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 135, Autumn 2025, Pages 1-221 

Keywords Cloud

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