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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Soil erosion susceptibility mapping using ensemble machine learning models: A case study of upper Congo river sub-basin
Luc Cimusa Kulimushi, Janvier Bashagaluke, Pankaj Prasad, et al.
CATENA (2022) Vol. 222, pp. 106858-106858
Closed Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Machine learning models for gully erosion susceptibility assessment in the Tensift catchment, Haouz Plain, Morocco for sustainable development
Youssef Bammou, Brahim Benzougagh, Abdessalam Ouallali, et al.
Journal of African Earth Sciences (2024) Vol. 213, pp. 105229-105229
Open Access | Times Cited: 24
Novel Ensemble Machine Learning Modeling Approach for Groundwater Potential Mapping in Parbhani District of Maharashtra, India
Md Masroor, Haroon Sajjad, Pankaj Kumar, et al.
Water (2023) Vol. 15, Iss. 3, pp. 419-419
Open Access | Times Cited: 29
Modelling of soil erosion susceptibility incorporating sediment connectivity and export at landscape scale using integrated machine learning, InVEST-SDR and Fragstats
Raj Kumar Bhattacharya, Nilanjana Das Chatterjee, Kousik Das
Journal of Environmental Management (2024) Vol. 353, pp. 120164-120164
Closed Access | Times Cited: 13
Enhancing wildfire mapping accuracy using mono-temporal Sentinel-2 data: A novel approach through qualitative and quantitative feature selection with explainable AI
Linh Nguyen Van, Vinh Ngoc Tran, Giang V. Nguyen, et al.
Ecological Informatics (2024) Vol. 81, pp. 102601-102601
Open Access | Times Cited: 10
Evaluating landslide susceptibility: the impact of resolution and hybrid integration approaches
Xia Zhao, Wei Chen, Paraskevas Tsangaratos, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
Electronic sensing combined with machine learning models for predicting soil nutrient content
Shuyan Liu, Xuegeng Chen, Xiaomeng Xia, et al.
Computers and Electronics in Agriculture (2024) Vol. 221, pp. 108947-108947
Closed Access | Times Cited: 5
Integration of multi-temporal SAR data and robust machine learning models for improvement of flood susceptibility assessment in the southwest coast of India
Pankaj Prasad, Sourav Mandal, Sahil Naik, et al.
Applied Computing and Geosciences (2024) Vol. 24, pp. 100189-100189
Open Access | Times Cited: 5
Optimizing Stacked Ensemble Machine Learning Models for Accurate Wildfire Severity Mapping
Linh Nguyen Van, Giha Lee
Remote Sensing (2025) Vol. 17, Iss. 5, pp. 854-854
Open Access
Evaluating soil erosion zones in the Kangsabati River basin using a stacking framework and SHAP model: a comparative study of machine learning approaches
Javed Mallick, Saeed Alqadhi, Swapan Talukdar, et al.
Environmental Sciences Europe (2025) Vol. 37, Iss. 1
Open Access
Forest fire susceptibility mapping using multi-criteria decision making and machine learning models in the Western Ghats of India
A. R. Uthappa, Bappa Das, Anurag Raizada, et al.
Journal of Environmental Management (2025) Vol. 379, pp. 124777-124777
Closed Access
Prediction of Vanadium Contamination Distribution Pattern Through Remote Sensing Image Fusion and Machine Learning
Z. G. Zhao, Yuman Sun, Weiwei Jia, et al.
Remote Sensing (2025) Vol. 17, Iss. 7, pp. 1164-1164
Open Access
Integrating conventional and remote sensing with DC resistivity datasets to map groundwater potential areas using the analytical hierarchy process method, North Wadi Diit, Egypt
Mohamed A. Genedi, Noura Gouhar, Gad El‐Qady, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Prediction of gully erosion susceptibility through the lens of the SHapley Additive exPlanations (SHAP) method using a stacking ensemble model
Jeongho Han, Jorge A. Guzmán, Maria L. Chu
Journal of Environmental Management (2025) Vol. 383, pp. 125478-125478
Open Access
Renewable energy, forest cover, export diversification, and ecological footprint: a machine learning application in moderating eco-innovations on agriculture in the BRICS-T economies
Hemachandra Padhan, Sudeshna Ghosh, Shawkat Hammoudeh
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 35, pp. 83771-83791
Open Access | Times Cited: 10
Predictive machine learning for gully susceptibility modeling with geo-environmental covariates: main drivers, model performance, and computational efficiency
Kwanele Phinzi, Szilárd Szabó
Natural Hazards (2024) Vol. 120, Iss. 8, pp. 7211-7244
Open Access | Times Cited: 3
Monitoring Soil Salinity Classes through Remote Sensing-Based Ensemble Learning Concept: Considering Scale Effects
Huifang Chen, Jingwei Wu, Chi Xu
Remote Sensing (2024) Vol. 16, Iss. 4, pp. 642-642
Open Access | Times Cited: 2
Soil erosion susceptibility prediction using ensemble hybrid models with multicriteria decision-making analysis: Case study of the Medjerda basin, northern Africa
Asma Bouamrane, Hamouda Boutaghane, Ali Bouamrane, et al.
International Journal of Sediment Research (2024) Vol. 39, Iss. 6, pp. 998-1014
Open Access | Times Cited: 2
Assessment of soil erosion risk and vulnerability in the transboundary Sio-Malaba-Malakisi watershed in Kenya and Uganda
Stanley Chasia, Luke Olang, Claudia Bess, et al.
Journal of Environmental Management (2024) Vol. 370, pp. 122916-122916
Closed Access | Times Cited: 2
Threshold-based inventory for flood susceptibility assessment of the world’s largest river island using multi-temporal SAR data and ensemble machine learning algorithms
Pankaj Prasad, Dipjyoti Gogoi, Debashish Gogoi, et al.
Stochastic Environmental Research and Risk Assessment (2024)
Closed Access | Times Cited: 2
Identification of gully erosion activity and its influencing factors: A case study of the Sunshui River Basin
Fengjie Fan, Xingli Gu, Jun Luo, et al.
PLoS ONE (2024) Vol. 19, Iss. 11, pp. e0309672-e0309672
Open Access | Times Cited: 2
Land degradation vulnerability mapping in a west coast river basin of India using analytical hierarchy process combined machine learning models
Bappa Das, Sujeet Desai, Amrita Daripa, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 35, pp. 83975-83990
Open Access | Times Cited: 6
Developing a hybrid deep learning model with explainable artificial intelligence (XAI) for enhanced landslide susceptibility modeling and management
Saeed Alqadhi, Javed Mallick, Meshel Q. Alkahtani, et al.
Natural Hazards (2023) Vol. 120, Iss. 4, pp. 3719-3747
Closed Access | Times Cited: 5
Assessment of Land Degradation and Droughts in an Arid Area Using Drought Indices, Modified Soil-Adjusted Vegetation Index and Landsat Remote Sensing Data
A. Derdour, Antonio Jódar-Abellán, Amparo Melián Navarro, et al.
Cuadernos de Investigación Geográfica (2023) Vol. 49, Iss. 2, pp. 65-81
Open Access | Times Cited: 4
Accommodating uncertainty in soil erosion risk assessment: Integration of Bayesian belief networks and MPSIAC model
Hossein Bashari, Abdolhossein Boali, Saeid Soltani
Natural Hazards Research (2023) Vol. 4, Iss. 1, pp. 134-147
Open Access | Times Cited: 4
Classification of Soil Horizons Based on Visnir and Swir Hyperespectral Images and Machine Learning Models
Karym Mayara de Oliveira, João Vitor Ferreira Gonçalves, Renan Falcioni, et al.
(2024)
Closed Access | Times Cited: 1
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