Scientific- Research Quarterly of Geographical Data (SEPEHR)

Scientific- Research Quarterly of Geographical Data (SEPEHR)

Quarterly of Geographical Data is an open access double-blind peer reviewed publication which is published by National Geographical Organization.  This journal is a quarterly publication, which publishes original research papers on journal scope.  This journal follows Committee on Publication Ethics (COPE) and complies with the highest ethical standards in accordance with ethical laws. All submitted manuscripts are checked for similarity through Hamyab software to ensure their authenticity and then rigorously peer-reviewed by expert reviewers. (Read More about the journal...).

          


Dear researchers, please pay attention to the following points before deciding to submit a paper:
  • Widespread enthusiasm of professors and distinguished scholars to contribute to the journal through submitting valuable papers of scholarly research is commendable.
  • The Geographic Data (SEPEHR)Journal is published quarterly, and is intended to provide on each issue with a balanced combination of papers on fields of extraction, production, processing and analysis of geographical data, along with providing geographical information.
  • number of submissions in different fields varies significantly according to the number of experts and researchers active in the field.
  • Submitted papers on urban, rural and political geography, climatology and geomorphology are currently in very great numbers, and consequently, their process of examination and publication have become lengthy.
  • Papers on aerial photography, geodesy and gravimetry are relatively less frequent, and will therefore have shorter process of examination and publication.
  • So, researchers who have time limitations concerning the confirmation or publication of their valuable papers are recommended to select the Journal of Geographical Data(SEPEHR), or other publications, with above conditions in mind.

Journal Features
  • Publisher: National Geographical Organization
  • Review time: 12 weeks
  • Frequency: Quarterly
  • Open access: Yes
  • Peer Review Policy:  Double-blind peer-review
  • Indexed and Abstracted: yes
  • Abstracts available in: Persian and English 
  • Article Processing Charges: No
  • Contact email: info@sepehr.org

 

Current Issue: Volume 34, Issue 136, Winter 2026, Pages 1-156 

Keywords Cloud

  • GIS
  • Remote Sensing
  • Iran
  • Tourism
  • Sustainable development
  • Geographic Information System
  • Earthquake
  • Passive defense
  • Geomorphology
  • crisis management
  • Land use
  • City
  • Locating
  • Climate change
  • Spatial analysis
  • Climate
  • MODIS
  • Satellite images
  • Vulnerability
  • Urban Planning
  • Ecotourism
  • NDVI
  • Drought
  • development
  • Zoning
  • Security
  • Precipitation
  • AHP
  • Planning
  • geographic information system (GIS)
  • genetic algorithm
  • Artificial neural network
  • Location
  • Google Earth Engine
  • GPS
  • Isfahan
  • Land surface temperature
  • Persian Gulf
  • Fuzzy logic
  • erosion
  • Air pollution
  • Physical development
  • Support Vector Machine
  • Geotourism
  • Change detection
  • ecosystem
  • Urban Management
  • Land use changes
  • Crisis
  • Ionosphere
  • environment
  • Tehran
  • globalization
  • Classification
  • Deep Learning
  • flood
  • Optimization
  • Satellite Imagery
  • Agriculture
  • TEC
  • Artificial neural networks
  • Dust
  • Modeling
  • Detection
  • LiDAR
  • Geospatial Information System
  • TOPSIS
  • landslide
  • Tabriz
  • Landsat
  • Trend
  • Shiraz
  • Correlation
  • Normalized difference vegetation index (NDVI)
  • Mann-Kendall test
  • SWOT
  • Digital elevation model
  • Temperature
  • Geographic Information Systems (GIS)
  • Flooding
  • Downscaling
  • Rural Development
  • Caspian Sea
  • Fars province
  • Time Series
  • population
  • Kermanshah
  • Kriging
  • Analytic hierarchy process (AHP)
  • Land surface temperature (LST)
  • geopolitics
  • Village
  • UAV
  • 3D modeling
  • technology
  • vegetation
  • Forest
  • Photogrammetry
  • Simulation
  • DEM
  • PCA
  • Neural network
  • Border
  • Ahvaz
  • Fuzzy
  • Green space
  • Tectonic
  • Sentinel 2
  • Kurdistan Province
  • Geoid
  • Markov Chain
  • sedimentation
  • RS
  • Landsat satellite
  • Groundwater
  • Strategy
  • Regional Development
  • Mashhad
  • Cellular automata
  • Urban growth
  • Mazandaran
  • AHP Model
  • Geospatial Information System (GIS)
  • Gully erosion
  • prediction
  • Subsidence
  • Urban green space
  • Hot spot analysis
  • Geographical Information System
  • Anomaly
  • SRTM
  • Point Cloud
  • Land cover
  • Clustering
  • Khuzestan Province
  • Satellite data
  • MODIS Sensor
  • Spatial data
  • urban land use
  • Wind erosion
  • RADAR
  • Hamedan Province
  • transportation
  • Decision tree
  • rural tourism
  • Sand
  • hydrology
  • sensor
  • SAR Interferometry
  • Vegetation index
  • Web GIS
  • ASTER
  • Ranking
  • ecology
  • urban development
  • Analytic Network Process (ANP)
  • evolution
  • Kermanshah province
  • Monitoring
  • data
  • methodology
  • Random Forest
  • Hydropolitics
  • Mahabad
  • natural environment
  • urban poverty
  • Thresholding
  • Aerosol Optical Depth
  • Landsat 8
  • Data Integration
  • Synoptic analysis
  • frost
  • Solar Energy
  • Routing
  • Digital elevation model (DEM)
  • Worn-out texture
  • Heavy precipitation
  • Maximum Likelihood
  • Machine learning algorithms
  • Ilam
  • Gilan
  • geography
  • Aerial imagery
  • Regression
  • Kashan City
  • Sentinel-2
  • localization
  • urbanization
  • Lake Urmia
  • Land use planning
  • Return period
  • Hamedan
  • Geographical Information System (GIS)
  • Geographic Information Systems
  • orthophoto
  • traffic
  • Thermal Island
  • Image fusion
  • LST
  • desert