Perdition of gully erosion susceptibility mapping using novel ensemble machine learning algorithms

被引：0
|
作者：
机构：
[1] Arabameri, Alireza
[2] Chandra Pal, Subodh
[3] 3,Costache, Romulus
[4] Saha, Asish
[5] 5,Rezaie, Fatemeh
[6] Seyed Danesh, Amir
[7] 8,9,10,Pradhan, Biswajeet
[8] 5,Lee, Saro
[9] Hoang, Nhat-Duc
来源：
Lee, Saro | 1600年 / Taylor and Francis Ltd.卷 / 12期
关键词：
Erosion - Potassium hydroxide - Adaptive boosting - Mapping - Land use - Learning systems - Machine learning - Geographic information systems - Landforms;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [21] GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of Iran
    Lei, Xinxiang
    Chen, Wei
    Avand, Mohammadtaghi
    Janizadeh, Saeid
    Kariminejad, Narges
    Shahabi, Hejar
    Costache, Romulus
    Shahabi, Himan
    Shirzadi, Ataollah
    Mosavi, Amir
    REMOTE SENSING, 2020, 12 (15)
  • [22] Gully Erosion Susceptibility Assessment Using Different Machine Learning Algorithms: A Case Study of Shazand Watershed in Iran
    Majid Mohammady
    Aliakbar Davudirad
    Environmental Modeling & Assessment, 2024, 29 : 249 - 261
  • [23] Gully Erosion Susceptibility Assessment Using Different Machine Learning Algorithms: A Case Study of Shazand Watershed in Iran
    Mohammady, Majid
    Davudirad, Aliakbar
    ENVIRONMENTAL MODELING & ASSESSMENT, 2024, 29 (02) : 249 - 261
  • [24] Gully erosion susceptibility mapping and prioritization of gully-dominant sub-watersheds using machine learning algorithms: Evidence from the Silabati River (tropical river, India)
    Hasanuzzaman, Md
    Adhikary, Partha Pratim
    Shit, Pravat Kumar
    ADVANCES IN SPACE RESEARCH, 2024, 73 (03) : 1653 - 1666
  • [25] Optimizing machine learning algorithms for spatial prediction of gully erosion susceptibility with four training scenarios
    Liu, Guoqing
    Arabameri, Alireza
    Santosh, M.
    Nalivan, Omid Asadi
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (16) : 46979 - 46996
  • [26] Optimizing machine learning algorithms for spatial prediction of gully erosion susceptibility with four training scenarios
    Guoqing Liu
    Alireza Arabameri
    M. Santosh
    Omid Asadi Nalivan
    Environmental Science and Pollution Research, 2023, 30 : 46979 - 46996
  • [27] Novel ensemble machine learning models in flood susceptibility mapping
    Prasad, Pankaj
    Loveson, Victor Joseph
    Das, Bappa
    Kotha, Mahender
    GEOCARTO INTERNATIONAL, 2022, 37 (16) : 4571 - 4593
  • [28] Machine Learning-Based Gully Erosion Susceptibility Mapping: A Case Study of Eastern India
    Saha, Sunil
    Roy, Jagabandhu
    Arabameri, Alireza
    Blaschke, Thomas
    Dieu Tien Bui
    SENSORS, 2020, 20 (05)
  • [29] Gully erosion susceptibility assessment and management of hazard-prone areas in India using different machine learning algorithms
    Gayen, Amiya
    Pourghasemi, Hamid Reza
    Saha, Sunil
    Keesstra, Saskia
    Bai, Shibiao
    SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 668 : 124 - 138
  • [30] Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility
    Chen, Wei
    Lei, Xinxiang
    Chakrabortty, Rabin
    Pal, Subodh Chandra
    Sahana, Mehebub
    Janizadeh, Saeid
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2021, 284
12345