{"title":"Automatic road identification and labeling in Landsat 4 TM images","authors":"J. Ton, A.K. Jain, W.R. Enslin, W.D. Hudson","doi":"10.1016/0031-8663(89)90002-1","DOIUrl":null,"url":null,"abstract":"<div><p>A conceptually parallel road detection method in Landsat 4 TM images is proposed. The goal is to detect roads at three different levels: major roads, local roads, and minor roads. This road network information is used for the evaluation of detected potential oil/gas pads, since these pads seldom occur on major roads but are often located at the end of minor access roads.</p><p>The proposed method is composed of two phases: low-level road detection and high-level road labeling. Experimental results from several images show that the proposed method can detect roads reasonably well in the low-level phase and is useful in pad evaluation. Future research includes combining multi-band information in road detection and determining thresholds in a more systematic way.</p></div>","PeriodicalId":101020,"journal":{"name":"Photogrammetria","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1989-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0031-8663(89)90002-1","citationCount":"41","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Photogrammetria","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0031866389900021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 41
Abstract
A conceptually parallel road detection method in Landsat 4 TM images is proposed. The goal is to detect roads at three different levels: major roads, local roads, and minor roads. This road network information is used for the evaluation of detected potential oil/gas pads, since these pads seldom occur on major roads but are often located at the end of minor access roads.
The proposed method is composed of two phases: low-level road detection and high-level road labeling. Experimental results from several images show that the proposed method can detect roads reasonably well in the low-level phase and is useful in pad evaluation. Future research includes combining multi-band information in road detection and determining thresholds in a more systematic way.
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