A　method　for　detecting　and　identifying　thin　and　vague　roads　in　aerial　images　is　proposed.　The　method　first　smooths　an　image　by　using　a　Gaussian　filter,　then　uses　a　fractional　differential　operator　to　enhance　the　image　for　sharpening　roads,　then　applies　a　one-pass　ridge　edge　detection　algorithm　to　roughly　detect　the　roads,　and　finally　utilizes　a　number　of　post　functions　to　accurately　identify　roads.　For　each　detected　point　in　an　aerial　road　image,　the　new　ridge　detection　algorithm　detects　if　it　is　a　candidate　for　the　ridge　edge　points　by　searching　through　four　different　directions.　After　that,　the　extracted　segments　of　lines/curves　are　smoothed　and　their　gaps　are　linked　according　to　preset　thresholds　of　lengths　and　directions,　and　the　noisy　lines　are　removed　based　on　the　rules　of　the　curve　length　and　shape　information.　If　roads　are　thick,　the　image　can　be　shrunk　to　a　road　with　a　width　less　than　six　pixels,　then　the　detection　result　for　the　course　resolution　image　is　mapped　into　the　original　image　to　accurately　re-identify　the　road.　In　experiments,　by　comparison　to　traditional　methods,　the　studied　method　can　have　better　detection　results　for　thin　and　vague　roads,　which　are　difficult　to　detect　with　traditional　algorithms.　c　The　Authors.　Published　by　SPIE　under　a　Creative　Commons　Attribution　3.0　Unported　License.　Distribution　or　reproduction　of　this　work　in　whole　or　in　part　requires　full　attribution　of　the　original　publication,　including　its　DOI.