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Environmental Sciences
Iran
2026

D-Index & Metrics

Environmental Sciences

D-Index
78
Citations
17406
World Ranking
1094
National Ranking
5

Research.com Recognitions

  • 2026 - Research.com Environmental Sciences in Iran Leader Award
  • 2025 - Research.com Environmental Sciences in Iran Leader Award

Overview

Himan Shahabi is affiliated with the University of Kurdistan in Iran and specializes in environmental science, contributing extensively to the field through research predominantly focused on flood risk assessment, landslides, and hydrology.

Their research encompasses several main topics, including:

  • Flood Risk Assessment and Management
  • Landslides and related hazards
  • Hydrology and Watershed Management Studies
  • Tree Root and Stability Studies
  • Cryospheric studies and observations
  • Groundwater and Watershed Analysis
  • Hydrology and Drought Analysis

Shahabi's work is situated largely within the domain of Environmental Science, with particular subfields involving:

  • Global and Planetary Change
  • Environmental Engineering
  • Management, Monitoring, Policy and Law
  • Atmospheric Science
  • Water Science and Technology

Recent published papers include:

  • Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier (2020, Remote Sensing)
  • Flash flood susceptibility mapping using a novel deep learning model based on deep belief network, back propagation and genetic algorithm (2020, Geoscience Frontiers)

Frequent co-authors in Shahabi's research career include:

  • Ataollah Shirzadi
  • Nadhir Al-Ansari
  • Baharin Bin Ahmad
  • Wei Chen

Their works have been published often in venues such as:

  • Remote Sensing
  • International Journal of Environmental Research and Public Health
  • Applied Sciences
  • IEEE Access
  • Sensors

Best Publications

  • A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.

    Khabat Khosravi;Binh Thai Pham;Kamran Chapi;Ataollah Shirzadi

  • A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods

    Khabat Khosravi;Himan Shahabi;Binh Thai Pham;Jan Adamowski

  • A novel hybrid artificial intelligence approach for flood susceptibility assessment

    Kamran Chapi;Vijay P. Singh;Ataollah Shirzadi;Himan Shahabi

  • Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment

    Himan Shahabi;Mazlan Hashim

  • Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods.

    Wei Chen;Yang Li;Weifeng Xue;Himan Shahabi

  • Performance evaluation of the GIS-based data mining techniques of best-first decision tree, random forest, and naïve Bayes tree for landslide susceptibility modeling

    Wei Chen;Shuai Zhang;Renwei Li;Himan Shahabi

  • Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China.

    Wei Chen;Jianbing Peng;Haoyuan Hong;Haoyuan Hong;Himan Shahabi

  • Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier

    Himan Shahabi;Ataollah Shirzadi;Kayvan Ghaderi;Ebrahim Omidvar

  • Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping.

    Hossein Shafizadeh-Moghadam;Roozbeh Valavi;Himan Shahabi;Kamran Chapi

  • Landslide susceptibility mapping at central Zab basin, Iran: a comparison between analytical hierarchy process, frequency ratio and logistic regression models

    Himan Shahabi;Saeed Khezri;Baharin Bin Ahmad;Mazlan Hashim

  • Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches

    Binh Thai Pham;Indra Prakash;Sushant K. Singh;Ataollah Shirzadi

  • Hybrid artificial intelligence models based on a neuro-fuzzy system and metaheuristic optimization algorithms for spatial prediction of wildfire probability

    Abolfazl Jaafari;Eric K. Zenner;Mahdi Panahi;Himan Shahabi

  • Flood susceptibility modelling using novel hybrid approach of reduced-error pruning trees with bagging and random subspace ensembles

    Wei Chen;Wei Chen;Haoyuan Hong;Haoyuan Hong;Shaojun Li;Himan Shahabi

  • Meta optimization of an adaptive neuro-fuzzy inference system with grey wolf optimizer and biogeography-based optimization algorithms for spatial prediction of landslide susceptibility

    Abolfazl Jaafari;Mahdi Panahi;Binh Thai Pham;Himan Shahabi

  • GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method

    Wei Chen;Xiaoshen Xie;Jianbing Peng;Himan Shahabi

  • Flood susceptibility assessment using integration of adaptive network-based fuzzy inference system (ANFIS) and biogeography-based optimization (BBO) and BAT algorithms (BA)

    M. Ahmadlou;M. Karimi;S. Alizadeh;A. Shirzadi

  • Shallow landslide susceptibility assessment using a novel hybrid intelligence approach

    Ataollah Shirzadi;Dieu Tien Bui;Binh Thai Pham;Karim Solaimani

  • Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms

    Viet-Ha Nhu;Ataollah Shirzadi;Himan Shahabi;Sushant K. Singh

  • Applying population-based evolutionary algorithms and a neuro-fuzzy system for modeling landslide susceptibility

    Wei Chen;Mahdi Panahi;Paraskevas Tsangaratos;Himan Shahabi

  • A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China

    Wei Chen;Ataollah Shirzadi;Himan Shahabi;Baharin Bin Ahmad

  • New Hybrids of ANFIS with Several Optimization Algorithms for Flood Susceptibility Modeling

    Dieu Tien Bui;Khabat Khosravi;Shaojun Li;Himan Shahabi

Frequent Co-Authors

Ataollah Shirzadi
Ataollah Shirzadi University of Kurdistan
Baharin Bin Ahmad
Baharin Bin Ahmad University of Technology Malaysia
Dieu Tien Bui
Dieu Tien Bui University of South-Eastern Norway
Biswajeet Pradhan
Biswajeet Pradhan University of Technology Sydney
Haoyuan Hong
Haoyuan Hong Nanjing University of Information Science and Technology
Nadhir Al-Ansari
Nadhir Al-Ansari Luleå University of Technology
Saro Lee
Saro Lee Korea Institute of Geoscience and Mineral Resources
Omid Rahmati
Omid Rahmati Agricultural Research Education And Extention Organization
John J. Clague
John J. Clague Simon Fraser University
A-Xing Zhu
A-Xing Zhu University of Wisconsin–Madison

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