绘制土壤侵蚀易感性地图:神经网络与模糊-AHP 技术的比较

IF 2.8 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Environmental Earth Sciences Pub Date : 2024-09-24 DOI:10.1007/s12665-024-11869-8
Marzieh Mokarram, Hamid Reza Pourghasemi, John P. Tiefenbacher, Tam Minh Pham
{"title":"绘制土壤侵蚀易感性地图:神经网络与模糊-AHP 技术的比较","authors":"Marzieh Mokarram,&nbsp;Hamid Reza Pourghasemi,&nbsp;John P. Tiefenbacher,&nbsp;Tam Minh Pham","doi":"10.1007/s12665-024-11869-8","DOIUrl":null,"url":null,"abstract":"<div><p>The purpose of this research was to model areas prone to erosion in the Gol-Mehran catchment in southern Iran. For this purpose, the soil erosion map was determined using membership functions and analytic hierarchy process (AHP) determined the soil erosion map. Additionally, using the self-organizing map (SOM) and principal component analysis (PCA) methods, the most crucial parameters affecting gully erosion were extracted. Finally, soil erosion was predicted using a multilayer perceptron (MLP) and radial basis function. The results of the fuzzy AHP method with all data and the selected data with SOM and PCA demonstrated that areas located in the center of the region were prone to gully erosion. The results of this research also demonstrated that urban lands have expanded significantly, while vegetation has decreased from 1990 to 2019, which has had a significant impact on soil erosion. The results also showed that the MLP model, with R<sup>2</sup> = 0.97, could accurately predict soil erosion.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"83 19","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mapping soil erosion susceptibility: a comparison of neural networks and fuzzy-AHP techniques\",\"authors\":\"Marzieh Mokarram,&nbsp;Hamid Reza Pourghasemi,&nbsp;John P. Tiefenbacher,&nbsp;Tam Minh Pham\",\"doi\":\"10.1007/s12665-024-11869-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The purpose of this research was to model areas prone to erosion in the Gol-Mehran catchment in southern Iran. For this purpose, the soil erosion map was determined using membership functions and analytic hierarchy process (AHP) determined the soil erosion map. Additionally, using the self-organizing map (SOM) and principal component analysis (PCA) methods, the most crucial parameters affecting gully erosion were extracted. Finally, soil erosion was predicted using a multilayer perceptron (MLP) and radial basis function. The results of the fuzzy AHP method with all data and the selected data with SOM and PCA demonstrated that areas located in the center of the region were prone to gully erosion. The results of this research also demonstrated that urban lands have expanded significantly, while vegetation has decreased from 1990 to 2019, which has had a significant impact on soil erosion. The results also showed that the MLP model, with R<sup>2</sup> = 0.97, could accurately predict soil erosion.</p></div>\",\"PeriodicalId\":542,\"journal\":{\"name\":\"Environmental Earth Sciences\",\"volume\":\"83 19\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Earth Sciences\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12665-024-11869-8\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Earth Sciences","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s12665-024-11869-8","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

这项研究的目的是为伊朗南部戈尔-梅赫兰集水区易受侵蚀的地区建立模型。为此,利用成员函数和层次分析法(AHP)确定了土壤侵蚀图。此外,利用自组织图(SOM)和主成分分析(PCA)方法,提取了影响沟壑侵蚀的最关键参数。最后,使用多层感知器(MLP)和径向基函数对土壤侵蚀进行了预测。采用模糊 AHP 方法处理所有数据以及采用 SOM 和 PCA 方法处理选定数据的结果表明,位于区域中心的地区容易发生沟壑侵蚀。研究结果还表明,从 1990 年到 2019 年,城市用地明显扩大,而植被却在减少,这对水土流失产生了重大影响。研究结果还表明,R2 = 0.97 的 MLP 模型可以准确预测土壤侵蚀。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Mapping soil erosion susceptibility: a comparison of neural networks and fuzzy-AHP techniques

The purpose of this research was to model areas prone to erosion in the Gol-Mehran catchment in southern Iran. For this purpose, the soil erosion map was determined using membership functions and analytic hierarchy process (AHP) determined the soil erosion map. Additionally, using the self-organizing map (SOM) and principal component analysis (PCA) methods, the most crucial parameters affecting gully erosion were extracted. Finally, soil erosion was predicted using a multilayer perceptron (MLP) and radial basis function. The results of the fuzzy AHP method with all data and the selected data with SOM and PCA demonstrated that areas located in the center of the region were prone to gully erosion. The results of this research also demonstrated that urban lands have expanded significantly, while vegetation has decreased from 1990 to 2019, which has had a significant impact on soil erosion. The results also showed that the MLP model, with R2 = 0.97, could accurately predict soil erosion.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Environmental Earth Sciences
Environmental Earth Sciences 环境科学-地球科学综合
CiteScore
5.10
自引率
3.60%
发文量
494
审稿时长
8.3 months
期刊介绍: Environmental Earth Sciences is an international multidisciplinary journal concerned with all aspects of interaction between humans, natural resources, ecosystems, special climates or unique geographic zones, and the earth: Water and soil contamination caused by waste management and disposal practices Environmental problems associated with transportation by land, air, or water Geological processes that may impact biosystems or humans Man-made or naturally occurring geological or hydrological hazards Environmental problems associated with the recovery of materials from the earth Environmental problems caused by extraction of minerals, coal, and ores, as well as oil and gas, water and alternative energy sources Environmental impacts of exploration and recultivation – Environmental impacts of hazardous materials Management of environmental data and information in data banks and information systems Dissemination of knowledge on techniques, methods, approaches and experiences to improve and remediate the environment In pursuit of these topics, the geoscientific disciplines are invited to contribute their knowledge and experience. Major disciplines include: hydrogeology, hydrochemistry, geochemistry, geophysics, engineering geology, remediation science, natural resources management, environmental climatology and biota, environmental geography, soil science and geomicrobiology.
期刊最新文献
Study on the influence of pipe jacking construction on existing subway tunnels Study on progressive damage and deformation law of coal body around borehole under different moisture states Hydrochemical stratigraphic analysis of the filling of the Meirama open pit mine II: parameters and elements Detection and comprehensive treatment for giant karst caves under the tunnel floor: a case study in Guangxi, China Mineralogical compositions and distributions of trace and rare earth elements in Eocene carbonaceous sediments of Western India: implications for paleoenvironment during peat accumulation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1