Landslide susceptibility prediction considering land use change and human activity: A case study under rapid urban expansion and afforestation in China
China has been subject to rapid urban expansion and afforestation since the economic reform in 1978. However, the influence of land use and cover changes (LUCCs) and human activities on landslide occurrence is often ignored in landslide susceptibility mapping and zonation (LSMZ). In this study, Ensh...
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| Published in | The Science of the total environment Vol. 866; p. 161430 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier B.V
25.03.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0048-9697 1879-1026 1879-1026 |
| DOI | 10.1016/j.scitotenv.2023.161430 |
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| Abstract | China has been subject to rapid urban expansion and afforestation since the economic reform in 1978. However, the influence of land use and cover changes (LUCCs) and human activities on landslide occurrence is often ignored in landslide susceptibility mapping and zonation (LSMZ). In this study, Enshi City, China, was selected as the study area because of dramatic LUCCs during the last two decades. This study divided landslide affecting factors (AFs) into base affecting factors (BAFs) and land-related affecting factors (LAFs), and 15 landslide susceptibility maps were created by three different types of models. The results showed that the combination 6 of heuristic multi-layer perceptron model with LAFs (HMLP-LAFC6) model obtained the highest model performance. In addition, any factor combinations of HMLP-LAF model outperformed other two types of models, and the use of land use and cover (LULC) in different periods as well as LUCCs may significantly impact the model performance. Given that land policy adjustments are normally core drivers of LUCC in China, a land planning based LSMZ framework was proposed, which is suitable for LSMZ in rapid LUCC regions with radical land policies. Finally, this paper strongly suggests developing more hybrid models that coupling dynamic AFs, clarifying the quantitative boundaries of time-irrelevant and dynamic AFs, increasing the accuracy of LULC prediction, and improving the abilities of bilateral understanding for effective, integrated, and systematic management of land planning and landslide hazards.
[Display omitted]
•The effects urban expansion and afforestation on landslide occurrence was discussed.•A hybrid model was designed to solve the dynamic LULC issue in LSMZ.•HMLP-LAFC6 model obtained the highest model performance among 15 models.•HMLP-LAF model enable to significantly increase the model performance.•A land planning-based framework of LSMZ with LUCC and LULC prediction was proposed. |
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| AbstractList | China has been subject to rapid urban expansion and afforestation since the economic reform in 1978. However, the influence of land use and cover changes (LUCCs) and human activities on landslide occurrence is often ignored in landslide susceptibility mapping and zonation (LSMZ). In this study, Enshi City, China, was selected as the study area because of dramatic LUCCs during the last two decades. This study divided landslide affecting factors (AFs) into base affecting factors (BAFs) and land-related affecting factors (LAFs), and 15 landslide susceptibility maps were created by three different types of models. The results showed that the combination 6 of heuristic multi-layer perceptron model with LAFs (HMLP-LAFC6) model obtained the highest model performance. In addition, any factor combinations of HMLP-LAF model outperformed other two types of models, and the use of land use and cover (LULC) in different periods as well as LUCCs may significantly impact the model performance. Given that land policy adjustments are normally core drivers of LUCC in China, a land planning based LSMZ framework was proposed, which is suitable for LSMZ in rapid LUCC regions with radical land policies. Finally, this paper strongly suggests developing more hybrid models that coupling dynamic AFs, clarifying the quantitative boundaries of time-irrelevant and dynamic AFs, increasing the accuracy of LULC prediction, and improving the abilities of bilateral understanding for effective, integrated, and systematic management of land planning and landslide hazards.China has been subject to rapid urban expansion and afforestation since the economic reform in 1978. However, the influence of land use and cover changes (LUCCs) and human activities on landslide occurrence is often ignored in landslide susceptibility mapping and zonation (LSMZ). In this study, Enshi City, China, was selected as the study area because of dramatic LUCCs during the last two decades. This study divided landslide affecting factors (AFs) into base affecting factors (BAFs) and land-related affecting factors (LAFs), and 15 landslide susceptibility maps were created by three different types of models. The results showed that the combination 6 of heuristic multi-layer perceptron model with LAFs (HMLP-LAFC6) model obtained the highest model performance. In addition, any factor combinations of HMLP-LAF model outperformed other two types of models, and the use of land use and cover (LULC) in different periods as well as LUCCs may significantly impact the model performance. Given that land policy adjustments are normally core drivers of LUCC in China, a land planning based LSMZ framework was proposed, which is suitable for LSMZ in rapid LUCC regions with radical land policies. Finally, this paper strongly suggests developing more hybrid models that coupling dynamic AFs, clarifying the quantitative boundaries of time-irrelevant and dynamic AFs, increasing the accuracy of LULC prediction, and improving the abilities of bilateral understanding for effective, integrated, and systematic management of land planning and landslide hazards. China has been subject to rapid urban expansion and afforestation since the economic reform in 1978. However, the influence of land use and cover changes (LUCCs) and human activities on landslide occurrence is often ignored in landslide susceptibility mapping and zonation (LSMZ). In this study, Enshi City, China, was selected as the study area because of dramatic LUCCs during the last two decades. This study divided landslide affecting factors (AFs) into base affecting factors (BAFs) and land-related affecting factors (LAFs), and 15 landslide susceptibility maps were created by three different types of models. The results showed that the combination 6 of heuristic multi-layer perceptron model with LAFs (HMLP-LAFC₆) model obtained the highest model performance. In addition, any factor combinations of HMLP-LAF model outperformed other two types of models, and the use of land use and cover (LULC) in different periods as well as LUCCs may significantly impact the model performance. Given that land policy adjustments are normally core drivers of LUCC in China, a land planning based LSMZ framework was proposed, which is suitable for LSMZ in rapid LUCC regions with radical land policies. Finally, this paper strongly suggests developing more hybrid models that coupling dynamic AFs, clarifying the quantitative boundaries of time-irrelevant and dynamic AFs, increasing the accuracy of LULC prediction, and improving the abilities of bilateral understanding for effective, integrated, and systematic management of land planning and landslide hazards. China has been subject to rapid urban expansion and afforestation since the economic reform in 1978. However, the influence of land use and cover changes (LUCCs) and human activities on landslide occurrence is often ignored in landslide susceptibility mapping and zonation (LSMZ). In this study, Enshi City, China, was selected as the study area because of dramatic LUCCs during the last two decades. This study divided landslide affecting factors (AFs) into base affecting factors (BAFs) and land-related affecting factors (LAFs), and 15 landslide susceptibility maps were created by three different types of models. The results showed that the combination 6 of heuristic multi-layer perceptron model with LAFs (HMLP-LAFC ) model obtained the highest model performance. In addition, any factor combinations of HMLP-LAF model outperformed other two types of models, and the use of land use and cover (LULC) in different periods as well as LUCCs may significantly impact the model performance. Given that land policy adjustments are normally core drivers of LUCC in China, a land planning based LSMZ framework was proposed, which is suitable for LSMZ in rapid LUCC regions with radical land policies. Finally, this paper strongly suggests developing more hybrid models that coupling dynamic AFs, clarifying the quantitative boundaries of time-irrelevant and dynamic AFs, increasing the accuracy of LULC prediction, and improving the abilities of bilateral understanding for effective, integrated, and systematic management of land planning and landslide hazards. China has been subject to rapid urban expansion and afforestation since the economic reform in 1978. However, the influence of land use and cover changes (LUCCs) and human activities on landslide occurrence is often ignored in landslide susceptibility mapping and zonation (LSMZ). In this study, Enshi City, China, was selected as the study area because of dramatic LUCCs during the last two decades. This study divided landslide affecting factors (AFs) into base affecting factors (BAFs) and land-related affecting factors (LAFs), and 15 landslide susceptibility maps were created by three different types of models. The results showed that the combination 6 of heuristic multi-layer perceptron model with LAFs (HMLP-LAFC6) model obtained the highest model performance. In addition, any factor combinations of HMLP-LAF model outperformed other two types of models, and the use of land use and cover (LULC) in different periods as well as LUCCs may significantly impact the model performance. Given that land policy adjustments are normally core drivers of LUCC in China, a land planning based LSMZ framework was proposed, which is suitable for LSMZ in rapid LUCC regions with radical land policies. Finally, this paper strongly suggests developing more hybrid models that coupling dynamic AFs, clarifying the quantitative boundaries of time-irrelevant and dynamic AFs, increasing the accuracy of LULC prediction, and improving the abilities of bilateral understanding for effective, integrated, and systematic management of land planning and landslide hazards. [Display omitted] •The effects urban expansion and afforestation on landslide occurrence was discussed.•A hybrid model was designed to solve the dynamic LULC issue in LSMZ.•HMLP-LAFC6 model obtained the highest model performance among 15 models.•HMLP-LAF model enable to significantly increase the model performance.•A land planning-based framework of LSMZ with LUCC and LULC prediction was proposed. |
| ArticleNumber | 161430 |
| Author | Xiong, Hanxiang Ma, Chuanming Li, Minghong Wang, Yuzhou Tan, Jiayao |
| Author_xml | – sequence: 1 givenname: Hanxiang surname: Xiong fullname: Xiong, Hanxiang email: hanxiangxiong@cug.edu.cn – sequence: 2 givenname: Chuanming surname: Ma fullname: Ma, Chuanming email: machuanming@cug.edu.cn – sequence: 3 givenname: Minghong surname: Li fullname: Li, Minghong – sequence: 4 givenname: Jiayao surname: Tan fullname: Tan, Jiayao – sequence: 5 givenname: Yuzhou surname: Wang fullname: Wang, Yuzhou |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36623663$$D View this record in MEDLINE/PubMed |
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| Keywords | ANN LS MLP-BAF FN Urban expansion AHP AUROC FPR FP LUCC SPI WLC MLP OA LSMZ TPR HMLP-LAFCn MLP-LAF MF NFR GD LULC AF Land use change BAF ROC TWI HMLP-LAF Afforestation DEM LAF TOL CTA VIF CTF FTC Human activity GTA NC CTG GTC MCDA FTG GTF TN Landslide susceptibility TP |
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