{"title":"解读贝叶斯优化深度学习模型，加强水土流失易发性预测和管理：印度东部案例研究","authors":"Meshel Alkahtani, Javed Mallick, Saeed Alqadhi, Md Nawaj Sarif, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo","doi":"10.1080/10106049.2024.2367611","DOIUrl":null,"url":null,"abstract":"Soil erosion poses a significant threat to sustainable land management and agricultural productivity. Addressing this issue requires advanced predictive models that can accurately identify areas at...","PeriodicalId":12532,"journal":{"name":"Geocarto International","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Interpretation of Bayesian-optimized deep learning models for enhancing soil erosion susceptibility prediction and management: a case study of Eastern India\",\"authors\":\"Meshel Alkahtani, Javed Mallick, Saeed Alqadhi, Md Nawaj Sarif, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo\",\"doi\":\"10.1080/10106049.2024.2367611\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Soil erosion poses a significant threat to sustainable land management and agricultural productivity. Addressing this issue requires advanced predictive models that can accurately identify areas at...\",\"PeriodicalId\":12532,\"journal\":{\"name\":\"Geocarto International\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geocarto International\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/10106049.2024.2367611\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geocarto International","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/10106049.2024.2367611","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Interpretation of Bayesian-optimized deep learning models for enhancing soil erosion susceptibility prediction and management: a case study of Eastern India
Soil erosion poses a significant threat to sustainable land management and agricultural productivity. Addressing this issue requires advanced predictive models that can accurately identify areas at...
期刊介绍：
Geocarto International is a professional academic journal serving the world-wide scientific and user community in the fields of remote sensing, GIS, geoscience and environmental sciences. The journal is designed: to promote multidisciplinary research in and application of remote sensing and GIS in geosciences and environmental sciences; to enhance international exchange of information on new developments and applications in the field of remote sensing and GIS and related disciplines; to foster interest in and understanding of science and applications on remote sensing and GIS technologies; and to encourage the publication of timely papers and research results on remote sensing and GIS applications in geosciences and environmental sciences from the world-wide science community.
The journal welcomes contributions on the following: precise, illustrated papers on new developments, technologies and applications of remote sensing; research results in remote sensing, GISciences and related disciplines;
Reports on new and innovative applications and projects in these areas; and assessment and evaluation of new remote sensing and GIS equipment, software and hardware.
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