Iranian Journal of Remote Sensing and GIS

Iranian Journal of Remote Sensing and GIS

Iranian Journal of Remote Sensing and GIS

Journal Archive


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Iranian Journal of Remote Sensing and GIS is a double-blind peer-reviewed quarterly journal, owned & managed by Iran Remote Sensing and GIS Association & published by Shahid Beheshti University since 2009 and is indexed in Scopus now. The journal publishes original articles, reviews, and letters relevant to all fields Remote Sensing and GIS including but not limited to the remote sensing, geographic information system (GIS), photogrammetry, geodesy and their applications in agriculture, forestry, geology, water resources, meteorology and climate, natural resources, urban management & satellite oceanography .

Journal Title

 Iranian Journal of Remote Sensing and GIS

P-ISSN

 2008-5966

E-ISSN

 2588-6185

Frequency

 Quarterly

Editor-in-Chief

 Ali Akbar Matkan, Ph.D.

Language 

 Persian with English abstracts

Plagiarism Checker

 iThenticate, Samimnoor (Persian)

Peer Review Policy

 Double-blind

Article Processing Charges

 See here

Average Review Time

 2 Months

Acceptance Rate

 24%

Owner

 Iran Remote Sensing and GIS Association

Publisher

 Shahid Beheshti University, Iran.
Most Visited Articles
A Review of Recent Researches on Integration of Building Information Modeling (BIM) and GIS
Investigating the Relationship between Drought and Water Quality Reduction Using Remote Sensing and Neural Network Methods
The Evaluation of GPM Precipitation Remote Sensing Data with Observed Data (Case Study: Mid-West of Iran)
Positioning lands prone for cultivating ficus fars province using fuzzy logic and the GIS approach
Developing an Agent-Based Model for Intelligent Control of Traffic Lights and Dynamic Routing
Investigating and Modeling the Effect of the Composition and Arrangement of the Landscapes of Yazd City on the Land Surface Temperature Using Machine Learning and Landsat-8 and Sentinel-2 Data
Estimation of Soil Surface Moisture Using ALOSPALSAR-2 Data
Cropland Mapping through Integration of Segmentation and Classification Techniques in Google Earth Engine
Current Issue: Volume 18, Issue 2 - Serial Number 70, 2026, Pages 1-204 

Keywords Cloud

  • remote sensing
  • GIS
  • MODIS
  • Machine Learning
  • Random forest
  • Classification
  • Support vector machine
  • Land use
  • Sentinel-2
  • Iran
  • NDVI
  • Google Earth Engine
  • Drought
  • ASTER
  • Deep Learning
  • Sentinel-1
  • Vegetation index
  • Land Surface Temperature
  • Artificial Neural Network
  • time series
  • LANDSAT 8
  • Landsat
  • Leaf Area Index
  • LST
  • OLI
  • Change detection
  • Maximum likelihood
  • Flood
  • Geographic Information System (GIS)
  • Tehran
  • Agriculture
  • Genetic algorithm
  • climate change
  • Evapotranspiration
  • Dust storms
  • Anzali Wetland
  • Geographic Information System
  • Hyperspectral images
  • MODIS Sensor
  • Fuzzy logic
  • Neural Network
  • snow cover
  • hyperspectral
  • Air pollution
  • Land cover
  • SVM
  • Object-oriented Classification
  • Landuse
  • Zoning
  • Satellite images
  • Feature selection
  • Alteration
  • Land use/cover
  • Agent-Based
  • Artificial Intelligence
  • building detection
  • Crop mapping
  • Shannon Entropy
  • Modeling
  • Water quality
  • Urmia Lake
  • Tehran metropolis
  • Fuzzy Inference System
  • Wheat
  • TOPSIS
  • Satellite Imagery
  • Radar
  • Spatial modeling
  • spatial equity
  • Sensitivity Analysis
  • Site Selection
  • kappa coefficient
  • Knowledge based system
  • STARFM
  • Sedimentation
  • Albedo
  • Satellite Precipitation Products
  • Validation
  • Clustering
  • Dust storm
  • Digital elevation model
  • ANP
  • Spatial resolution
  • Trend
  • high-pass filter
  • Geographic information systems
  • Hyperspectral Imagery
  • Porphyry Copper
  • Multi-temporal Sentinel-2 Images
  • vulnerability
  • Interpolation error
  • Landscape metrics
  • GPM
  • Landsat- 8
  • Geometric Correction
  • Spatial analysis
  • spectroscopy
  • Mashhad
  • Earthquake
  • Threshold
  • RMSE
  • prediction
  • Alfalfa
  • Urban
  • Kurdistan province
  • Soil erosion
  • MCDM
  • ETM+
  • Mean absolute error
  • Zonation
  • Karun Watershed
  • Principal Component Analysis
  • Interferometric synthetic aperture radar (InSAR)
  • Entropy
  • Digital elevation model (DEM)
  • Heat island
  • Satellite image
  • Fire
  • spectral angle mapper indecs
  • Climatic factors
  • SAM
  • Urban heat islands
  • TIN
  • AIRS
  • Kajaki Dam
  • Radiative transfer model
  • Stepwise regression
  • Crop Coefficient
  • NDVI time-series
  • Network Capacity
  • Sentinel- 2
  • Neural Networks
  • monitoring
  • Yield Estimation
  • Gini coefficient
  • Land cover change
  • IMERG
  • game theory
  • Conservation
  • Precipitation Estimation
  • Accessibility
  • Tilt Angle
  • UAV
  • Image registration
  • Standardized precipitation index
  • Dust
  • Red edge Index
  • Runoff
  • XGBoost
  • Orbital Parameters Model
  • organic matter
  • internet of things
  • Machine Learning Algorithms
  • Keywords: Remote Sensing
  • thermal remote sensing
  • Coherence
  • Linear Regression
  • spatio-temporal analyses
  • Multiple regression
  • Road Network
  • Water bodies
  • Precipitation
  • spectral and spatial data
  • Soil salinity
  • Texture
  • Road extraction
  • Image Fusion
  • Overall accuracy
  • Iron ore
  • Trend analysis
  • Multi-criteria Decision Making
  • Random Forests
  • movement prediction
  • Kriging
  • Sistan Plain
  • Erosion
  • Feature extraction
  • Support Vector Machine (SVM)
  • Soft Classification
  • Accuracy Assessment
  • Urban Design
  • Mashhad metropolis
  • Magnetometric
  • Land use changes
  • Land use change
  • Artificial Neural Networks
  • Ensemble Model
  • Fourier transform
  • Rainfall
  • markov chain
  • CHIRPS
  • Ant Colony Optimization
  • downscaling
  • Spectral Indices
  • Markov Random Field
  • AOD
  • Spatial features
  • SEBAL
  • Weighting
  • Correlation