支持向量机用于苏拉威西岛东南部肯达里登革热的易感性建模

P. Widayani, Abhista Fawwaz Sahitya, Agatha Andriantari Saputri
{"title":"支持向量机用于苏拉威西岛东南部肯达里登革热的易感性建模","authors":"P. Widayani, Abhista Fawwaz Sahitya, Agatha Andriantari Saputri","doi":"10.7494/geom.2024.18.1.29","DOIUrl":null,"url":null,"abstract":"Dengue fever (DF) is an infectious disease that is still a problem in Indonesia. The total death rate due to DF was 705 people in 2021; in 2022, this increased to 1183 (Indonesian Ministry of Health, 2023). Seeing this fact, prevention efforts are still needed when handling DF cases in all of the regions of Indonesia. This research was conducted in the Kendari area of Southeast Sulawesi, where there are still cases of DF. The purpose of this study was to create a spatial model of dengue susceptibility using a support vector machine. Landsat 8 imagery was used to intercept data on building density, vegetation density, land use, and land surface temperatures. Rainfall and humidity variables were obtained from the Meteorological, Climatological, and Geophysical Agency (BMKG). Based on the modeling results, the districts of Wua-wua, Kadia, Barunga, Poasi, and Puuwatu are areas with high susceptibility. The results of testing the susceptibility model to dengue hemorrhagic fever (DHF) in Kendari obtained an area under the curve (AUC) of 0.75, meaning that this model was well-accepted.","PeriodicalId":36672,"journal":{"name":"Geomatics and Environmental Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Support Vector Machine for Susceptibility Modeling of Dengue Fever in Kendari, Southeast Sulawesi\",\"authors\":\"P. Widayani, Abhista Fawwaz Sahitya, Agatha Andriantari Saputri\",\"doi\":\"10.7494/geom.2024.18.1.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dengue fever (DF) is an infectious disease that is still a problem in Indonesia. The total death rate due to DF was 705 people in 2021; in 2022, this increased to 1183 (Indonesian Ministry of Health, 2023). Seeing this fact, prevention efforts are still needed when handling DF cases in all of the regions of Indonesia. This research was conducted in the Kendari area of Southeast Sulawesi, where there are still cases of DF. The purpose of this study was to create a spatial model of dengue susceptibility using a support vector machine. Landsat 8 imagery was used to intercept data on building density, vegetation density, land use, and land surface temperatures. Rainfall and humidity variables were obtained from the Meteorological, Climatological, and Geophysical Agency (BMKG). Based on the modeling results, the districts of Wua-wua, Kadia, Barunga, Poasi, and Puuwatu are areas with high susceptibility. The results of testing the susceptibility model to dengue hemorrhagic fever (DHF) in Kendari obtained an area under the curve (AUC) of 0.75, meaning that this model was well-accepted.\",\"PeriodicalId\":36672,\"journal\":{\"name\":\"Geomatics and Environmental Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geomatics and Environmental Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7494/geom.2024.18.1.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geomatics and Environmental Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7494/geom.2024.18.1.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0

摘要

登革热(DF)是一种传染病,在印度尼西亚仍是一个问题。2021 年,因登革热死亡的总人数为 705 人;2022 年,这一数字增至 1183 人(印度尼西亚卫生部,2023 年)。有鉴于此,印尼各地区在处理 DF 病例时仍需开展预防工作。本研究在仍有 DF 病例的东南苏拉威西岛肯达里地区进行。本研究的目的是利用支持向量机创建登革热易感性空间模型。使用 Landsat 8 图像截取了有关建筑密度、植被密度、土地利用和地表温度的数据。降雨量和湿度变量来自气象、气候和地球物理局(BMKG)。根据建模结果,Wua-wua、Kadia、Barunga、Poasi 和 Puuwatu 地区为高易感地区。肯达里登革出血热(DHF)易感性模型的测试结果显示,曲线下面积(AUC)为 0.75,这意味着该模型的接受度很高。
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
Support Vector Machine for Susceptibility Modeling of Dengue Fever in Kendari, Southeast Sulawesi
Dengue fever (DF) is an infectious disease that is still a problem in Indonesia. The total death rate due to DF was 705 people in 2021; in 2022, this increased to 1183 (Indonesian Ministry of Health, 2023). Seeing this fact, prevention efforts are still needed when handling DF cases in all of the regions of Indonesia. This research was conducted in the Kendari area of Southeast Sulawesi, where there are still cases of DF. The purpose of this study was to create a spatial model of dengue susceptibility using a support vector machine. Landsat 8 imagery was used to intercept data on building density, vegetation density, land use, and land surface temperatures. Rainfall and humidity variables were obtained from the Meteorological, Climatological, and Geophysical Agency (BMKG). Based on the modeling results, the districts of Wua-wua, Kadia, Barunga, Poasi, and Puuwatu are areas with high susceptibility. The results of testing the susceptibility model to dengue hemorrhagic fever (DHF) in Kendari obtained an area under the curve (AUC) of 0.75, meaning that this model was well-accepted.
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
Geomatics and Environmental Engineering
Geomatics and Environmental Engineering Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
2.30
自引率
0.00%
发文量
27
期刊最新文献
Improving Traffic-noise-mitigation Strategies with LiDAR-based 3D Tree-canopy Analysis Apartment Rental Market in Border Cities of Poland and Ukraine Comparison of Statistical and Machine-Learning Model for Analyzing Landslide Susceptibility in Sumedang Area, Indonesia Sustainability Analysis of Domestic Raw Water Supply in Bandung City of Indonesia Estimation of Natural Uranium and Its Risk-Assessment in Groundwater of Bangalore Urban District of Karnataka, India
×
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