基于街景图像和深度学习的城市道路植物景观视觉质量评价

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中图分类号：S759.92 文献标志码：A 文章编号：1673-923X（2025）07-0205-12

Evaluation of urban roadway plant landscape visual quality using street view images and deep learning

CHENYiduo，HUHaihui

（ColegeofHorticlturedLdscapetecture，oreastgulturalUesityabino，Heiog，ia）

Abstract：【Objectie】Inurbanroadnetworksplantlandscapesalongroadsidesareotolyetiallementsofurbanbeauifcationbut alsodirectlyimpactresidentsqualityoflifeandurbaecologicalbalanceUnderstandingthedistrbutionoftevisualqualityofurbnoad plantlandscapesand their influencing factors canprovidetheoreticalsupportfor future urbanroad plant landscape planningand design. 【Method】Taking Harbin asacasestudy，weutilized stret viewimagedata andcombinedthe SegNeXtsemanticsegmentation model withtheSENetdeepleaingmodeltoquantifyindicatorssuchasthegreeviewindex.Acomprehensiveevaluationofplantadscape visual qualitywasconductedusingtheTrueSkillscoringsystemandtherandomforestalgorithm.【Result】1）Scores forplantandscape evaluationiatoossballibcttlotoeer districtscoredlower2）ereasasignificantpositivecoelationetweentheGVandboththeCIandPLDsugestingutal enhancement;howee，angativeoelationasevedbeweenstructuralLRandtheGVI，andbetweenndD.3）In the visual quality evaluation model based onrandom forest，PLMC had over 50% feature importance，indicating that PLMC is theprimary factorinpredictigalalt4vallalalitabn'stdastedteelih concentrationineothwestegion，iletherarasispladaixeddistrbutioofghndlosoes.【Cocsion】oosd visualqualityvaluationmetodprovidesateoreicalbasisfortesieificplainganddesignofurbanplatandscaps，withpotetial for broader application to other cities， promoting sustainable urban landscape development.

Keywords：semantic segmentation;random forest;roadwayplantlandscape;street view images;visualquality

城市道路是城市中供车辆、行人和其他交通方式通行的线性交通通道，是构成城市交通网络的重要组成部分。（剩余16875字）