Volume 15 (2023)
Volume 14 (2022)
Volume 13 (2021)
Volume 12 (2020)
Volume 11 (2019)
Volume 10 (2018)
Volume 9 (2017)
Volume 8 (2016)
Volume 7 (2015)
Volume 6 (2014)
Volume 5 (2013)
Volume 4 (2012)
Volume 3 (2011)
Volume 2 (2010)
Volume 1 (2009)
Classification of Hyperspectral Images Using a Combination of Features Extracted from the Weighted Local Kernel Matrix of Spectral and Fractal Features

Behnam Asghari Beirami; Mehdi Mokhtarzade

Articles in Press, Accepted Manuscript, Available Online from 04 January 2023

https://doi.org/10.48308/gisj.2023.103055

Abstract
  The use of spatial features to improve the classification accuracy of hyperspectral images has become popular in recent years. Various methods for spectral-spatial classification of hyperspectral images have been introduced to date, and relevant research is being conducted to develop methods with a more ...  Read More

Comparison of the Efficiency of Local Climatic Zone Algorithm in Separating Built-Up Area Compared to Built-Up Indices

Najme Satari; Malihe Erfani; FATEMEH Jahanishakib

Volume 15, Issue 4 , February 2024, , Pages 1-16

https://doi.org/10.48308/gisj.2022.102576

Abstract
  Trend analysis of growth of cities and predicting their changes in the future are essential for spatial planning. For this purpose, it is necessary to map build-up areas. In many areas, especially in arid climate, it is not possible to separate the build-up areas from the surrounding land cover simply. ...  Read More

Improving the Classification of Hyperspectral Images Using the Combined Model of CapsNet and the Extreme Gradient Boosting

Pouya Ahmadi; Tayebe Managhebi; Hamid Ebadi; Behnam Asghari

Volume 15, Issue 3 , September 2023, , Pages 41-60

https://doi.org/10.48308/gisj.2023.102347

Abstract
  With the development of remote sensing science, the use of hyperspectral images is becoming more widespread. Classification is one of the most popular topics in hyperspectral remote sensing. In the last two decades, a number of methods have been proposed to address the problem of hyperspectral data classification.In ...  Read More

Design and Implementation of an Object-Based AdaBoost Algorithm Based on Active Learning for Land-Cover Classification in High-Resolution Images

Mina Hamidi; Hamid Ebadi; abbas kiani

Volume 14, Issue 2 , July 2022, , Pages 19-36

https://doi.org/10.52547/gisj.14.2.19

Abstract
  By improvement of the spatial resolution of remote sensing images, more accurate information are provided from the image scene such as texture structures. However, extraction of land cover information from these datas has become a challenging process due to the high spectral diversity and the heterogeneity ...  Read More

Cropland Mapping through Integration of Segmentation and Classification Techniques in Google Earth Engine

Alireza Taheri Dehkordi; Mohammad Javad Valadanzouj; Alireza Safdarinezhad

Volume 14, Issue 1 , June 2022, , Pages 1-20

https://doi.org/10.52547/gisj.14.1.1

Abstract
  Map of croplands is one of the information layers required in the efficient management of these lands. Having such maps makes it possible to monitor agricultural fields during the growing season continuously. In this study, a solution to produce map of Shahrekord’s agricultural lands in two agricultural ...  Read More

An Analysis on Land Use Process Changes and Forecasting in Urmia City Using SVM Model and Neural Networks

ali khedmatzadeh; Mir Najaf Mousavi; Hojjat Mohammadi Torkamani

Volume 12, Issue 4 , February 2021, , Pages 53-72

https://doi.org/10.52547/gisj.12.4.53

Abstract
  The growth of the urban population has been led to increasing of the urban spaces and growth of the city size. as a result of further construction and alteration of the land available to the benefit of its built-up spaces. Special location the city of Urmia at proximity of the Urmia lake and unfavorable ...  Read More

Object based interpretation of high spatial remote sensing images based on knowledge-based systems

Abbas Kiani; Hamid Ebadi; Hekmat allah Khanlou

Volume 10, Issue 4 , February 2019, , Pages 27-54

Abstract
  Land cover classification in remote sensing imagery is one of the most widely used spatial information extraction methods, which can facilitate generating object imagery classes of the ground surface in order to automate and accelerate meeting the basic needs of management, organization, and exploitation ...  Read More

A Comparative study of the traditional accuracy assessment and disagreement measures of the classification of remote sensing imagery

Mehran Dadjoo; Sayyed Bagher Fatemi Nasrabadi

Volume 10, Issue 4 , February 2019, , Pages 55-68

Abstract
  Evaluation of the image classification results is very important in the remote sensing projects. So far, many indices have been presented to assess the accuracy of image classification, though Kappa coefficient and Overall accuracy are the most famous ones. Some researchers have criticized these two ...  Read More

Classification of LiDAR Points Cloud Using Markov Random Field and Machine Learning Techniques

F Aghighi; O.M Ebadati; H Aghighi

Volume 9, Issue 2 , December 2017, , Pages 41-60

Abstract
  Light Detection and Ranging (LiDAR) point cloud dataset and 3 dimensional (3-D) models have been extensively used for urban feature extraction, urban management, forestry management, managing urban green space, tourism management, robotics, and video and computer games' production. One of the main steps ...  Read More