were published (Figure (Figure1) after 1) a after rigorous a rigorous peer-review peer-review process. process. Compared Compared with with 2018, 2018, the number of submissions and publications in 2019 increased by 48.08% and 49.07%, the number of submissions and publications in 2019 increased by 48.08% and 49.07%, respectively. respectively. Among the publications in 2019, there were 2822 (90.89%) articles, 98 (3.16%) letters, 65 Among the publications in 2019, there were 2822 (90.89%) articles, 98 (3.16%) letters, 65 (2.09%) (2.09%) technical notes, and 53 (1.707%) reviews (Figure 2). The monthly publication number technical notes, and 53 (1.707%) reviews (Figure2). The monthly publication number increased from increased from 214 in January to 313 in December (Figure 3). 214 in January to 313 in December (Figure3).

FigureFigure 1. Number 1. Number of submissions of submissions and and publications publications in the in thepast past three three years years for the for theRemoteRemote Sensing Sensing Open Open Access JournalAccess of JournalMDPI. of MDPI.

RemoteRemote Sens. 2020 Sens., 202012, 2442, 12, x FOR PEER REVIEW 4 of 10 4 of 9 Remote Sens. 2020, 12, x FOR PEER REVIEW 4 of 10

Figure 2. Number of publication types in 2019 for the Remote Sensing Open Access Journal of MDPI. Figure 2. Number of publication types in 2019 for the Remote Sensing Open Access Journal of MDPI. Figure 2. Number of publication types in 2019 for the Remote Sensing Open Access Journal of MDPI.

Figure 3. Number of monthly submissions and publications in 2019 for the Remote Sensing Open Access JournalFigureof MDPI. 3. Number of monthly submissions and publications in 2019 for the Remote Sensing Open Access Journal of MDPI. FigureAuthors 3. Number originated of monthly from submissions 118 countries and publications/regions. in Figure2019 for4 the shows Remote theSensing top Open 10 countriesAccess /territories Journal of MDPI. based onAuthors the percentage originated of from author 118 distribution, countries/regions. including Figure China,4 shows the the USA,top 10 Germany, countries/territories Italy, the UK, based on the percentage of author distribution, including China, the USA, Germany, Italy, the UK, Spain,AuthorsRemote France, Sens. originated 2020 Canada,, 12, x fromFOR Australia, PEER 118 REVIEWcountr andies/regions. the Netherlands. Figure 4 shows China th ise at top the 10 top countries/territories of the list, at about 5 of 45.32%,10 Spain, France, Canada, Australia, and the Netherlands. China is at the top of the list, at about 45.32%, basedfollowed on the by percentage the USA atof 23.53%.author distribution, including China, the USA, Germany, Italy, the UK, followed by the USA at 23.53%. Spain, France, Canada, Australia, and the Netherlands. China is at the top of the list, at about 45.32%, followed by the USA at 23.53%.

Figure 4. Top 10 countries/territories based on the percentage of author distribution in 2018 vs. 2019 Figure 4. Top 10 countries/territories based on the percentage of author distribution in 2018 vs. 2019 for theforRemote the Remote Sensing Sensing Open Open Access Access Journal Journalof of MDPI.MDPI.

2.1. Publication Time As shown in Figure 5, the average publication time (APT, 44.4 days), median publication time (MPT, 42 days), and time from submission to first decision (TFD, 20 days) in 2019 were much shorter, so that innovative studies were published without delay, which helped with the dissemination of .

Figure 5. The average publication time (APT, blue), median publication time (MPT, red), and time from submission to first decision (TFD, green) in the past three years.

2.2. Special Issue (SI) In 2019, 451 SIs were set up, an increase of 45.95% compared with 2018 (Figure 6). Moreover, Figure 6 shows that the publication rate for SIs in 2019 was 71.02%, keeping a similar rate as 2018, as SIs were still the main sources of publications. All SIs can be accessed at https://www.mdpi.com/journal/remotesensing/special_issues. Inviting top researchers to edit Special Issues has been very productive and has attracted a large number of researchers looking to publish their research in a top-quality journal expeditiously.

Remote Sens. 2020, 12, x FOR PEER REVIEW 5 of 10

Remote Sens.Figure2020, 124. ,Top 2442 10 countries/territories based on the percentage of author distribution in 2018 vs. 2019 5 of 9 for the Remote Sensing Open Access Journal of MDPI.

2.1. Publication2.1. Publication Time Time As shownAs shown in Figure in Figure5, the5, the average average publication publication time (APT, (APT, 44.4 44.4 days), days), median median publication publication time (MPT, time (MPT, 42 days), and time from submission to first decision (TFD, 20 days) in 2019 were much shorter, so that 42 days), and time from submission to first decision (TFD, 20 days) in 2019 were much shorter, so that innovative studies were published without delay, which helped with the dissemination of research. innovative studies were published without delay, which helped with the dissemination of research.

Figure 5. The average publication time (APT, blue), median publication time (MPT, red), and time from Figure 5. The average publication time (APT, blue), median publication time (MPT, red), and time submission to first decision (TFD, green) in the past three years. from submission to first decision (TFD, green) in the past three years. 2.2. Special Issue (SI) 2.2. Special Issue (SI) In 2019,In 2019, 451 451 SIs SIs were were set set up, up, an an increase increase of 45.95% 45.95% compared compared with with 2018 2018 (Figure (Figure 6). Moreover,6). Moreover, FigureFigure6 shows 6 shows that that the publicationthe publication rate rate for for SIs SIs in in 2019 2019 was was 71.02%, 71.02%, keepingkeeping a similar rate rate as as 2018, 2018, as as SIs wereSIs still were the main still sources the ofmain publications. sources Allof SIspublications. can be accessed All atSIs https: can// www.mdpi.combe accessed /journalat / remotesensinghttps://www.mdpi.com/journal/remot/special_issues. Inviting topesensing/special_issues. researchers to edit SpecialInviting Issues top hasresearchers been very to productiveedit andSpecial has attracted Issues has a largebeen very number productive of researchers and has a lookingttracted a to large publish number their of researchers research in looking a top-quality to Remote Sens. 2020, 12, x FOR PEER REVIEW 6 of 10 journalpublish expeditiously. their research in a top-quality journal expeditiously.

FigureFigure 6. The 6. The new new Special Special Issues Issues (SIs) (SIs) set set upup and the the rate rate of of publications publications for forSIs SIsin the in past the pastthree three years years in theinRemote the Remote Sensing Sensing Open Open Access Access Journal Journalof of MDPI.MDPI.

TheThe best best five five SIs SIs that that closed closed in in 2019 2019 are are listedlisted in Table Table 2:2:

Table 2. The newly set up Special Issues (SIs) and the rate of publications for SIs in the past three years.

SI Title Guest Editors Publication Jiali Shang, Jiangui Liu, Catherine Advances of Multi-Temporal Remote Sensing in Champagne, Taifeng Dong, John 28 Vegetation and Agriculture Research Kovacs Concurrent Positioning, Mapping and Perception Jingbin Liu, Yuanxi Yang, Juha of Multi-Source Data Fusion for Smart 21 Hyyppä, Naser El-Sheimy Applications Convolutional Neural Networks Applications in Davide Cozzolino, Raffaele Gaetano, 20 Remote Sensing Francescopaolo Sica Global Navigation Satellite Systems for Earth Jianghui Geng, Maorong Ge, Jennifer 26 Observing System Haase, Weiping Jiang High-precision GNSS: , Open Problems Xingxing Li, Jacek Paziewski, Mattia 35 and Geoscience Applications Crespi

3. Editorial Board In 2019, five new sections were set up and five new Section Editors-in-Chief (SEiCs) joined us, including Dr. Magaly Koch for the Section “Environmental Remote Sensing”, Prof. Stuart Phinn for “Coral Reef Remote Sensing”, Prof. Mattia Crespi for “Engineering Remote Sensing”, Dr. Vincenzo Levizzani for “Remote Sensing of the Water Cycle”, and Dr. Deepak R. Mishra for “Remote Sensing Letter”. Moreover, Prof. Gerrit de Leeuw and Dr. Jorge Vazquez took over from Dr. Richard Müller and Dr. Xiaofeng Li as new SEiCs for “ Remote Sensing” and “Ocean Remote Sensing”, respectively. In addition, 27 new Associate Editors were promoted and the number of Editorial Board Members increased from 280 to 605 in 2019 (Table 3). We also created two new positions in 2019, Topic Editor and Reviewer Board Member. The 17 Topic Editors were on board to help propose and manage new Special Issues, and also to promote our journal at various conferences. Furthermore, 1107 Reviewer Board Members joined our team to help provide high-quality reviews.

Remote Sens. 2020, 12, 2442 6 of 9

Table 2. The newly set up Special Issues (SIs) and the rate of publications for SIs in the past three years.

SI Title Guest Editors Publication Advances of Multi-Temporal Remote Sensing in Jiali Shang, Jiangui Liu, Catherine 28 Vegetation and Agriculture Research Champagne, Taifeng Dong, John Kovacs Concurrent Positioning, Mapping and Perception of Jingbin Liu, Yuanxi Yang, Juha Hyyppä, 21 Multi-Source Data Fusion for Smart Applications Naser El-Sheimy Convolutional Neural Networks Applications in Remote Davide Cozzolino, Raffaele Gaetano, 20 Sensing Francescopaolo Sica Global Navigation Satellite Systems for Earth Observing Jianghui Geng, Maorong Ge, Jennifer Haase, 26 System Weiping Jiang High-precision GNSS: Methods, Open Problems and Xingxing Li, Jacek Paziewski, Mattia Crespi 35 Geoscience Applications

3. Editorial Board In 2019, five new sections were set up and five new Section Editors-in-Chief (SEiCs) joined us, including Dr. Magaly Koch for the Section “Environmental Remote Sensing”, Prof. Stuart Phinn for “Coral Reef Remote Sensing”, Prof. Mattia Crespi for “Engineering Remote Sensing”, Dr. Vincenzo Levizzani for “Remote Sensing of the Water Cycle”, and Dr. Deepak R. Mishra for “Remote Sensing Letter”. Moreover, Prof. Gerrit de Leeuw and Dr. Jorge Vazquez took over from Dr. Richard Müller and Dr. Xiaofeng Li as new SEiCs for “Atmosphere Remote Sensing” and “Ocean Remote Sensing”, respectively. In addition, 27 new Associate Editors were promoted and the number of Editorial Board Members increased from 280 to 605 in 2019 (Table3). We also created two new positions in 2019, Topic Editor and Reviewer Board Member. The 17 Topic Editors were on board to help propose and manage new Special Issues, and also to promote our journal at various conferences. Furthermore, 1107 Reviewer Board Members joined our team to help provide high-quality reviews.

Table 3. The summary of team construction in the past two years.

Position 2018 2019 2018–2019 Increase EiC 1 1 0 SEiC 8 13 5 Advisory Board Member 3 8 5 Senior Associate Editor 4 4 0 Associate Editor 30 57 27 Editorial Board Member 280 605 325 Topic Editor 0 17 17 Reviewer Board Member 0 1107 1107

All Editorial Board Members, Reviewer Board Members, and Topic Editor information can be accessed at the following links, respectively:

1. https://www.mdpi.com/journal/remotesensing/editors; 2. https://www.mdpi.com/journal/remotesensing/submission_reviewers; 3. https://www.mdpi.com/journal/remotesensing/topic_editors.

4. Competition Among all the 30 journals under the category “Remote Sensing” (https://jcr.incites.thomsonreuters. com), the Impact Factor of Remote Sensing OAJ of MDPI (4.509) ranks 9th, Q2 (Figure7). Compared to the top five journals, the main competitive advantages of Remote Sensing OAJ of MDPI are shorter publication time, a lower article processing charge, and rich experience in the open-access field. Remote Sens. 2020, 12, x FOR PEER REVIEW 7 of 10

Table 3. The summary of team construction in the past two years.

Position 2018 2019 2018–2019 Increase EiC 1 1 0 SEiC 8 13 5 Advisory Board Member 3 8 5 Senior Associate Editor 4 4 0 Associate Editor 30 57 27 Editorial Board Member 280 605 325 Topic Editor 0 17 17 Reviewer Board Member 0 1107 1107

All Editorial Board Members, Reviewer Board Members, and Topic Editor information can be accessed at the following links, respectively: 1. https://www.mdpi.com/journal/remotesensing/editors; 2. https://www.mdpi.com/journal/remotesensing/submission_reviewers; 3. https://www.mdpi.com/journal/remotesensing/topic_editors.

4. Competition Analysis Among all the 30 journals under the category “Remote Sensing” (https://jcr.incites.thomsonreuters.com), the Impact Factor of Remote Sensing OAJ of MDPI (4.509) ranks 9th, Q2 (Figure 7). Compared to the top five journals, the main competitive advantages of Remote Sensing OAJ of MDPI are shorter publication time, a lower article processing charge, and rich Remote Sens. 2020, 12, 2442 7 of 9 experience in the open-access field.

Figure 7. TheFigure top 7. 12 The journals top 12 journals under under the the category category “Remote“Remote Sensing” Sensing” based based on Impact on Factor Impact (2019). Factor (2019). Data were calculatedData were calculated from Web from of We Scienceb of Science on on 13 13 July July 2020.2020.

Among allAmong of the all journals of the journals under under this this category, category, thethe Eigenfactor Eigenfactor score score and normalized and normalized Eigenfactor Eigenfactor of Remote Sensing OAJ of MDPI (0.06661, 8.1265) ranks 1st (Figures 8 and 9). We have been of Remote Sensing OAJ of MDPI (0.06661, 8.1265) ranks 1st (Figures8 and9). We have been emphasizing Remoteemphasizing Sens. 2020 ,both 12, x FORthe PEERquality REVIEW of the published articles and the impact in the field since 2018. 8 of 10 both the qualityRemote of Sens. the 2020 published, 12, x FOR PEER articles REVIEW and the impact in the field since 2018. 8 of 10

Figure 8. The top 10 journals under the category “Remote Sensing” based on Eigenfactor score (2019). Figure 8. TheDataFigure top were 108. Thecalculated journals top 10 journalsfrom under We underb theof Science categorythe category on 13 “RemoteJuly “Remot 2020.e Sensing” Sensing” based based on Eigenfactor on Eigenfactor score (2019). score (2019). Data were calculatedData were calculated from Web from of We Scienceb of Science on 13on 13 July July 2020. 2020.

Figure 9. The top 10 journals under the category “Remote Sensing” based on normalized Eigenfactor Figure 9. The top 10 journals under the category “Remote Sensing” based on normalized Eigenfactor (2019). Data(2019). wereFigure Data calculated9. The were top calculated 10 journals from from Web under Web of the Scienceof category Science onon“Remot 13 July Julye Sensing” 2020. 2020. based on normalized Eigenfactor (2019). Data were calculated from on 13 July 2020. Among all of the journals under this category, the Article Influence Score of Remote Sensing OAJ of MDPIAmong (0.927) all ranks of the 9th journals (Figure under 10). this category, the Article Influence Score of Remote Sensing OAJ of MDPI (0.927) ranks 9th (Figure 10).

Remote Sens. 2020, 12, 2442 8 of 9

Among all of the journals under this category, the Article Influence Score of Remote Sensing OAJ of MDPI (0.927)Remote Sens. ranks 2020, 9th12, x FOR (Figure PEER REVIEW10). 9 of 10

Figure 10.FigureThe 10. top The 10 top journals 10 journals under under the the category category “Remot “Remotee Sensing” Sensing” based based on Article on Article Influence Influence Score Score (2019). Data(2019). were Data calculatedwere calculated from from Web Web of of Science Science onon 13 July July 2020. 2020.

5. A Bibliographic5. A Bibliographic analysis analysis of Remoteof Remote Sensing Sensing OpenOpen Access Access Journal Journal of MDPI of MDPI A detailedA detailed bibliometric bibliometric profile profile of of the theRemote Remote Sensing Open Open Access Access Journal Journal PublishedPublished by MDPI by MDPI betweenbetween 2009 and 2009 2018 and 2018 is provided is provided by by Drs. Drs. Zhang, Zhang, Thenkabail and and Wang Wang [5]. [ 5]. 6. Current Achievements and the Way Forward 6. Current Achievements and the Way Forward Remote Sensing Open Access Journal (OAJ) of MDPI was the first open access journal in remote Remotesensing Sensing that began Open publishing Access Journalin the year(OAJ) 2009. ofIt published MDPI was about the 100 first articles open per access year then, journal but now in remote sensingpublishes that began above publishing 3000 articles in theper year, year the 2009. highest It published by any remote about sensing 100 articles international per year journal. then, It is but now publishesnow above a well-recognized 3000 articles and per respected year, the international highest by anyjournal remote of repute sensing in remote international sensing, journal.where the It is now a well-recognizedvery best and respected in the subjec internationalt from around journal the world of publish repute regu in remotelarly. Insensing, 2019, 8381 where articles the were very best submitted, but only 36% of them were published, which indicates a very high interest in publishing scientists in the subject from around the world publish regularly. In 2019, 8381 articles were submitted, in the journal, but at the same time, there is a critical review process where a large number (64%) of but onlythe 36% articles of them were were rejected published, either at whichsubmission indicates or during a very the highpeer-review interest process. in publishing Maintaining in the an journal, but at theimpact same factor time, of 4.509 there with is asuch critical a high review numberprocess of publications where is aitself large a testament number to (64%) the quality of the of articles were rejectedthe articles either published. at submission Remote orSensing during Open the Access peer-review Journal ofprocess. MDPI can Maintaining easily further an increase impact its factor of 4.509 withimpact such factor a high swiftly, number if 20–30% of publications of the lesser isranked itself articles a testament are not to published. the quality However, of the articlesthis creates published. Remote Sensinga problem Open where Access very Journal good articlesof MDPI are canrejected easily solely further based increase on novelty its impactor unfounded, factor swiftly,and often if 20–30% biased, subjective criticism of the value of the article. The journal follows a rigorous peer-review of the lesser ranked articles are not published. However, this creates a problem where very good process involving two or more reviewers (most often three or more reviewers) followed by single or articlesmulti-tiered are rejected editorial solely basedscrutiny. on Typically, novelty multiple or unfounded, rounds of and reviews often and biased, editorial subjective scrutiny criticism are of the valueinvolved. of the article. The journal follows a rigorous peer-review process involving two or more reviewers (mostRemote often Sensing three OAJ orof moreMDPI is reviewers) now a well-recognized followed by leading single open or multi-tieredaccess journal editorialthat allows scrutiny. Typically,free multiple downloads rounds of the ofarticles reviews from andanywhere editorial in the scrutiny world with are simple involved. internet access. Its review is Remotefast with Sensing a median OAJ ofof 45 MDPI days isfrom now submission a well-recognized to publishing. leading It has rich open set access of articles, journal as evidenced that allows free by the journal performance parameters in Table 1. These articles are written by some of the best downloadsresearchers of the on articles the subject from from anywhere around inthe the world. world In 2019, with articles simple originated internet from access. 118 Itscountries. review is fast with a medianNearly 70% of 45 for days these from articles submission came from to publishing.China and the It hasUSA, rich followed set of by articles, European as evidenced countries by the journal performance(Germany, Italy, parameters the UK, Spain, in TableFrance,1. the These Netherlands), articles are Canada, written and by Australia. some of Remote the best Sensing researchers OAJ on the subjectprovides from readers around and the authors world. statistics In 2019, on articleseach arti originatedcle, such as the from number 118 countries. of downloads Nearly and number 70% for these articles cameof citations. from Remote China Sensing and the OAJ USA, ranks followed #1 amongst by all European remote sensin countriesg journals (Germany, in terms of Italy, Eigenfactor the UK, Spain, scores (0.06661) and normalized Eigenfactor scores (8.1265). It increased its citations by 12,516 in 2019 France, the Netherlands), Canada, and Australia. Remote Sensing OAJ provides readers and authors (36,083) compared to 2018 (23,567), the highest increase in the year by any Remote Sensing Journal. statistics on each article, such as the number of downloads and number of citations. Remote Sensing OAJ ranks #1 amongst all remote sensing journals in terms of Eigenfactor scores (0.06661) and normalized Eigenfactor scores (8.1265). It increased its citations by 12,516 in 2019 (36,083) compared to 2018 (23,567), the highest increase in the year by any Remote Sensing Journal. Remote Sensing of Environment Remote Sens. 2020, 12, 2442 9 of 9 with 62,697 citations, and IEEE Transactions on Geoscience and Remote Sensing with 46,565 citations rank above Remote Sensing OAJ in 2019. There is a clear “paradigm-shift” in how remote sensing science is conducted in the last few years with swift advances in big-data analytics, machine learning, deep learning, artificial , cloud computing, and Application Programming Interfaces (APIs). Analysis Ready Data (ARD) and reference training and validation data Hubs in support of creating knowledge- to train machine deep learning algorithms and validation of the products further help in speed and accuracy \ of production of myriad remotely sensed data derived science applications. A whole new world of smallsats and CubeSats are revolutionizing how remote sensing data is acquired, processed, and made available to users. As a result of all these endeavors, remote sensing data user base and its applications are expanding exponentially and has led to quantum leap in productivity and speed of research. Combination of these factors are expected to further increase remote sensing data derived science publications and applications in the coming years. Going forward, our goal remains to publish cutting-edge impactful research of importance and value to scientists and the public, research that enhances our knowledge or fills a missing gap in knowledge, and applied science of practical value in remote sensing and related .

Funding: This research received no external funding. Acknowledgments: The EiC would like to express thanks to Denise Liu, Managing Editor of Remote Sensing, as well as the Editorial Team who contributed by providing inputs to this article. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Conflicts of Interest: The author declares no conflict of interest.

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