Mobile-based image interpretation and geotagging using artificial intelligence and open-source geospatial technology

IF 2.3 Q2 REMOTE SENSING Applied Geomatics Pub Date : 2023-09-07 DOI:10.1007/s12518-023-00522-x
Arati Paul, Sakshi Chauhan, Dibyendu Dutta
{"title":"Mobile-based image interpretation and geotagging using artificial intelligence and open-source geospatial technology","authors":"Arati Paul,&nbsp;Sakshi Chauhan,&nbsp;Dibyendu Dutta","doi":"10.1007/s12518-023-00522-x","DOIUrl":null,"url":null,"abstract":"<div><p>Image geotagging is a process where geographic coordinates are attached to an image. Mobile-based geotagging application has many advantages, viz. real-time monitoring, ensuring data authenticity etc. Since an ordinary mobile camera cannot interpret the geotagged images, they are manually analysed later for a specific purpose. Therefore, the human interpreters are to put their time and effort to analyse the images. This becomes difficult when the number of images is more. The heterogeneity of captured images, in terms of intensity, viewing angle etc., limits the application of traditional image processing techniques for automatic image interpretation. Hence, artificial intelligence (AI)–based image processing technique needs to be employed that enables machines to learn from instances and provide assistance in field photo interpretation. In the present work, a smartphone-based application, embedded with enhanced capabilities of AI and geospatial technology, has been developed using open-source technology. The application employs AI to detect certain categories’ semantic objects and automatically generates their details. The mean of detection precision, recall and F1 score are estimated as 0.96, 0.91 and 0.93, respectively. The present work successfully demonstrates the use of open-source technology for AI-enabled geotagging and dissemination of ground information through WebGIS application.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"15 4","pages":"795 - 805"},"PeriodicalIF":2.3000,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-023-00522-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0

Abstract

Image geotagging is a process where geographic coordinates are attached to an image. Mobile-based geotagging application has many advantages, viz. real-time monitoring, ensuring data authenticity etc. Since an ordinary mobile camera cannot interpret the geotagged images, they are manually analysed later for a specific purpose. Therefore, the human interpreters are to put their time and effort to analyse the images. This becomes difficult when the number of images is more. The heterogeneity of captured images, in terms of intensity, viewing angle etc., limits the application of traditional image processing techniques for automatic image interpretation. Hence, artificial intelligence (AI)–based image processing technique needs to be employed that enables machines to learn from instances and provide assistance in field photo interpretation. In the present work, a smartphone-based application, embedded with enhanced capabilities of AI and geospatial technology, has been developed using open-source technology. The application employs AI to detect certain categories’ semantic objects and automatically generates their details. The mean of detection precision, recall and F1 score are estimated as 0.96, 0.91 and 0.93, respectively. The present work successfully demonstrates the use of open-source technology for AI-enabled geotagging and dissemination of ground information through WebGIS application.

Abstract Image

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
使用人工智能和开源地理空间技术的基于移动设备的图像解释和地理标记
图像地理标记是将地理坐标附加到图像上的过程。基于移动设备的地理标记应用具有实时监控、保证数据真实性等优点。由于普通的移动相机无法解释这些带有地理标记的图像,因此需要稍后对它们进行人工分析,以达到特定的目的。因此,口译员要花时间和精力分析这些图像。当图像数量较多时,这就变得困难了。捕获图像在强度、视角等方面的异质性限制了传统图像处理技术在自动图像判读中的应用。因此,需要采用基于人工智能(AI)的图像处理技术,使机器能够从实例中学习,并在现场照片解释中提供帮助。在目前的工作中,使用开源技术开发了基于智能手机的应用程序,嵌入了增强的人工智能和地理空间技术功能。该应用程序使用人工智能来检测某些类别的语义对象,并自动生成其详细信息。检测精度、召回率和F1得分的平均值分别为0.96、0.91和0.93。目前的工作成功地展示了通过WebGIS应用程序使用开源技术进行人工智能地理标记和地面信息传播。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Applied Geomatics
Applied Geomatics REMOTE SENSING-
CiteScore
5.40
自引率
3.70%
发文量
61
期刊介绍: Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences. The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology. Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements
期刊最新文献
Interphase modeling of sedimentation rate using the GIS-based modified universal soil loss equation Circle-circle intersection. A universal method for solving typical surveying problems Drainage analysis of the Karanja River basin, Karnataka, India using Geo-informatics Predicting the spatiotemporal changes of an agriculturally vulnerable region of Bangladesh A new fuzzy location-based approach for fire station site selection in Tehran
×
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