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<p>This letter brings to the attention of the Editorial Board several serious methodological and analytical concerns regarding the hybrid machine learning study published by Manna and Rani (<CitationRef CitationID="CR2">2026</CitationRef>) in Environmental Monitoring and Assessment. Our review identifies multiple structural shortcomings at the levels of data design, model validation, interpretation of results, and quantitative projections. Documenting these concerns in the scientific literature would not only contribute to the correction of the study in question but would also provide a methodological reference for researchers employing similar hybrid machine learning frameworks and help establish a more rigorous basis for policy decisions related to afforestation planning.</p>

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Letter to the editor “A hybrid machine learning approach to identify potential green cover area for bio–physical suitability mapping in the western semi–arid Rarh region of West Bengal, Purulia” by Ali et al. 2026, Environmental Monitoring and Assessment, 198,571

  • 期刊论文

  • 发表日期：

    2026年7月11日

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  • Eyyup Ensar Başakın

摘要

This letter brings to the attention of the Editorial Board several serious methodological and analytical concerns regarding the hybrid machine learning study published by Manna and Rani (2026) in Environmental Monitoring and Assessment. Our review identifies multiple structural shortcomings at the levels of data design, model validation, interpretation of results, and quantitative projections. Documenting these concerns in the scientific literature would not only contribute to the correction of the study in question but would also provide a methodological reference for researchers employing similar hybrid machine learning frameworks and help establish a more rigorous basis for policy decisions related to afforestation planning.