遥感方法在尼日利亚索科托平原地质解释中的应用

IF 0.3 Q4 REMOTE SENSING South African Journal of Geomatics Pub Date : 2019-02-27 DOI:10.4314/SAJG.V7I3.12
Aisabokhae Joseph, O. Bamidele
{"title":"遥感方法在尼日利亚索科托平原地质解释中的应用","authors":"Aisabokhae Joseph, O. Bamidele","doi":"10.4314/SAJG.V7I3.12","DOIUrl":null,"url":null,"abstract":"Landsat-8 OLI imagery of Sokoto, Nigeria, was processed to emphasize the geology features and mineral potential of the area. Band ratios   were assigned to RGB. Band ratio  highlights ferric ion minerals,  emphasizes ferrous minerals, and  distinguishes iron oxide minerals from carbonate minerals. In a second technique, band ratio  was replaced with  in order to accentuate clay minerals with high reflectance within band 7. The last technique evaluated in this study used spectral information from minimum noise fraction image to map surface geology. Supervised classification training sites were selected using five classes (clay, ironstone, alteration zone, water and vegetation). The band ratio classification using maximum likelihood classification was fairly accurate and matched the geologic map of the area, also showing an alteration zone that coincided with the migmatite-quartz/mica schist contact. The classified image was finally passed through a filtering effect for generalization of the data. This filtering effect was helpful in discriminating the pixels of ironstone and those of the alteration zone on the classified map.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2019-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4314/SAJG.V7I3.12","citationCount":"6","resultStr":"{\"title\":\"Application of remote sensing method for geological interpretation of Sokoto Plain, Nigeria\",\"authors\":\"Aisabokhae Joseph, O. Bamidele\",\"doi\":\"10.4314/SAJG.V7I3.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Landsat-8 OLI imagery of Sokoto, Nigeria, was processed to emphasize the geology features and mineral potential of the area. Band ratios   were assigned to RGB. Band ratio  highlights ferric ion minerals,  emphasizes ferrous minerals, and  distinguishes iron oxide minerals from carbonate minerals. In a second technique, band ratio  was replaced with  in order to accentuate clay minerals with high reflectance within band 7. The last technique evaluated in this study used spectral information from minimum noise fraction image to map surface geology. Supervised classification training sites were selected using five classes (clay, ironstone, alteration zone, water and vegetation). The band ratio classification using maximum likelihood classification was fairly accurate and matched the geologic map of the area, also showing an alteration zone that coincided with the migmatite-quartz/mica schist contact. The classified image was finally passed through a filtering effect for generalization of the data. This filtering effect was helpful in discriminating the pixels of ironstone and those of the alteration zone on the classified map.\",\"PeriodicalId\":43854,\"journal\":{\"name\":\"South African Journal of Geomatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2019-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.4314/SAJG.V7I3.12\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South African Journal of Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/SAJG.V7I3.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/SAJG.V7I3.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 6

摘要

对尼日利亚索科托的Landsat-8 OLI图像进行了处理,以强调该地区的地质特征和矿产潜力。波段比率分配给RGB。波段比突出铁离子矿物,强调亚铁矿物,将氧化铁矿物与碳酸盐矿物区分开来。在第二种技术中,为了突出波段7内高反射率的粘土矿物,将波段比替换为。本文评价的最后一种技术是利用最小噪声分数图像的光谱信息来绘制地表地质。采用粘土、铁石、蚀变带、水体和植被5个类别选择监督分类训练场地。最大似然分类的带比分类较为准确,与该地区的地质图吻合,并显示出与混辉岩-石英/云母片岩接触相吻合的蚀变带。最后对分类后的图像进行滤波处理,实现数据的泛化。这种滤波效果有助于在分类图上区分铁矿和蚀变带的像元。
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
Application of remote sensing method for geological interpretation of Sokoto Plain, Nigeria
Landsat-8 OLI imagery of Sokoto, Nigeria, was processed to emphasize the geology features and mineral potential of the area. Band ratios   were assigned to RGB. Band ratio  highlights ferric ion minerals,  emphasizes ferrous minerals, and  distinguishes iron oxide minerals from carbonate minerals. In a second technique, band ratio  was replaced with  in order to accentuate clay minerals with high reflectance within band 7. The last technique evaluated in this study used spectral information from minimum noise fraction image to map surface geology. Supervised classification training sites were selected using five classes (clay, ironstone, alteration zone, water and vegetation). The band ratio classification using maximum likelihood classification was fairly accurate and matched the geologic map of the area, also showing an alteration zone that coincided with the migmatite-quartz/mica schist contact. The classified image was finally passed through a filtering effect for generalization of the data. This filtering effect was helpful in discriminating the pixels of ironstone and those of the alteration zone on the classified map.
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
自引率
0.00%
发文量
82
期刊最新文献
Classification of 3D Sonar Point Clouds derived Underwater using Machine and Deep Learning (CANUPO and RandLA-Net) Approaches Characterising the evolution of the urban form of zones that accommodate warehousing clusters in the City of Cape Town municipality Error Analysis in Multibeam Hydrographic Survey System Temporal Characterization of Land Use Change and Land-scape Processes in Informal Settlements in the City of Cape Town, South Africa Analysis of thermally-induced displacements of the HartRAO Lunar Laser Ranger optical tube: impact on pointing
×
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