Explaining Land Use Change Impacts on Ecological Quality along the China–Pakistan Economic Corridor via an RSEI and SHAP-Enhanced Machine Learning Framework

Explaining Land Use Change Impacts on Ecological Quality along the China–Pakistan Economic Corridor via an RSEI and SHAP-Enhanced Machine Learning Framework. This collection of data files contains the different datasets, TIFF images, code, tables, graphs, and results associated with the paper.

Authors

Yaochen Qin (ORCID: https://orcid.org/0000-0002-6962-8838)
Muhammad Sajid Mehmood (ORCID: https://orcid.org/0000-0002-2055-3505)
Di Lu (ORCID: https://orcid.org/0000-0002-9923-6405)
Yuming Zhao (ORCID: https://orcid.org/0000-0001-7219-0999)
Zabih Ullah
Yue Qiuhan
Hongsheng Qian
Peng Li

Institutions

Pingdingshan University (CN)
Henan University (CN)

Publication Details

Journal: Zenodo (CERN European Organization for Nuclear Research)
Published: 2026-06-26
DOI: https://doi.org/10.5281/zenodo.20900803
Primary Topic: Belt and Road Initiative
Type: article
Field-Weighted Citation Impact: 0.00

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article

Explaining Land Use Change Impacts on Ecological Quality along the China–Pakistan Economic Corridor via an RSEI and SHAP-Enhanced Machine Learning Framework

Yaochen Qin, Muhammad Sajid Mehmood, Di Lu, Yuming Zhao et al.

Jun 26, 2026

Zenodo (CERN European Organization for Nuclear Research)

Belt and Road Initiative

article

Explaining Land Use Change Impacts on Ecological Quality along the China–Pakistan Economic Corridor via an RSEI and SHAP-Enhanced Machine Learning Framework

Yaochen Qin, Muhammad Sajid Mehmood, Di Lu, Yuming Zhao, Zabih Ullah, Yue Qiuhan, Hongsheng Qian, Peng Li

June 26, 2026article en

Abstract

Explaining Land Use Change Impacts on Ecological Quality along the China–Pakistan Economic Corridor via an RSEI and SHAP-Enhanced Machine Learning Framework. This collection of data files contains the different datasets, TIFF images, code, tables, graphs, and results associated with the paper.

Zenodo (CERN European Organization for Nuclear Research)

Pingdingshan University (CN), Henan University (CN)

Openalex Percentile: Top 3%

Belt and Road Initiative

DOI Open Access PDF OpenAlex

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