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)
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


  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


  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

A Novel Method for Forest Height Estimation Using PolInSAR Data

Amir Aghabalaei; Hamid Ebadi; Yasser Maghsoudi

Volume 12, Issue 2 , August 2020, , Pages 57-72


  Monitoring the earth and its biosphere is an essential task in any scale to achieve a sustainable development. Therefore, forests, as an invaluable natural resource, have an important role to control the climate changes and the carbon cycle. For this reason, biomass and consequently forest height have ...  Read More

Target detection from high-resolution remote sensing images using deep learning methods

nima farhadi; Abas Kiani; Hamid Ebadi

Volume 11, Issue 1 , May 2019, , Pages 48-64


  Object detection is one of the fundamental issues in image interpretation process, especially from remote-sensing imagery. One of the most effective and efficient methods in this field is the use of deep learning algorithm for feature extraction and interpretation. An object is a collection of unique ...  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

  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