About this journal
Aims and scope
GIScience & Remote Sensing is a fully open access journal publishing original, peer-reviewed articles associated with geographic information systems (GIS), remote sensing of the environment (including digital image processing), geocomputation, spatial data mining, and geographic environmental modelling. Papers reflecting both basic and applied research are published.
In support of reproducibility for all kinds of work, the journal requires that data and software used in the analysis be deposited in a repository that complies with the Open + FAIR policies of the COPDESS consortium.
Peer Review Statement
GIScience & Remote Sensing is an international, ranked, peer-reviewed journal which publishes original research contributions to scientific knowledge. The journal accepts the following type of article: research article, reviews, data notes and method articles.
All manuscript submissions are subject to initial appraisal by the Editor, and, if found suitable for further consideration, to peer review by independent, anonymous expert referees. All articles are made freely and permanently available online through gold open access publication.
All peer review is single anonymized and submission can be made online via Submission Portal.
*Please note that GIScience & Remote Sensing converted to a full Open Access journal from Volume 59 (2022).
Journal metrics
Usage
- 499K annual downloads/views
Citation metrics
- 6.0 (2023) Impact Factor
- Q1 Impact Factor Best Quartile
- 7.3 (2023) 5 year IF
- 11.2 (2023) CiteScore (Scopus)
- Q1 CiteScore Best Quartile
- 1.766 (2023) SNIP
- 1.756 (2023) SJR
Speed/acceptance
- 6 days avg. from submission to first decision
- 61 days avg. from submission to first post-review decision
- 9 days avg. from acceptance to online publication
- 21% acceptance rate
Understanding and using journal metrics
Journal metrics can be a useful tool for readers, as well as for authors who are deciding where to submit their next manuscript for publication. However, any one metric only tells a part of the story of a journal’s quality and impact. Each metric has its limitations which means that it should never be considered in isolation, and metrics should be used to support and not replace qualitative review.
We strongly recommend that you always use a number of metrics, alongside other qualitative factors such as a journal’s aims & scope, its readership, and a review of past content published in the journal. In addition, a single article should always be assessed on its own merits and never based on the metrics of the journal it was published in.
For more details, please read the Author Services guide to understanding journal metrics.
Journal metrics in brief
Usage and acceptance rate data above are for the last full calendar year and are updated annually in February. Speed data is updated every six months, based on the prior six months. Citation metrics are updated annually mid-year. Please note that some journals do not display all of the following metrics (find out why).
- Usage: the total number of times articles in the journal were viewed by users of Taylor & Francis Online in the previous calendar year, rounded to the nearest thousand.
Citation Metrics
- Impact Factor*: the average number of citations received by articles published in the journal within a two-year window. Only journals in the Clarivate Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), Arts and Humanities Citation Index (AHCI) and the Emerging Sources Citation Index (ESCI) have an Impact Factor.
- Impact Factor Best Quartile*: the journal’s highest subject category ranking in the Journal Citation Reports. Q1 = 25% of journals with the highest Impact Factors.
- 5 Year Impact Factor*: the average number of citations received by articles in the journal within a five-year window.
- CiteScore (Scopus)†: the average number of citations received by articles in the journal over a four-year period.
- CiteScore Best Quartile†: the journal’s highest CiteScore ranking in a Scopus subject category. Q1 = 25% of journals with the highest CiteScores.
- SNIP (Source Normalized Impact per Paper): the number of citations per paper in the journal, divided by citation potential in the field.
- SJR (Scimago Journal Rank): Average number of (weighted) citations in one year, divided by the number of articles published in the journal in the previous three years.
Speed/acceptance
- From submission to first decision: the average (median) number of days for a manuscript submitted to the journal to receive a first decision. Based on manuscripts receiving a first decision in the last six months.
- From submission to first post-review decision: the average (median) number of days for a manuscript submitted to the journal to receive a first decision if it is sent out for peer review. Based on manuscripts receiving a post-review first decision in the last six months.
- From acceptance to online publication: the average (median) number of days from acceptance of a manuscript to online publication of the Version of Record. Based on articles published in the last six months.
- Acceptance rate: articles accepted for publication by the journal in the previous calendar year as percentage of all papers receiving a final decision.
For more details on the data above, please read the Author Services guide to understanding journal metrics.
*Copyright: Journal Citation Reports®, Clarivate Analytics
†Copyright: CiteScore™, Scopus
Editorial board
Editor in Chief
Jungho Im, Assistant Professor, Ulsan National Institute of Science & Technology, Ulsan, South Korea
Associate Editors
Yongze Song, Senior Lecturer, Curtin University, Perth, Australia
spatial statistics, geospatial methods, urban remote sensing, sustainable development
Zhen Zhen, Associate Professor, Northeast Forestry University, Harbin, Heilongjiang, China
remote sensing of forest, land use/land cover classification, geostatistics
Editorial Board
Enner Alcântara, Professor, Sao Paulo State University Julio de Mesquita Filho, Brazil
inland waters, natural hazards, environmental modeling
Nishan Bhattarai, PhD, University of Oklahoma, Norman, OK, USA
hydrological remote sensing, evapotranspiration/surface energy balance, vegetation dynamics
Thomas Blaschke, Professor, University of Salzburg, Austria
remote sensing integration, place-based GIS, object-based image analysis, geoinformatics
Linga Reddy Cenkeramaddi, Professor, Universitetet i Agder, Grimstad, Norway
radars, sensors, sensor fusion and machine learning for remote sensing applications
Weitao Chen, Professor, China University of Geosciences, Wuhan, China
artificial intelligence, geoscience and remote sensing
Minha Choi, Professor, Sungkyunkwan University, Seoul, South Korea
remote sensing of hydrology, soil moisture, evapotranspiration
Rosa Coluzzi, PhD, Consiglio Nazionale delle Ricerche, Tito Scalo, Italy
EO data integration, land cover and land use changes, environmental mapping and monitoring
Russell G. Congalton, Professor, University of New Hampshire, Durham, NH, USA
spatial data quality/uncertainty/accuracy assessment, digital image classification, GIS analysis
Maria João Costa, Associate Professor, University of Évora, Portugal
optical remote sensing of the atmosphere, satellite remote sensing of water quality
Zheng Duan, Associate Senior Lecturer, Lunds Universitet, Sweden
remote sensing, water cycle, ecosystem, data-model fusion, machine learning
Peng Fu, Assistant Professor, Harrisburg University of Science and Technology, Harrisburg, PA, USA
deep learning, data fusion, disaster assessment, hyperspectral and thermal remote sensing
Yongshuo Fu, Professor, Beijing Normal University, China
climate change; vegetation phenology; terrestrial carbon and water cycles; machine learning
Peng Gong, Professor Emeritus, University of California Berkeley, CA, USA
remote sensing applications, global land cover mapping, urban remote sensing, wetland mapping
Barry Haack, Emeritus Professor, George Mason University, Fairfax, VA, USA
image processing, RADAR, multi-sensor data fusion, land cover classification
Perry Hardin, Professor, Brigham Young University, Provo, UT, USA
Culture and geography of Africa, hyperspectral remote sensing of urban areas
Michael E. Hodgson, Distringuished Professor Emeritus, University of South Carolina, Columbia, SC, USA
LiDAR, terrain modeling, hazards
Bandana Kar, AAAS Science, Technology and Policy Fellow, Department of Energy, Washington, DC, USA
hazards and damage assessment, big data integration, urban informatics
Yinghai Ke, Professor, Capital Normal University, Beijing, China
urban monitoring, remote sensing of hydrological processes, multi-sensor data fusion, machine learning
Thomas Krumpen, Senior Researcher, Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany
sea ice thickness observations, sea ice mass balance changes, polar remote sensing
Prashant Kumar, PhD, Space Applications Centre, Ahmedabad, India
data Assimilation, Extreme Weather, NWP Model
Xiaodong Li, Professor, Innovation Academy for Precision Measurement Science and Technology CAS, Wuhan, China
optical image analysis, data fusion, superresolution, change detection, surface water monitoring
Jie Lin, Associate Professor, Zhejiang University, Zhejiang, China
spatial analysis; Multivariate analysis; Health geography; Areal interpolation
Desheng Liu, Professor, Ohio State University, Columbus, OH, USA
digital image prcessing, multi-temporal image analysis, land use and land cover change, spatial statistics
Tao Liu, Assistant Professor, Michigan Technological University, Houghton, MI, USA
UAV remote sensing, artificial intelligence application
Zhenyu Lu, Senior Software Engineer, ESRI, Redlands, CA, USA
machine learning, urban remote sensing, LiDAR
Kamlesh P. Lulla, Senior Scientist, NASA Jon Space Center, Houston, TX, USA
satellite image processing, land terrain monitoring, water resources and water stress in vegetation, UAS technology for remote sensing applications
Deepak Mishra, Professor, University of Georgia, Athens, GA, USA
remote sensing of wetlands and water quality, ocean optics and satellite oceanography, remote sensing in global climate change
Debashis Mitra, PhD, Indian Institute of Remote Sensing, Dehradun, India
remote sensing for coastal zones, coastal geology and geomorphology, coastal zone management, coastal hazards and remote sensing
Soe W. Myint, Professor and Meadows Endowed Chair, Texas State University, San Marcos, TX, USA
urban image analysis, land use land cover change and environmental issues, agriculture mapping and water use, urban heat island
Haemi Park, PhD, Sophia University, Chiyoda-ku, Japan
carbon monitoring, GPP, vegetation
Seonyoung Park, Professor, Seoul National University of Science and Technology, South Korea
Artificial intelligence, natural disasters, data fusion
George P. Petropoulos, Assistant Professor, Harokopio University of Athens, Greece
Earth observation modeling, geospatial analysis techniques, natural hazards
Robert Pontius Jr, Professor, Clark University, Worcester, MA, USA
error assessment, land change science, dynamic simulation models
Xingwen Quan, Associate Professor, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
remote sensing, wildfire danger assessment, active fire detection, fire severity, machine learning
Parinaz Rahimzadeh-Bajgiran, Associate Professor, University of Maine, Orono, ME, USA
optical remote sensing, multispectral, hyperspectral, forest
R. Douglas Ramsey, Professor, Utah State University, Logan, UT, USA
landscape monitoring, rangeland ecology, landscape modeling
Víctor Rodríguez-Galiano, Professor, University of Seville, Spain
remote sensing of vegetation, remote sensing of phenology, land cover mapping, machine learning, time series analysis
Elif Sertel, Professor, Istanbul Technical University, Turkey
remote sensing, GeoAI, Earth Observation, LULC
Prashant K. Srivastava, Assistant Professor, Banaras Hindu University Institute of Environment & Sustainable Development, Varanasi, India
microwave remote sensing, hyperspectral remote sensing, artificial intelligence, physical model
Douglas A. Stow, Professor Emeritus, San Diego State University, CA, USA
remote sensing change detection, remote sensing of wildfire, post-disturbance vegetation recovery, post-hazard damage assessment
Weiwei Sun, Professor, Ningbo University, Jiangbei, Ningbo, China
hyperspectral, remote sensing, machine learning, coastal wetland, multi-modal geospatial data
Sasai Takahiro, Assistant Professor, Tohoku University, Sendai, Japan
terrestrial carbon cycle, diagnostic-type biosphere model , Earth system models
Jason A. Tullis, Professor, University of Arkansas, Fayetteville, AR, USA
Provenance and replicability in GIScience, ecosystem services, Mars observation
Qihao Weng, Professor, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
remote sensing, urban climatology, urban ecology, GIScience
Frank Witmer, Associate Professor, University of Alaska, Anchorage, AK, USA
remote sensing of violent conflict, nighttime lights satellite data, spatial statistical analysis
Wei Wu, Associate Professor, University of Southern Mississippi, Hattiesburg, MS, USA
spatial modeling and statistics, remote sensing in hydrology and ecology, Bayesian hierarchical modeling
Chaowei Yang, Professor, George Mason University, Fairfax, VA, USA
spatial cloud computing, spatiotemporal big data, geospatial cyberinfrastructure, geospatial semantics
Kang Yang, Professor, Nanjing University, China
remote sensing of cryosphere, remote sensing of hydrology, satellite image analysis
Cheolhee Yoo, Research Assistant Professor, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
thermal remote sensing, urban climate, machine learning
Stephen R. Yool, Professor Emeritus, University of Arizona, Tucson, AZ, USA
spectral modeling and time series analysis, wildland fire modeling, infectious disease modeling
Tianjie Zhao,PhD, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
microwave remote sensing; SAR; Microwave radiometry; Hydrology; Cryosphere
Editor-in-Chief Emeritus
John R. Jensen
Abstracting and indexing
Indexing
GIScience & Remote Sensing is currently indexed in:
- CABI
- Cambridge Scientific Abstracts
- CSA Sustainability Science ABstacts
- DOAJ
- Ecology Abstracts
- Water Resources Abstracts
- EBSCOhost
- GeoRef
- Elsevier BV
- GEOBASE
- Scopus
- Online Computer Library Centre
- Ovid
- ProQuest
- Science Citation Index Expanded (SCIE)
- Web of Science
- Wildlife Review Abstracts
Open access
GIScience & Remote Sensing is an open access journal and only publishes open access articles. Publishing open access means that your article will be free to access online immediately on publication, increasing the visibility, readership, and impact of your research.
Why choose open access?
- Increase the discoverability and readership of your article
- Make an impact and reach new readers, not just those with easy access to a research library
- Freely share your work with anyone, anywhere
- Comply with funding mandates and meet the requirements of your institution, employer or funder
- Rigorous peer review for every open access article
Article Publishing Charges (APC)
To publish open access in this journal you may be asked to pay an Article Publishing Charge (APC). You may be able to publish your article at no cost to yourself or with a reduced APC if your institution or research funder has an open access agreement or membership with Taylor & Francis. Discounts and waivers may also be available for researchers in selected countries when publishing in open access journals.
Use our APC finder to calculate your article publishing charge
News, offers and calls for papers
Continuous publication
Currently known as:
- GIScience & Remote Sensing (2004 - current)
Formerly known as
- Mapping Sciences and Remote Sensing (1984 - 2003)
Advertising information
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