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
Estimation of Soil Surface Moisture Using ALOSPALSAR-2 Data
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
Current Issue: Volume 18, Issue 1 - Serial Number 69, 2026, Pages 1-212 

Change Detection in Residential Areas Construction by Using Photogrammetry Products

10.48308/gisj.2025.236867.1231

Muhammad Amin Bakhshi, Mehrdad Eslami, Ali Sarkargar Ardakani, Ramin Saadi Esfangareh

Keywords Cloud

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