Assessment of explainable tree-based ensemble algorithms for the enhancement of Copernicus digital elevation model in agricultural lands

Author:

Okolie Chukwuma123,Adeleke Adedayo4,Mills Jon3,Smit Julian5,Maduako Ikechukwu6,Bagheri Hossein7,Komar Tom3,Wang Shidong3

Affiliation:

1. Division of Geomatics, University of Cape Town, Cape Town, South Africa

2. Department of Surveying and Geoinformatics, University of Lagos, Lagos, Nigeria

3. School of Engineering, Newcastle University, Newcastle upon Tyne, UK

4. Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, South Africa

5. Department of Civil Engineering and Geomatics, Cape Peninsula University of Technology, Cape Town, South Africa

6. Office of Global Innovation, UNICEF, New York, USA

7. Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan, Iran

Funder

Commonwealth Scholarship Commission

University of Cape Town

Publisher

Informa UK Limited

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Comparison of machine learning and statistical approaches for Digital Elevation Model (DEM) correction: interim results;The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences;2024-06-11

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