100 m soil landscape grids of Canada
Abstract With the latest collection of soil point and available co-variables data, 100 m grids of soil type and selected soil attributes of Canada are developed. While model-based statistical validations during the machine learning runs are satisfactory, limited independent statistical validations a...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05460-4 |
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| _version_ | 1849344807655178240 |
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| author | Xiaoyuan Geng Juanxia He Victoria Grima Yefang Jiang Maggi Tetreau Stephen Crittenden Simon Kiley Albert. J. VandenBygaart Jason Vanrobaeys |
| author_facet | Xiaoyuan Geng Juanxia He Victoria Grima Yefang Jiang Maggi Tetreau Stephen Crittenden Simon Kiley Albert. J. VandenBygaart Jason Vanrobaeys |
| author_sort | Xiaoyuan Geng |
| collection | DOAJ |
| description | Abstract With the latest collection of soil point and available co-variables data, 100 m grids of soil type and selected soil attributes of Canada are developed. While model-based statistical validations during the machine learning runs are satisfactory, limited independent statistical validations are also made. The 100 m soil landscape grids can be used for national and regional soil organic carbon stock inventory and carbon sequestration assessment. There are also potential applications for soil health, soil erosion, land suitability and other large area-based modelling and applications. |
| format | Article |
| id | doaj-art-9b3e1c2b6b634584a9acd049c8dfd986 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-9b3e1c2b6b634584a9acd049c8dfd9862025-08-20T03:42:34ZengNature PortfolioScientific Data2052-44632025-07-0112111210.1038/s41597-025-05460-4100 m soil landscape grids of CanadaXiaoyuan Geng0Juanxia He1Victoria Grima2Yefang Jiang3Maggi Tetreau4Stephen Crittenden5Simon Kiley6Albert. J. VandenBygaart7Jason Vanrobaeys8Science and Technology Branch, Agriculture and Agri-Food CanadaScience and Technology Branch, Agriculture and Agri-Food CanadaSwan Lake First Nation, Swan Lake Land Governance OfficeScience and Technology Branch, Agriculture and Agri-Food CanadaParks CanadaScience and Technology Branch, Agriculture and Agri-Food CanadaScience and Technology Branch, Agriculture and Agri-Food CanadaScience and Technology Branch, Agriculture and Agri-Food CanadaPest Management Regulatory Agency, Health CanadaAbstract With the latest collection of soil point and available co-variables data, 100 m grids of soil type and selected soil attributes of Canada are developed. While model-based statistical validations during the machine learning runs are satisfactory, limited independent statistical validations are also made. The 100 m soil landscape grids can be used for national and regional soil organic carbon stock inventory and carbon sequestration assessment. There are also potential applications for soil health, soil erosion, land suitability and other large area-based modelling and applications.https://doi.org/10.1038/s41597-025-05460-4 |
| spellingShingle | Xiaoyuan Geng Juanxia He Victoria Grima Yefang Jiang Maggi Tetreau Stephen Crittenden Simon Kiley Albert. J. VandenBygaart Jason Vanrobaeys 100 m soil landscape grids of Canada Scientific Data |
| title | 100 m soil landscape grids of Canada |
| title_full | 100 m soil landscape grids of Canada |
| title_fullStr | 100 m soil landscape grids of Canada |
| title_full_unstemmed | 100 m soil landscape grids of Canada |
| title_short | 100 m soil landscape grids of Canada |
| title_sort | 100 m soil landscape grids of canada |
| url | https://doi.org/10.1038/s41597-025-05460-4 |
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