{"title":"从卫星图像监测大马普托地区的道路基础设施：面向对象的分类方法","authors":"Arianna Burzacchi, Matteo Landrò, Simone Vantini","doi":"arxiv-2409.06406","DOIUrl":null,"url":null,"abstract":"The information about pavement surface type is rarely available in road\nnetwork databases of developing countries although it represents a cornerstone\nof the design of efficient mobility systems. This research develops an\nautomatic classification pipeline for road pavement which makes use of\nsatellite images to recognize road segments as paved or unpaved. The proposed\nmethodology is based on an object-oriented approach, so that each road is\nclassified by looking at the distribution of its pixels in the RGB space. The\nproposed approach is proven to be accurate, inexpensive, and readily replicable\nin other cities.","PeriodicalId":501172,"journal":{"name":"arXiv - STAT - Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Monitoring road infrastructures from satellite images in Greater Maputo: an object-oriented classification approach\",\"authors\":\"Arianna Burzacchi, Matteo Landrò, Simone Vantini\",\"doi\":\"arxiv-2409.06406\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The information about pavement surface type is rarely available in road\\nnetwork databases of developing countries although it represents a cornerstone\\nof the design of efficient mobility systems. This research develops an\\nautomatic classification pipeline for road pavement which makes use of\\nsatellite images to recognize road segments as paved or unpaved. The proposed\\nmethodology is based on an object-oriented approach, so that each road is\\nclassified by looking at the distribution of its pixels in the RGB space. The\\nproposed approach is proven to be accurate, inexpensive, and readily replicable\\nin other cities.\",\"PeriodicalId\":501172,\"journal\":{\"name\":\"arXiv - STAT - Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - STAT - Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.06406\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.06406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Monitoring road infrastructures from satellite images in Greater Maputo: an object-oriented classification approach
The information about pavement surface type is rarely available in road
network databases of developing countries although it represents a cornerstone
of the design of efficient mobility systems. This research develops an
automatic classification pipeline for road pavement which makes use of
satellite images to recognize road segments as paved or unpaved. The proposed
methodology is based on an object-oriented approach, so that each road is
classified by looking at the distribution of its pixels in the RGB space. The
proposed approach is proven to be accurate, inexpensive, and readily replicable
in other cities.
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