Correction: Geoscience Letters (2022) 9:26 https://doi.org/10.1186/s40562-022-00236-9

In this article [1], the affiliation details for co-authors Huanyuan Wang and Ling Han were incorrectly given as ‘School of Land Engineering, Chang’an University, Xi’ani, 710054, Shaanx, China’, but should have been ‘Shaanxi Key Laboratory of Land Consolidation, School of Land Engineering, Chang’an University, Xi’an, Shaanxi, China’

• 1. Zhang T, Li Y, Wang T, Wang H, Chen T, Sun Z, Luo D, Li C, Han L (2022) Evaluation of different machine learning models and novel deep learning-based algorithm for landslide susceptibility mapping. Geosci Lett 9:26. https://doi.org/10.1186/s40562-022-00236-9

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Authors and Affiliations

1. Key Laboratory of Degraded and Unused Land Consolidation Engineering, The Ministry of Natural Resources, Xi’an, Shaanxi, China

   Tingyu Zhang, Yanan Li, Tianqing Chen & Zenghui Sun

2. Institute of Land Engineering and Technology, Shaanxi Provincial Land Engineering Construction Group Co., Ltd, Xi’an, Shaanxi, China

   Tingyu Zhang, Yanan Li, Tianqing Chen & Zenghui Sun

3. Shaanxi Provincial Land Engineering Construction Group Land Survey Planning and Design Institute Co., Ltd, Xi’an, Shaanxi, China

   Tao Wang, Dan Luo & Chao Li

4. Shaanxi Key Laboratory of Land Consolidation, School of Land Engineering, Chang’an University, Xi’an, Shaanxi, China

   Huanyuan Wang & Ling Han

1. Tingyu ZhangView author publications

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2. Yanan LiView author publications

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3. Tao WangView author publications

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4. Huanyuan WangView author publications

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5. Tianqing ChenView author publications

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6. Zenghui SunView author publications

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7. Dan LuoView author publications

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8. Chao LiView author publications

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Correspondence to Huanyuan Wang.

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Zhang, T., Li, Y., Wang, T. et al. Correction: Evaluation of different machine learning models and novel deep learning-based algorithm for landslide susceptibility mapping. Geosci. Lett. 10, 44 (2023). https://doi.org/10.1186/s40562-023-00296-5

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• Published: 26 September 2023

• DOI: https://doi.org/10.1186/s40562-023-00296-5

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