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<section style="box-sizing: border-box;font-style: normal;font-weight: 400;text-align: justify;font-size: 16px;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;width: 15%;padding: 0px 5px 0px 0px;box-sizing: border-box;"><section style="text-align: center;margin: 10px 0%;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.91" data-w="100" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfIkDgv0xVOVxyGFb0TVl5dkHcu1y9XDic1gKzHWKjUUbkmvibj8kGA1Cw/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section></section><section style="display: inline-block;vertical-align: top;width: 70%;box-sizing: border-box;"><section style="margin: 10px 0% 0px;box-sizing: border-box;" powered-by="gulangu"><section class="horizontal-tb" style="text-align: center;font-size: 12px;color: rgb(153, 166, 171);line-height: 1.4;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><span style="letter-spacing: 0px;line-height: 1.4;box-sizing: border-box;">欢迎点击以上蓝色字体</span><br style="box-sizing: border-box;"  /></p><p style="margin: 0px;padding: 0px;box-sizing: border-box;">关注</p></section></section></section><section style="display: inline-block;vertical-align: top;width: 15%;padding: 0px 0px 0px 5px;box-sizing: border-box;"><section style="text-align: center;margin: 10px 0%;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.91" data-w="100" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfIkDgv0xVOVxyGFb0TVl5dkHcu1y9XDic1gKzHWKjUUbkmvibj8kGA1Cw/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section></section></section><section style="margin: 10px 0px;box-sizing: border-box;" powered-by="gulangu"><section style="width: 50%;border-width: 3px;border-style: solid;border-color: rgb(254, 193, 192);box-sizing: border-box;"></section><section class="horizontal-tb" style="padding: 5px 4px;clear: both;letter-spacing: 1px;box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;clear: none;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">作者苏州规划设计研究院交通所所长、同济大学建筑与城市规划学院博士研究生樊钧，同济大学建筑与城市规划学院硕士研究生唐皓明，同济大学建筑与城市规划学院助理教授、硕士生导师叶宇在《规划师》2019年第14期撰文，<span style="text-indent: 0px;box-sizing: border-box;">在新型城镇化背景下，日益提升的空间品质需求需要更人性化、宜步行的街道。在当前城市设计的实施及评估中，急</span><span style="text-indent: 2em;box-sizing: border-box;">需一套综合、快速的评价方法来评估街道的慢行品质，以协助更精准的设计导控。研究以苏州古城区为例，探索多源大数据支撑下的大规模且精细化的分析方法。通过空间网络分析和聚类算法实现形态组构评价，通过兴趣点数据(POI)实现功能多样性</span><span style="text-indent: 2em;box-sizing: border-box;">评价，通过街景数据和深度学习实现视觉感知评价，通过位置服务数据(LBS)实现场所行为活动评价，进而基于层次分析法(AHP)整合前三方面的内容，并结合活力高低实现多维度下的慢行品质评价和特征街道画像。基于各维度情况，研究对不同类型的潜力街道给出针对性导控策略。该分析方法实现了慢行品质这一难以评价要素的精细化度量，在实践上具有普适性和易用性。</span></p></section><section style="width: 50%;border-width: 3px;border-style: solid;border-color: rgb(42, 118, 162);float: right;margin-top: -6px;box-sizing: border-box;"></section><section style="clear: both;box-sizing: border-box;"></section></section><section style="margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;border-color: rgb(21, 103, 167);border-style: solid;border-width: 1px;padding: 0px 4px;box-sizing: border-box;"><section style="margin: 0.5em 0px;text-align: left;transform: translate3d(0px, 0px, 0px);-webkit-transform: translate3d(0px, 0px, 0px);-moz-transform: translate3d(0px, 0px, 0px);-o-transform: translate3d(0px, 0px, 0px);box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);font-size: 12px;padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">[ 关键词 ] 慢行品质；街景数据；多源城市数据；街道画像</p></section><section style="border-top: 2px dotted rgb(95, 94, 102);width: 100%;box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="font-size: 12px;color: rgb(56, 30, 5);letter-spacing: 1px;padding: 0px 4px;box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">[ 文章编号 ]1006-0022(2019)14-0005-07　</p><p style="white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">[ 中图分类号 ]TU984　</p><p style="white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">[ 文献标识码 ]B </p><p style="white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">[ 引文格式 ]樊钧，唐皓明，叶宇．街道慢行品质的多维度评价与导控策略—基于多源城市数据的整合分析[J]．规划师，2019(14)：5-11．</p></section></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.3692308" data-w="65" src="http://mmbiz.qpic.cn/mmbiz_gif/2BPlVTS3ahcJcSQTvU7yNR75YDHb1Rj9IYwb0KMjIpYzkc7shdchOXTP0b7DNoUfO8wzbShiaxNUS4pgbtfRrQg/640?wx_fmt=gif" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="gif"  /></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section class="horizontal-tb" style="display: inline-block;border-radius: 1em;background-color: rgb(21, 103, 167);padding: 0.3em 0.8em;color: rgb(255, 255, 255);font-size: 18px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">一</strong></p><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">研究背景</strong></p></section></section><section style="margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;border-width: 1px;border-style: solid;border-color: rgb(21, 103, 167);padding: 10px;box-shadow: rgb(0, 0, 0) 0px 0px 0px;box-sizing: border-box;"><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（一）人本尺度下的街道慢行品质</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">在以人为本的新型城镇化背景下，我国公共空间建<span style="text-indent: 2em;box-sizing: border-box;">设呈现出由“速度优先”向“品质追求”转变的新态势，</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">并随之掀起了街道重塑的浪潮。这一情况与西方城市公</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">共空间设计与营造的发展历程相吻合，是城市建设方式</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">向集约精细、人性化发展的必然需求。与此同时，城</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">市居民对于街道空间品质的关注从“形态导向”转向“生</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">活导向”，街道空间规划和导控也从以往满足功能性的</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">交通需求、注重美学性的城市美化，向提升生活性的空</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">间使用、日常性的空间感受转变，进而催生了对人本尺</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">度下街道慢行品质的关注与提升需求。</span></p><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">在本次研究中，人本尺度(Human-scale)指人可以<span style="letter-spacing: 0px;box-sizing: border-box;">看得见、摸得着、感受得到的与人体密切相关的空间尺</span><span style="letter-spacing: 0px;box-sizing: border-box;">度，是对目前网格、街区和地块等尺度的深化与必要补</span><span style="letter-spacing: 0px;box-sizing: border-box;">充。而人本尺度下的街道慢行品质不局限于视觉感知</span><span style="letter-spacing: 0px;box-sizing: border-box;">上的空间品质，而是从人的生活需求和日常使用角度出</span><span style="letter-spacing: 0px;box-sizing: border-box;">发，囊括空间形态、场所活动、功能混合和视觉感知等</span><span style="letter-spacing: 0px;box-sizing: border-box;">多个维度。</span></p></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（二）已有进展与局限</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">从20世纪60年代开始，简·雅各布斯对人本尺度<span style="letter-spacing: 0px;box-sizing: border-box;">的城市形态进行了思考，此后凯文·林奇、威廉·怀</span><span style="letter-spacing: 0px;box-sizing: border-box;">特、克莱尔·马库斯及扬·盖尔 等学者和设计师</span><span style="letter-spacing: 0px;box-sizing: border-box;">在定性研究与设计实践上开展了对人本尺度城市空间的</span><span style="letter-spacing: 0px;box-sizing: border-box;">探索。这些探索是对功能主导的现代主</span><span style="letter-spacing: 0px;box-sizing: border-box;">义城市规划与设计的反思，对现有研究</span><span style="letter-spacing: 0px;box-sizing: border-box;">有指导意义，但由于缺乏对量化数据与</span><span style="letter-spacing: 0px;box-sizing: border-box;">模型的深入研究，不利于大规模、精细</span><span style="letter-spacing: 0px;box-sizing: border-box;">化设计实践与导控。Fruin、Naik等人</span><span style="letter-spacing: 0px;box-sizing: border-box;">后续通过量化研究，专门针对街道慢行</span><span style="letter-spacing: 0px;box-sizing: border-box;">品质的某一方面加以深入研究，但缺乏</span><span style="letter-spacing: 0px;box-sizing: border-box;">综合性的评估考量。</span></p><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;"><span style="letter-spacing: 0px;box-sizing: border-box;">面对“城市双修”、“微更新”和</span><span style="letter-spacing: 0px;box-sizing: border-box;">“美丽街区”等人本尺度下的城市规划</span><span style="text-indent: 2em;box-sizing: border-box;">与设计实践需求，街道空间慢行品质研</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">究需要注意两个问题：①需要连续、大</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">规模及高精度的街道空间与画像，而非</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">少量的几个街道剖断面；②在形态、功</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">能、感知和行为等多维度下进行整合分</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">析，实现对慢行品质要素的多方面考虑。</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">只有解决以上两个问题，才能够真正助</span><span style="text-indent: 2em;letter-spacing: 0px;box-sizing: border-box;">力于街道慢行品质导控实践研究。</span></p></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（三）新数据带来的新可能</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">随着新城市科学的发展，新数据、<span style="letter-spacing: 0px;box-sizing: border-box;">新技术的出现有利于解决以往以主观经</span><span style="letter-spacing: 0px;box-sizing: border-box;">验为主的街道品质评价客观性不足的问</span><span style="letter-spacing: 0px;box-sizing: border-box;">题，保证后续设计尺度的精确性，如</span><span style="letter-spacing: 0px;box-sizing: border-box;">利用街道基础数据和sDNA软件进行道</span><span style="letter-spacing: 0px;box-sizing: border-box;">路空间形态适应性的分析等。在涌现出</span><span style="letter-spacing: 0px;box-sizing: border-box;">的一系列新数据和新技术中，街景数据</span><span style="letter-spacing: 0px;box-sizing: border-box;">由于数据开放且贴近行人视角，已实现</span><span style="letter-spacing: 0px;box-sizing: border-box;">了绿化可见度等大规模且精细度高的</span><span style="letter-spacing: 0px;box-sizing: border-box;">感知维度评价。</span></p><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">借助新数据和新技术，本次研究从<span style="letter-spacing: 0px;box-sizing: border-box;">形态、功能、感知和行为等多维度去理</span><span style="letter-spacing: 0px;box-sizing: border-box;">解街道空间的复杂性，选取路网数据和</span><span style="letter-spacing: 0px;box-sizing: border-box;">空间网络分析技术对街道组织结构进行</span><span style="letter-spacing: 0px;box-sizing: border-box;">分析，选取POI数据对道路的主导功能</span><span style="letter-spacing: 0px;box-sizing: border-box;">和功能多样性进行分析，选取街景数据</span><span style="letter-spacing: 0px;box-sizing: border-box;">和深度学习技术进行街道品质的感知评</span><span style="letter-spacing: 0px;box-sizing: border-box;">价，选取LBS定位数据确定人群的行为</span><span style="letter-spacing: 0px;box-sizing: border-box;">活动，以更好地进行街道慢行品质的量</span><span style="letter-spacing: 0px;box-sizing: border-box;">化评价和完成街道画像。这些选取的新</span><span style="letter-spacing: 0px;box-sizing: border-box;">数据和新技术具有开放性、普遍性的特</span><span style="letter-spacing: 0px;box-sizing: border-box;">征，有助于弥补现有量化分析的不足。</span></p></section></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.3692308" data-w="65" src="http://mmbiz.qpic.cn/mmbiz_gif/2BPlVTS3ahcJcSQTvU7yNR75YDHb1Rj9IYwb0KMjIpYzkc7shdchOXTP0b7DNoUfO8wzbShiaxNUS4pgbtfRrQg/640?wx_fmt=gif" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="gif"  /></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section class="horizontal-tb" style="display: inline-block;border-radius: 1em;background-color: rgb(21, 103, 167);padding: 0.3em 0.8em;color: rgb(255, 255, 255);font-size: 18px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">二</strong></p><p style="margin: 0px;padding: 0px;box-sizing: border-box;"> 街道慢行品质相关研究回顾</p></section></section><section style="margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;border-width: 1px;border-style: solid;border-color: rgb(21, 103, 167);padding: 10px;box-shadow: rgb(0, 0, 0) 0px 0px 0px;box-sizing: border-box;"><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">关于街道慢行品质的研究，经历了<span style="letter-spacing: 0px;box-sizing: border-box;">从定性讨论到定量评价的过程，从早期</span><span style="letter-spacing: 0px;box-sizing: border-box;">简·雅各布斯 通过观察调研提出街区</span><span style="letter-spacing: 0px;box-sizing: border-box;">尺度和街道多样的重要性，到阿兰·雅各</span><span style="letter-spacing: 0px;box-sizing: border-box;">布斯 对“伟大的街道”的分类和特征</span><span style="letter-spacing: 0px;box-sizing: border-box;">描述，再到近些年基于现场社会调研、</span><span style="letter-spacing: 0px;box-sizing: border-box;">街景数据等逐渐深化的要素定量评价</span><span style="letter-spacing: 0px;box-sizing: border-box;">分析。目前，典型的定量研究主要从街</span><span style="letter-spacing: 0px;box-sizing: border-box;">道环境要素和使用者的适应性两方面展</span><span style="letter-spacing: 0px;box-sizing: border-box;">开评价(表1)。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="1" data-w="581" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfjhBibic5HUXjzXxyIhKXEfsVicDStVUEhjicLGMylNtN5zr1PmMUIuzaMg/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">现有研究大多专注于街道空间品质<span style="letter-spacing: 0px;box-sizing: border-box;">的单一维度叠合，少数研究者如唐婧娴</span><span style="letter-spacing: 0px;box-sizing: border-box;">等人综合了两个维度进行街道品质测度。</span><span style="letter-spacing: 0px;box-sizing: border-box;">但街道空间具有复杂性，需要更全面综</span><span style="letter-spacing: 0px;box-sizing: border-box;">合的评价模型，过去的研究限于数据和</span><span style="letter-spacing: 0px;box-sizing: border-box;">技术难以实现。而当下的新技术环境特</span><span style="letter-spacing: 0px;box-sizing: border-box;">别是机器学习技术的成熟，有可能实现</span><span style="letter-spacing: 0px;box-sizing: border-box;">大规模、高精细及多维度的街道慢行品</span><span style="letter-spacing: 0px;box-sizing: border-box;">质分析。</span></p></section></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.3692308" data-w="65" src="http://mmbiz.qpic.cn/mmbiz_gif/2BPlVTS3ahcJcSQTvU7yNR75YDHb1Rj9IYwb0KMjIpYzkc7shdchOXTP0b7DNoUfO8wzbShiaxNUS4pgbtfRrQg/640?wx_fmt=gif" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="gif"  /></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section class="horizontal-tb" style="display: inline-block;border-radius: 1em;background-color: rgb(21, 103, 167);padding: 0.3em 0.8em;color: rgb(255, 255, 255);font-size: 18px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">三</strong></p><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">街道慢行品质多维度评价方法</strong></p></section></section><section style="margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;border-width: 1px;border-style: solid;border-color: rgb(21, 103, 167);padding: 10px;box-shadow: rgb(0, 0, 0) 0px 0px 0px;box-sizing: border-box;"><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（一）评价对象</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">随着城市的发展，苏州古城面临着<span style="letter-spacing: 0px;box-sizing: border-box;">空间品质提升的挑战，其规划急需从以</span><span style="letter-spacing: 0px;box-sizing: border-box;">车为本的规划转型为以人为本的规划，</span><span style="letter-spacing: 0px;box-sizing: border-box;">尤其要注重慢行系统的改善提升。研究</span><span style="letter-spacing: 0px;box-sizing: border-box;">以苏州古城外城河内街道为研究对象</span><span style="letter-spacing: 0px;box-sizing: border-box;">(街道段数量为2872段，覆盖面积为</span><span style="letter-spacing: 0px;box-sizing: border-box;">14.2km2)，以人群活动数据、兴趣点位</span><span style="letter-spacing: 0px;box-sizing: border-box;">置数据和街景图片数据等为主要数据来</span><span style="letter-spacing: 0px;box-sizing: border-box;">源，运用空间网络分析、机器学习等技术，</span><span style="letter-spacing: 0px;box-sizing: border-box;">实现大规模、高精度的古城街道慢行品</span><span style="letter-spacing: 0px;box-sizing: border-box;">质评价，为旧城更新提供技术支撑。</span></p></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（二）评价方法步骤</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">研究步骤包含数据收集、多维度评<span style="letter-spacing: 0px;box-sizing: border-box;">价、慢行品质与街道画像、针对性导控</span><span style="letter-spacing: 0px;box-sizing: border-box;">策略四个阶段( 图1)。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.5064815" data-w="1080" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfGgxzadr0GIo4EuCCTBTmbXiaYLGMfFe6qPHZd4YITurGoBW9wGkZmEQ/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section style="margin-top: 10px;margin-bottom: 10px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section style="width: 40px;height: 5px;line-height: 5px;box-sizing: border-box;"><section style="width: 5px;height: 5px;border-radius: 50%;border-width: 1px;border-style: solid;border-color: rgb(58, 140, 226);display: inline-block;vertical-align: middle;box-sizing: border-box;"></section><section style="display: inline-block;vertical-align: middle;width: 30px;border-top: 1px dashed rgb(58, 140, 226);border-right-color: rgb(58, 140, 226);border-bottom-color: rgb(58, 140, 226);border-left-color: rgb(58, 140, 226);box-sizing: border-box;"></section></section><section class="horizontal-tb" style="padding-left: 8px;padding-right: 8px;color: rgb(58, 140, 226);box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">1.<span style="letter-spacing: 0px;box-sizing: border-box;"></span>数据收集</p></section><section style="width: 40px;text-align: right;margin-left: auto;height: 5px;line-height: 5px;box-sizing: border-box;"><section style="display: inline-block;vertical-align: middle;width: 30px;border-top: 1px dashed rgb(58, 140, 226);border-right-color: rgb(58, 140, 226);border-bottom-color: rgb(58, 140, 226);border-left-color: rgb(58, 140, 226);box-sizing: border-box;"></section><section style="width: 5px;height: 5px;border-radius: 50%;border-width: 1px;border-style: solid;border-color: rgb(58, 140, 226);display: inline-block;vertical-align: middle;box-sizing: border-box;"></section></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">在数据收集阶段，研究小组于2018<span style="letter-spacing: 0px;box-sizing: border-box;">年秋季对研究区域的2872段街道的街景</span><span style="letter-spacing: 0px;box-sizing: border-box;">图片开展了收集。街道总长为354.9km，</span><span style="letter-spacing: 0px;box-sizing: border-box;">研究抓取了47422 个采样点上94844 张</span><span style="letter-spacing: 0px;box-sizing: border-box;">百度街景图片数据(图像分辨率为480</span><span style="letter-spacing: 0px;box-sizing: border-box;">×360 像素)，平均采样间距约为20ｍ。</span><span style="box-sizing: border-box;">此外，研究还收集了工作日和周末共10</span><span style="letter-spacing: 0px;box-sizing: border-box;">个时间段的LBS 数据，抓取了POI数据</span><span style="letter-spacing: 0px;box-sizing: border-box;">点38049个。</span></p><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">研究收集的路网基础数据来源于开<span style="letter-spacing: 0px;box-sizing: border-box;">源的OSM地图(http://extract.bbbike.</span><span style="letter-spacing: 0px;box-sizing: border-box;">org/)，POI兴趣点抓取于高德地图。街</span><span style="letter-spacing: 0px;box-sizing: border-box;">景数据首先基于路网拓扑计算，保证街</span><span style="letter-spacing: 0px;box-sizing: border-box;">景图像能平行于街道的长轴方向，随后</span><span style="letter-spacing: 0px;box-sizing: border-box;">再由Python( 是一种计算机程序设计语</span><span style="letter-spacing: 0px;box-sizing: border-box;">言)经HTTP URL调用百度街景API(http:</span><span style="letter-spacing: 0px;box-sizing: border-box;">//api.map.baidu.com/lbsapi/) 获得，通</span><span style="letter-spacing: 0px;box-sizing: border-box;">过输入视线垂直和水平方向的角度，以</span><span style="letter-spacing: 0px;box-sizing: border-box;">及视点位置数据，可以抓取每一个样本</span><span style="letter-spacing: 0px;box-sizing: border-box;">点的街景视图。其中，垂直角度为零，</span><span style="letter-spacing: 0px;box-sizing: border-box;">即平视的街景视角；水平角度根据路网</span><span style="letter-spacing: 0px;box-sizing: border-box;">形态，抓取平行于道路的前后两张街</span><span style="letter-spacing: 0px;box-sizing: border-box;">景视图。此外，LBS数据由Python经</span><span style="letter-spacing: 0px;box-sizing: border-box;">HTTPS调用腾讯宜出行平台位置服务</span><span style="letter-spacing: 0px;box-sizing: border-box;">API(https://apis.map.qq.com/) 获得。</span></p></section><section style="margin-top: 10px;margin-bottom: 10px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section style="width: 40px;height: 5px;line-height: 5px;box-sizing: border-box;"><section style="width: 5px;height: 5px;border-radius: 50%;border-width: 1px;border-style: solid;border-color: rgb(58, 140, 226);display: inline-block;vertical-align: middle;box-sizing: border-box;"></section><section style="display: inline-block;vertical-align: middle;width: 30px;border-top: 1px dashed rgb(58, 140, 226);border-right-color: rgb(58, 140, 226);border-bottom-color: rgb(58, 140, 226);border-left-color: rgb(58, 140, 226);box-sizing: border-box;"></section></section><section class="horizontal-tb" style="padding-left: 8px;padding-right: 8px;color: rgb(58, 140, 226);box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">2.<span style="letter-spacing: 0px;box-sizing: border-box;"></span>多维度评价</p></section><section style="width: 40px;text-align: right;margin-left: auto;height: 5px;line-height: 5px;box-sizing: border-box;"><section style="display: inline-block;vertical-align: middle;width: 30px;border-top: 1px dashed rgb(58, 140, 226);border-right-color: rgb(58, 140, 226);border-bottom-color: rgb(58, 140, 226);border-left-color: rgb(58, 140, 226);box-sizing: border-box;"></section><section style="width: 5px;height: 5px;border-radius: 50%;border-width: 1px;border-style: solid;border-color: rgb(58, 140, 226);display: inline-block;vertical-align: middle;box-sizing: border-box;"></section></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">多维度评价综合了街道慢行品质的<span style="letter-spacing: 0px;box-sizing: border-box;">环境要素和使用者的适应性两方面，从</span><span style="letter-spacing: 0px;box-sizing: border-box;">形态、功能、感知和行为四个维度进行</span><span style="letter-spacing: 0px;box-sizing: border-box;">评价。</span></p><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">(1) 在形态维度上，研究基于sDNA<span style="letter-spacing: 0px;box-sizing: border-box;">对道路的空间组织结构进行了步行适宜性</span><span style="letter-spacing: 0px;box-sizing: border-box;">的评价与聚类。sDNA是由卡迪夫大学提</span><span style="letter-spacing: 0px;box-sizing: border-box;">出的量化分析工具，可以基于拓扑、角度</span><span style="letter-spacing: 0px;box-sizing: border-box;">或米制距离的变化进行分析。由于基于角</span><span style="letter-spacing: 0px;box-sizing: border-box;">度距离的可达性被证实与实际观察到</span><span style="letter-spacing: 0px;box-sizing: border-box;">的人车行为分布具有良好的相关性，本次</span><span style="letter-spacing: 0px;box-sizing: border-box;">研究采用基于角度距离的中间性(Angular </span><span style="letter-spacing: 0px;box-sizing: border-box;">Betweenness)作为道路网络可达性的度</span><span style="letter-spacing: 0px;box-sizing: border-box;">量值。不同的分析半径反映出街道组织结</span><span style="letter-spacing: 0px;box-sizing: border-box;">构对相应距离出行的适应性，500m常被</span><span style="letter-spacing: 0px;box-sizing: border-box;">认为是步行舒适距离，大尺度的半径则更</span><span style="letter-spacing: 0px;box-sizing: border-box;">适宜车行等通勤交通。研究选择500～</span><span style="letter-spacing: 0px;box-sizing: border-box;">10000m的半径对苏州全市街道进行连续</span><span style="letter-spacing: 0px;box-sizing: border-box;">分析，在聚类算法的协助下以更大范围的</span><span style="letter-spacing: 0px;box-sizing: border-box;">分析视角考虑从步行距离到车行距离的街</span><span style="letter-spacing: 0px;box-sizing: border-box;">道空间组织构成特征。</span></p><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">(2) 在功能维度上，研究基于POI分<span style="letter-spacing: 0px;box-sizing: border-box;">析了街道设施的多样性，并运用ArcGIS，</span><span style="letter-spacing: 0px;box-sizing: border-box;">基于香农指数对街道设施的多样性开展量</span><span style="letter-spacing: 0px;box-sizing: border-box;">化评价，计算公式如下：</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.3879781" data-w="549" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2Of6ib0WBWibJ8iaC6Z6icQPyBpHpOWunqAXqiaunwV1IE3vXHMPjXChPEXmicA/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">(3) 在感知维度上，研究首先基于街<span style="letter-spacing: 0px;box-sizing: border-box;">景数据和机器学习进行了街道空间感知</span><span style="letter-spacing: 0px;box-sizing: border-box;">评价，并运用卷积神经网络工具(SegNet)</span><span style="letter-spacing: 0px;box-sizing: border-box;">对要素类别进行了图像切割。这种方法</span><span style="letter-spacing: 0px;box-sizing: border-box;">可以测度天空、建筑、绿化和道路等不</span><span style="letter-spacing: 0px;box-sizing: border-box;">同街景要素的占比。考虑到现有研究在</span><span style="letter-spacing: 0px;box-sizing: border-box;">国内城市中直接运用这一工具的识别</span><span style="letter-spacing: 0px;box-sizing: border-box;">效果良好，故未基于国内图片数据开展</span><span style="letter-spacing: 0px;box-sizing: border-box;">进一步的图像标定。其次，再运用机器</span><span style="letter-spacing: 0px;box-sizing: border-box;">学习领域的人工神经网络算法(Artificial</span><span style="letter-spacing: 0px;box-sizing: border-box;">Neural Network，简称“ANN”) 构建评</span><span style="letter-spacing: 0px;box-sizing: border-box;">价模型。ANN是一种模仿生物神经网络</span><span style="letter-spacing: 0px;box-sizing: border-box;">功能的数学算法，一个典型的ANN包括</span><span style="letter-spacing: 0px;box-sizing: border-box;">多个神经元(人工节点) 多层互联所形成</span><span style="letter-spacing: 0px;box-sizing: border-box;">的一个类似生物神经网络的网状结构。</span><span style="letter-spacing: 0px;box-sizing: border-box;">这一非线性的架构使其可以集体地、并</span><span style="letter-spacing: 0px;box-sizing: border-box;">行地计算函数的各个部分，对于复杂、</span><span style="letter-spacing: 0px;box-sizing: border-box;">多样而又相互交联的建成环境要素分析</span><span style="letter-spacing: 0px;box-sizing: border-box;">较为适宜，因此其能够基于相对小样本</span><span style="letter-spacing: 0px;box-sizing: border-box;">的街景评价来训练评价模型，进而对所</span><span style="letter-spacing: 0px;box-sizing: border-box;">有街景照片进行大规模评价打分。最后，</span><span style="letter-spacing: 0px;box-sizing: border-box;">计算每一条街道段的空间感知评价分数，</span><span style="letter-spacing: 0px;box-sizing: border-box;">得分越高，人本尺度的感知越好。</span></p><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">(4) 在行为维度上，研究基于LBS数<span style="letter-spacing: 0px;box-sizing: border-box;">据对人群在街道的行为活力进行分析。</span><span style="letter-spacing: 0px;box-sizing: border-box;">研究分别选取了工作日与周末7点、11</span><span style="letter-spacing: 0px;box-sizing: border-box;">点、15点、19点和22点共10个时间</span><span style="letter-spacing: 0px;box-sizing: border-box;">段收集人群位置信息，保证了数据的代</span><span style="letter-spacing: 0px;box-sizing: border-box;">表性。随后，利用ArcGIS对人群位置进</span><span style="letter-spacing: 0px;box-sizing: border-box;">行核密度分析，观察人群聚集程度高的</span><span style="letter-spacing: 0px;box-sizing: border-box;">地区，再与路网做空间连接分析(Spatial </span><span style="letter-spacing: 0px;box-sizing: border-box;">Join Analysis)，便于下一步构建评价模型。</span></p></section><section style="margin-top: 10px;margin-bottom: 10px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section style="width: 40px;height: 5px;line-height: 5px;box-sizing: border-box;"><section style="width: 5px;height: 5px;border-radius: 50%;border-width: 1px;border-style: solid;border-color: rgb(58, 140, 226);display: inline-block;vertical-align: middle;box-sizing: border-box;"></section><section style="display: inline-block;vertical-align: middle;width: 30px;border-top: 1px dashed rgb(58, 140, 226);border-right-color: rgb(58, 140, 226);border-bottom-color: rgb(58, 140, 226);border-left-color: rgb(58, 140, 226);box-sizing: border-box;"></section></section><section class="horizontal-tb" style="padding-left: 8px;padding-right: 8px;color: rgb(58, 140, 226);box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">3.<span style="letter-spacing: 0px;box-sizing: border-box;"></span>慢行品质与街道画像</p></section><section style="width: 40px;text-align: right;margin-left: auto;height: 5px;line-height: 5px;box-sizing: border-box;"><section style="display: inline-block;vertical-align: middle;width: 30px;border-top: 1px dashed rgb(58, 140, 226);border-right-color: rgb(58, 140, 226);border-bottom-color: rgb(58, 140, 226);border-left-color: rgb(58, 140, 226);box-sizing: border-box;"></section><section style="width: 5px;height: 5px;border-radius: 50%;border-width: 1px;border-style: solid;border-color: rgb(58, 140, 226);display: inline-block;vertical-align: middle;box-sizing: border-box;"></section></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;"><span style="letter-spacing: 0px;box-sizing: border-box;">为了从形态、功能和感知三个维度</span><span style="letter-spacing: 0px;box-sizing: border-box;">对街道慢行品质进行综合评价，研究运</span><span style="letter-spacing: 0px;box-sizing: border-box;">用AHP 层次分析法，寻求了二十余位有</span><span style="letter-spacing: 0px;box-sizing: border-box;">规划、建筑背景的专家以及硕士、博士</span><span style="letter-spacing: 0px;box-sizing: border-box;">研究生，对三个维度进行打分，具体的</span><span style="letter-spacing: 0px;box-sizing: border-box;">判断矩阵如下：</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.470483" data-w="559" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2Of10sciaHUkugHOselLdQAQ0jThcRRVMS0SY56pH4mxGtTAaduC2KBibpA/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">在确定维度权重后(表2)，经计算<span style="letter-spacing: 0px;box-sizing: border-box;">获得苏州古城街道慢行品质得分结果，</span><span style="letter-spacing: 0px;box-sizing: border-box;">同时获得古城的街道画像。研究将得分</span><span style="letter-spacing: 0px;box-sizing: border-box;">前1/2 的街道视为慢行适宜型街道，将</span><span style="letter-spacing: 0px;box-sizing: border-box;">得分后1/2 的街道视为慢行品质待优化</span><span style="letter-spacing: 0px;box-sizing: border-box;">的街道。随后，再根据街道行为活力的</span><span style="letter-spacing: 0px;box-sizing: border-box;">高低，与形态、功能、感知评价得分后</span><span style="letter-spacing: 0px;box-sizing: border-box;">1/2 的结果进行叠加分析，得到六类街道：</span><span style="letter-spacing: 0px;box-sizing: border-box;">高活力—低适应型街道、高活力—缺设施</span><span style="letter-spacing: 0px;box-sizing: border-box;">型街道、高活力—低品质型街道、低活力—</span><span style="letter-spacing: 0px;box-sizing: border-box;">低适应型街道、低活力—缺设施型街道、</span><span style="letter-spacing: 0px;box-sizing: border-box;">低活力—低品质型街道。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.262963" data-w="1080" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfGBWVG1JUTPOztAiciabf3ricOGpW9bBAOrNmWjxibZMcySjH9punemR9HQ/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section style="margin-top: 10px;margin-bottom: 10px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section style="width: 40px;height: 5px;line-height: 5px;box-sizing: border-box;"><section style="width: 5px;height: 5px;border-radius: 50%;border-width: 1px;border-style: solid;border-color: rgb(58, 140, 226);display: inline-block;vertical-align: middle;box-sizing: border-box;"></section><section style="display: inline-block;vertical-align: middle;width: 30px;border-top: 1px dashed rgb(58, 140, 226);border-right-color: rgb(58, 140, 226);border-bottom-color: rgb(58, 140, 226);border-left-color: rgb(58, 140, 226);box-sizing: border-box;"></section></section><section class="horizontal-tb" style="padding-left: 8px;padding-right: 8px;color: rgb(58, 140, 226);box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">4.<span style="letter-spacing: 0px;box-sizing: border-box;"></span>针对性导控策略</p></section><section style="width: 40px;text-align: right;margin-left: auto;height: 5px;line-height: 5px;box-sizing: border-box;"><section style="display: inline-block;vertical-align: middle;width: 30px;border-top: 1px dashed rgb(58, 140, 226);border-right-color: rgb(58, 140, 226);border-bottom-color: rgb(58, 140, 226);border-left-color: rgb(58, 140, 226);box-sizing: border-box;"></section><section style="width: 5px;height: 5px;border-radius: 50%;border-width: 1px;border-style: solid;border-color: rgb(58, 140, 226);display: inline-block;vertical-align: middle;box-sizing: border-box;"></section></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">研究最后选取养蚕里弄、幽兰路和<span style="letter-spacing: 0px;box-sizing: border-box;">西大街某巷段等六条对应不同类型的重</span><span style="letter-spacing: 0px;box-sizing: border-box;">点街道进行个案分析，提出相应的导控</span><span style="letter-spacing: 0px;box-sizing: border-box;">策略。</span></p></section></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.3692308" data-w="65" src="http://mmbiz.qpic.cn/mmbiz_gif/2BPlVTS3ahcJcSQTvU7yNR75YDHb1Rj9IYwb0KMjIpYzkc7shdchOXTP0b7DNoUfO8wzbShiaxNUS4pgbtfRrQg/640?wx_fmt=gif" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="gif"  /></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section class="horizontal-tb" style="display: inline-block;border-radius: 1em;background-color: rgb(21, 103, 167);padding: 0.3em 0.8em;color: rgb(255, 255, 255);font-size: 18px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">四</strong></p><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">苏州古城街道慢行品质评价实践</strong></p></section></section><section style="display: block;box-sizing: border-box;" powered-by="gulangu"><section style="margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;"><section style="display: inline-block;width: 100%;border-width: 1px;border-style: solid;border-color: rgb(21, 103, 167);padding: 10px;box-shadow: rgb(0, 0, 0) 0px 0px 0px;box-sizing: border-box;"><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（一）基于sDNA 与聚类分析的街道形态组构特质评价</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">研究对苏州全市街道进行半径500m、<span style="letter-spacing: 0px;box-sizing: border-box;">1000m、1500m……9000m、9500m、</span><span style="letter-spacing: 0px;box-sizing: border-box;">10000m等中间性分析后，截取古城街道</span><span style="letter-spacing: 0px;box-sizing: border-box;">结果(图2)。由此可以观察到当R=500m</span><span style="letter-spacing: 0px;box-sizing: border-box;">时观前街地区、古城西北角、西南角和</span><span style="letter-spacing: 0px;box-sizing: border-box;">桂花公园附近邻里道路较密集，街道空</span><span style="letter-spacing: 0px;box-sizing: border-box;">间较适宜步行或骑行等慢行交通。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.4759259" data-w="1080" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfNFfyua3SNg2RwdvxiaAsR3NLicTe1eRkD9gojhrq9Q2WHle0FyBknqBw/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;"><span style="letter-spacing: 0px;box-sizing: border-box;">因本次研究侧重街道慢行品质的分</span><span style="letter-spacing: 0px;box-sizing: border-box;">析，故后续街道画像评价只使用了sDNA</span><span style="letter-spacing: 0px;box-sizing: border-box;">R=500m的结果，但最后街道的导控策</span><span style="letter-spacing: 0px;box-sizing: border-box;">略考虑了基于聚类分析所抽取的街道空</span><span style="letter-spacing: 0px;box-sizing: border-box;">间组构特征。具体来说，研究运用SPSS</span><span style="letter-spacing: 0px;box-sizing: border-box;">对中间性分析结果进行归一化处理后，</span><span style="letter-spacing: 0px;box-sizing: border-box;">采用聚类分析(图3)发掘了古城内街道</span><span style="letter-spacing: 0px;box-sizing: border-box;">的典型类型。古城内以邻里道路为主，</span><span style="letter-spacing: 0px;box-sizing: border-box;">主要是保存完好的各类小街巷和部分城</span><span style="letter-spacing: 0px;box-sizing: border-box;">市支路；片区级偏向步行的次要道路为</span><span style="letter-spacing: 0px;box-sizing: border-box;">仓街、邾长巷和养育巷等道路，适宜慢</span><span style="letter-spacing: 0px;box-sizing: border-box;">行交通；片区级偏向车行的次要道路主</span><span style="letter-spacing: 0px;box-sizing: border-box;">要为人民路北段、白塔西路等；片区级</span><span style="letter-spacing: 0px;box-sizing: border-box;">主要道路为人民路南段、齐门路两条城</span><span style="letter-spacing: 0px;box-sizing: border-box;">内主要交通性道路，而干将西路和干将</span><span style="letter-spacing: 0px;box-sizing: border-box;">东路为城市级主要道路，承担连接古城</span><span style="letter-spacing: 0px;box-sizing: border-box;">与新区的交通职能。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.4796296" data-w="1080" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfjqPqKYmn1iay8SFgPN5aibqpNH5xicNqib51TpYN33BXia79ribvoTuaMNiaw/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（二）基于POI 的街道功能多样性分析</p></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;"><span style="box-sizing: border-box;">研究将抓取到的38049个POI数</span><span style="box-sizing: border-box;">据，根据性质分为医疗、科教、体育休</span><span style="box-sizing: border-box;">闲、生活服务、购物、餐饮、交通和景</span><span style="box-sizing: border-box;">点八大类设施，随后以道路中心线为基</span><span style="box-sizing: border-box;">准，分析不同街道段50m半径内的缓冲</span><span style="box-sizing: border-box;">区中单位长度POI的种类和数量。若单</span><span style="box-sizing: border-box;">类POI的密度超过分析区域75％的，视</span><span style="box-sizing: border-box;">为街道的主导功能(图4)。数值越高，</span><span style="box-sizing: border-box;">表示该街道的主导功能越多，其中也有</span><span style="box-sizing: border-box;">无主导功能的街道。主导功能的中位数</span><span style="box-sizing: border-box;">为1，下四分位为3，通过研究可以观察</span><span style="box-sizing: border-box;">到部分街道存在多种主导功能，其设施</span><span style="box-sizing: border-box;">的服务能力较强。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.7758621" data-w="696" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfdkiaIHKlDkkxe2Q62NqyojKuC04Vhk7SXHwpGyRO1on1DTDLBPHBqpg/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">为了更准确地分析街道功能的多样<span style="box-sizing: border-box;">性，研究运用ArcGIS，基于香农指数开</span><span style="box-sizing: border-box;">展量化评价(图5)，由此可以得出人民路、</span><span style="box-sizing: border-box;">凤凰街和新市路两侧的POI 功能多样性</span><span style="box-sizing: border-box;">较强，苏州大学内部、古城东北角住区、</span><span style="box-sizing: border-box;">东南角住区、第四中学和苏州中学附近区域的POI功能多样性差。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="1.1713666" data-w="461" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfGbHvGDZ8fHaN3keA5LjBMQ0rmQcQtvKuucvibLcrqergucRzgibUK0Kw/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（三）基于街景数据的街道空间品质感知评价</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">在获取了苏州古城近期的街景图像<span style="box-sizing: border-box;">后，研究运用SegNet开展图像识别。</span><span style="box-sizing: border-box;">SegNet 可以提取图像特征，识别出天空、</span><span style="box-sizing: border-box;">道路、建筑、绿化和车辆等要素类型，</span><span style="box-sizing: border-box;">在此基础上可计算每张图片中不同要素</span><span style="box-sizing: border-box;">所占的比例(图6)。对苏州古城具体街</span><span style="box-sizing: border-box;">景的要素占比进行识别，可以为评价模</span><span style="box-sizing: border-box;">型的建立和导控策略的制定提供基础。</span><span style="box-sizing: border-box;">为了获取对街道的主观感知，研究</span><span style="box-sizing: border-box;">小组邀请规划专家及专业学生对街景打</span><span style="box-sizing: border-box;">分。首先，机器筛选出1500张具有苏</span><span style="box-sizing: border-box;">州古城街道代表的照片，然后手工精选</span><span style="box-sizing: border-box;">出500张最具代表性的比较样本，基于</span><span style="box-sizing: border-box;">JAVA 编写相应的评价程序，邀请专家及</span><span style="box-sizing: border-box;">学生对样本进行两两比较 (5000 次/ 人</span><span style="box-sizing: border-box;">×10 人/ 次)，选出感知度更高的街景图</span><span style="box-sizing: border-box;">片(图7)。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.4675926" data-w="1080" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2Of8KRiaTibdFfH1U4ypLyhUm41uDLBD4BzPJ7Te6S5xnXNo6q8NMSlu7Zw/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.4518519" data-w="1080" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfN2ebBkhmhnlqJ1Q0hibUTjpAZ9PPEo5hkVzJcEarHRkpyiaF0mibG8CFQ/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">其次，运用The Elo Rating System<span style="box-sizing: border-box;">算法，将两两比较的系列结果转化为每</span><span style="box-sizing: border-box;">张街景图片的实际分值，为之后的统计</span><span style="box-sizing: border-box;">分析提供分析基础。随后，运用ANN算</span><span style="box-sizing: border-box;">法计算得出这些相对小样本的街景品质</span><span style="box-sizing: border-box;">评价结果，训练自动化的品质评价模型，</span><span style="box-sizing: border-box;">用于对苏州古城街景的全面打分(图8)。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.6288416" data-w="846" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2Of7iadcGb5lcJ4OmKGqcTLKZqThfEJaYZTmve3nAuBBYT1y7C4UuhCgBQ/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（四）基于LBS 的街道行为活力分析</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">从苏州古城工作日和周末的人口分<span style="box-sizing: border-box;">布可以看到( 图9)，平江历史文化街区、</span><span style="box-sizing: border-box;">苏州大学、观前街和阊胥路等地区是全</span><span style="box-sizing: border-box;">天的人群热点地区。研究将人群热点以</span><span style="box-sizing: border-box;">古城街道为单位进行显示，便于下一步构</span><span style="box-sizing: border-box;">建慢行品质评价和完成街道画像，由此</span><span style="box-sizing: border-box;">可以观察到观前街、苏州大学、人民路</span><span style="box-sizing: border-box;">与干将东西路附近的街道人群密度较高。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.7296898" data-w="677" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2Of1iaM7NM0LlU4FOjGW05yKW2Kc9QZHzPJsc1IFicQVEclB7RkibickrgNpg/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（五）街道慢行品质评价与街道画像</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">基于形态、功能和感知三个维度的<span style="box-sizing: border-box;">分析，研究使用AHP层次分析法对苏州</span><span style="box-sizing: border-box;">古城区内的各个街道段进行慢行品质综</span><span style="box-sizing: border-box;">合评价(图10)，并开展全面画像，将总</span><span style="box-sizing: border-box;">得分前1/2 的街道视为慢行适宜型街道。</span><span style="text-indent: 2em;box-sizing: border-box;">随后，选取总得分后1/2 的街道，视为</span><span style="text-indent: 2em;box-sizing: border-box;">急需改进的街道，并根据人群活力的高</span><span style="text-indent: 2em;box-sizing: border-box;">低，分类型进行改善。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="1.146789" data-w="436" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfZIibr48wVp3TG7u24YStX6mB9H4ibdEics8ofBnB6Hrmeh2tia6JaOTBPg/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">研究将人群活力与三个维度做叠合<span style="box-sizing: border-box;">分析(图11)，叠合高活力街道与得分后</span><span style="box-sizing: border-box;">1/2街道的功能、特征和品质因素，得出</span><span style="box-sizing: border-box;">三类街道数量均较少，说明在古城内人群</span><span style="box-sizing: border-box;">活动多的区域，设施、街道形态与街景给</span><span style="box-sizing: border-box;">人的感受均较好；叠合低活力街道与得分</span><span style="box-sizing: border-box;">后1/2 街道的功能、特征和品质因素，得</span><span style="box-sizing: border-box;">出三类街道在古城不同区域均有所分布，</span><span style="box-sizing: border-box;">其中低活力—缺设施型街道的数量最多。</span><span style="box-sizing: border-box;">虽然研究不能直接论证设施的多样性差影</span><span style="box-sizing: border-box;">响了人群活动，但是后续从街道更新的角</span><span style="box-sizing: border-box;">度可以考虑适当在这类街道增加与居民日</span><span style="box-sizing: border-box;">常使用相关的各类设施。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.9732771" data-w="711" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfmicB292gav8U1VeLYuqAGBw02CvdjKTmGr5ic5jwxo0fw4ouiaRGagkbQ/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（六）街道个案的针对性导控策略展示</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">根据六类街道画像类型，研究选取了<span style="box-sizing: border-box;">六条街道段进行个案分析，并根据其得分</span><span style="box-sizing: border-box;">低的原因提出相应的导控策略(图12)。</span><span style="text-indent: 2em;box-sizing: border-box;">由于高活力街道意味着更高频的市民活</span><span style="text-indent: 2em;box-sizing: border-box;">动，在同等情况下，建议优先改进高活力</span><span style="text-indent: 2em;box-sizing: border-box;">的三类街道：①养蚕里弄某段为高活力—</span><span style="text-indent: 2em;box-sizing: border-box;">缺设施型街道，无街道主导功能，建议根</span><span style="text-indent: 2em;box-sizing: border-box;">据两边用地具体情况，在未来城市更新中</span><span style="text-indent: 2em;box-sizing: border-box;">考虑混合土地使用的设置与便民设施的设</span><span style="text-indent: 2em;box-sizing: border-box;">置。②潘儒巷某段为高活力—低适应型</span><span style="text-indent: 2em;box-sizing: border-box;">街道，由于是断头路，街道的步行性低，</span><span style="text-indent: 2em;box-sizing: border-box;">建议未来在街道更新中考虑打通邻近街</span><span style="text-indent: 2em;box-sizing: border-box;">巷，整治道路界面，优化步行流线，以</span><span style="text-indent: 2em;box-sizing: border-box;">更好地适应活动人群的需求。③西善长</span><span style="text-indent: 2em;box-sizing: border-box;">巷某段为高活力—低品质型街道，由于绿</span><span style="text-indent: 2em;box-sizing: border-box;">化较少、天空要素占比高，街道的步行</span><span style="text-indent: 2em;box-sizing: border-box;">感受差，且其在街道组构特质分类中属</span><span style="text-indent: 2em;box-sizing: border-box;">于偏车行的片区次要道路，建议通过增</span><span style="text-indent: 2em;box-sizing: border-box;">加街道家具等方式提升步行感受。未来，</span><span style="text-indent: 2em;box-sizing: border-box;">研究也可进一步对比单一维度优化后对</span><span style="text-indent: 2em;box-sizing: border-box;">街道活力和品质高低的影响。</span></p></section><section style="text-align: center;margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.5446809" data-w="705" src="http://mmbiz.qpic.cn/mmbiz_png/j8bTq15u0mgDckVZstibvzEYvXfXjg2OfEvZFvibCRFxavtrJk7N3MErH1ibq4GvjUzgQyHZU21FCbiadVicFHiapFhQ/640?wx_fmt=png" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="png"  /></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;"><span style="text-indent: 2em;box-sizing: border-box;">后续若条件允许，也可以考虑进一</span><span style="text-indent: 2em;box-sizing: border-box;">步改善低活力的三类街道：①幽兰路某</span><span style="text-indent: 2em;box-sizing: border-box;">巷道为低活力—缺设施型街道，无街道</span><span style="text-indent: 2em;box-sizing: border-box;">主导功能，建议根据周边居民实际需求</span><span style="text-indent: 2em;box-sizing: border-box;">适当增加服务设施。②西中市某巷段为</span><span style="text-indent: 2em;box-sizing: border-box;">低活力—低适应型街道，未来街道更新</span><span style="text-indent: 2em;box-sizing: border-box;">可适当考虑在其和北边道路间增加支路。</span><span style="text-indent: 2em;box-sizing: border-box;">③西大街某巷段为低活力—低品质型街</span><span style="text-indent: 2em;box-sizing: border-box;">道，建议优化街景品质，提升街道活力。</span></p></section></section></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.3692308" data-w="65" src="http://mmbiz.qpic.cn/mmbiz_gif/2BPlVTS3ahcJcSQTvU7yNR75YDHb1Rj9IYwb0KMjIpYzkc7shdchOXTP0b7DNoUfO8wzbShiaxNUS4pgbtfRrQg/640?wx_fmt=gif" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="gif"  /></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section class="horizontal-tb" style="display: inline-block;border-radius: 1em;background-color: rgb(21, 103, 167);padding: 0.3em 0.8em;color: rgb(255, 255, 255);font-size: 18px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">五</strong></p><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">讨论与展望</strong></p></section></section><section style="display: block;box-sizing: border-box;" powered-by="gulangu"><section style="margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;"><section style="display: inline-block;width: 100%;border-width: 1px;border-style: solid;border-color: rgb(21, 103, 167);padding: 10px;box-shadow: rgb(0, 0, 0) 0px 0px 0px;box-sizing: border-box;"><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（一）多维度街道慢行品质评价</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">本次研究提出的多维度街道慢行品<span style="box-sizing: border-box;">质的评价方法相较于传统的定性、单一</span><span style="box-sizing: border-box;">维度的定量研究，具有综合性、普适性</span><span style="box-sizing: border-box;">的优点。首先，不同于以往新数据和新</span><span style="box-sizing: border-box;">技术的点状运用尝试，本次研究整合了</span><span style="box-sizing: border-box;">街道品质评价的环境要素和使用适应性，</span><span style="box-sizing: border-box;">从形态、功能、感知和行为等多维度进</span><span style="box-sizing: border-box;">行系统性的评价。其次，开源的分析技</span><span style="box-sizing: border-box;">术以及POI 数据、街景数据、LBS数据</span><span style="box-sizing: border-box;">和OSM数据等相较于人工踏勘拍照，能</span><span style="box-sizing: border-box;">大大节省时间，高效地大规模展开分析，</span><span style="box-sizing: border-box;">可以运用在多个城市中，在保持人本尺</span><span style="box-sizing: border-box;">度精细度的同时，获得城市乃至区域尺</span><span style="box-sizing: border-box;">度的慢行品质评价。</span></p><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">在新数据的多样性、空间精度和普<span style="box-sizing: border-box;">遍性都不断增强的大背景下，“街道城</span><span style="box-sizing: border-box;">市主义”“人本城市主义”等理念正逐</span><span style="box-sizing: border-box;">渐从口号式的呼吁和探索性的研究，转</span><span style="box-sizing: border-box;">化为规划设计实践中的切实运用。新城</span><span style="box-sizing: border-box;">市科学背景下新数据和新技术的涌现，</span><span style="box-sizing: border-box;">正在为品质和活力导向的城市设计与导</span><span style="box-sizing: border-box;">控带来新的可能。相对于传统的定性研</span><span style="box-sizing: border-box;">究和基于小样本数据的统计分析，利用</span><span style="box-sizing: border-box;">大规模、多源城市数据的“厚数据模型”，</span><span style="box-sizing: border-box;">可以高效、快速和科学地实现问题导向</span><span style="box-sizing: border-box;">下的城市分析，助力于城市规划和城市</span><span style="box-sizing: border-box;">设计实践的科学化，更好地协助“品</span><span style="box-sizing: border-box;">质”“活力”导向下的相关规划与城市</span><span style="box-sizing: border-box;">设计。</span></p></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（二）适用城市设计与“城市双修”等实践运用</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">这一分析框架在当下总体城市设计<span style="box-sizing: border-box;">和“城市双修”等需要开展大规模分析</span><span style="box-sizing: border-box;">且兼具人本尺度的规划设计实践中具有</span><span style="box-sizing: border-box;">很强的操作性，特别是纳入了街景</span><span style="box-sizing: border-box;">数据和机器学习的视觉感知评价，丰富</span><span style="box-sizing: border-box;">了以往城市数据局限于2D 层面的问题，</span><span style="box-sizing: border-box;">补充了3D层面的视角，进一步完善了传</span><span style="box-sizing: border-box;">统小样本数据分析涉及面小的缺陷，为</span><span style="box-sizing: border-box;">后续的设计提供了数据支撑。</span></p><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">这一综合化、自动化的分析框架也<span style="box-sizing: border-box;">能助力于美丽街区建设和街道微更新等</span><span style="box-sizing: border-box;">人本尺度规划实践，既能基于全城街道</span><span style="box-sizing: border-box;">进行大规模品质分析，又能对与品质相</span><span style="box-sizing: border-box;">关的要素属性做针对性分析，根据具体</span><span style="box-sizing: border-box;">街道个案找出问题所在，为街道更新的</span><span style="box-sizing: border-box;">选点和导控策略提供依据。</span></p></section><section style="margin: 0.5em 0px;text-align: left;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;vertical-align: top;box-sizing: border-box;"><section class="horizontal-tb" style="background-color: rgb(21, 103, 167);color: rgb(255, 255, 255);padding-left: 5px;padding-right: 5px;margin-bottom: 4px;letter-spacing: 1px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">（三）研究局限与未来探索</p></section><section style="height: 2px;width: 100%;background-color: rgb(0, 0, 0);box-sizing: border-box;"></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="text-indent: 2em;white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;">本次研究的亮点在于进行了多维度<span style="box-sizing: border-box;">的街道品质评价，但受数据源与研究局</span><span style="box-sizing: border-box;">限，仍有一定不足。在数据收集方面，</span><span style="box-sizing: border-box;">部分适宜居民步行的巷道不宜采样车通</span><span style="box-sizing: border-box;">行，缺少街景数据，后续考虑进行现场</span><span style="box-sizing: border-box;">补拍。街景数据受限于采样车的视角，</span><span style="box-sizing: border-box;">对于行人更为常用的人行道空间的反映</span><span style="box-sizing: border-box;">会有所偏差。此外，LBS的信度还需增强，</span><span style="box-sizing: border-box;">其定位与采样方面可能存在一定的误差。</span><span style="box-sizing: border-box;">在未来的研究中，需扩大分析范围及内容，</span><span style="box-sizing: border-box;">进一步研究街道慢行品质与实际出行行为</span><span style="box-sizing: border-box;">及居民健康的相关性，为人本导向的规划</span><span style="box-sizing: border-box;">设计实践提供更多维度的支撑。</span></p></section></section></section></section><section style="margin: 0.5em 0px;text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="max-width: 100%;vertical-align: middle;display: inline-block;line-height: 0;box-sizing: border-box;"><img class="raw-image" data-ratio="0.3692308" data-w="65" src="http://mmbiz.qpic.cn/mmbiz_gif/2BPlVTS3ahcJcSQTvU7yNR75YDHb1Rj9IYwb0KMjIpYzkc7shdchOXTP0b7DNoUfO8wzbShiaxNUS4pgbtfRrQg/640?wx_fmt=gif" style="vertical-align: middle;max-width: 100%;box-sizing: border-box;" data-type="gif"  /></section></section><section style="margin: 0.5em 0px;box-sizing: border-box;" powered-by="gulangu"><section style="padding: 5px;background-color: rgb(21, 103, 167);box-sizing: border-box;"><section style="display: inline-block;width: 100%;border-color: white;padding: 10px;border-style: solid;border-width: 1px;box-shadow: rgb(0, 0, 0) 0px 0px 0px;box-sizing: border-box;"><section class="horizontal-tb" style="text-align: center;color: rgb(255, 255, 255);font-size: 14px;box-sizing: border-box;" powered-by="gulangu"><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">文章全文详见《规划师》2019年14期</strong></p><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">《</strong>街道慢行品质的多维度评价与导控策略——基于多源城市数据的整合分析<strong style="letter-spacing: 0px;box-sizing: border-box;"><span style="letter-spacing: 0px;line-height: 1.45;box-sizing: border-box;">》</span></strong></p></section></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;"><br style="box-sizing: border-box;"  /></p></section><section style="text-align: center;margin: 10px 0%;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 95%;vertical-align: top;border-style: solid;border-width: 2px;border-radius: 0px;border-color: rgb(181, 180, 180);box-sizing: border-box;"><section style="margin: -5px 0% 5px;transform: translate3d(-5px, 0px, 0px);-webkit-transform: translate3d(-5px, 0px, 0px);-moz-transform: translate3d(-5px, 0px, 0px);-o-transform: translate3d(-5px, 0px, 0px);box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;vertical-align: top;background-color: rgb(252, 221, 93);padding: 5px;border-width: 0px;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;vertical-align: top;border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 202, 0);background-color: rgb(255, 255, 255);padding: 10px;box-sizing: border-box;"><section style="margin: 10px 0% 0px;box-sizing: border-box;" powered-by="gulangu"><section class="horizontal-tb" style="color: rgb(100, 100, 100);font-size: 14px;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;"><strong style="box-sizing: border-box;">来源：2019年14期《规划师》杂志</strong><br style="box-sizing: border-box;"  /></p></section></section><section style="margin: 0px 0% 8px;box-sizing: border-box;" powered-by="gulangu"><section style="background-color: rgb(181, 180, 180);height: 2px;box-sizing: border-box;"></section></section><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;vertical-align: top;padding: 10px;box-sizing: border-box;"><section style="margin: 10px 0% 0px;box-sizing: border-box;" powered-by="gulangu"><section class="horizontal-tb" style="font-size: 14px;color: rgb(100, 100, 100);line-height: 1.8;box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">新媒体编辑：刘晓莹</p></section></section><section style="margin: 10px 0%;box-sizing: border-box;" powered-by="gulangu"><section class="horizontal-tb" style="font-size: 14px;line-height: 1.8;color: rgb(100, 100, 100);box-sizing: border-box;"><p style="margin: 0px;padding: 0px;box-sizing: border-box;">审读：刘芳</p></section></section></section></section></section></section></section></section></section></section><section class="horizontal-tb" style="box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;margin: 0px;padding: 0px;box-sizing: border-box;"><br style="box-sizing: border-box;"  /></p></section><section style="margin-top: 10px;margin-bottom: 10px;box-sizing: border-box;" powered-by="gulangu"><section style="width: 100%;font-size: 0px;box-sizing: border-box;"><section style="margin-left: 24px;border-bottom: 1px solid rgb(156, 94, 21);box-sizing: border-box;"></section><section style="float: left;margin-top: -1px;background-color: rgb(255, 255, 254) !important;box-sizing: border-box;"><section style="width: 0px;height: 8px;border-left: 1px solid rgb(156, 94, 21);margin-left: 23px;box-sizing: border-box;"></section><section style="width: 16px;margin-left: 8px;box-sizing: border-box;"><section style="width: 16px;height: 8px;border-left: 1px solid rgb(156, 94, 21);border-right: 1px solid rgb(156, 94, 21);border-bottom: 1px solid rgb(156, 94, 21);box-sizing: border-box;"></section><section style="width: 8px;height: 16px;margin-top: -8px;border-top: 1px solid rgb(156, 94, 21);border-right: 1px solid rgb(156, 94, 21);border-bottom: 1px solid rgb(156, 94, 21);box-sizing: border-box;"></section></section><section style="width: 8px;height: 16px;border-top: 1px solid rgb(156, 94, 21);border-left: 1px solid rgb(156, 94, 21);margin-top: -1px;box-sizing: border-box;"></section></section><section style="float: right;margin-top: -1px;background-color: rgb(255, 255, 254) !important;box-sizing: border-box;"> <section style="width: 0px;height: 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border-box;"></section><section style="width: 16px;margin-left: 8px;margin-top: -1px;box-sizing: border-box;"><section style="width: 8px;height: 16px;border-bottom: 1px solid rgb(156, 94, 21);border-right: 1px solid rgb(156, 94, 21);border-top: 1px solid rgb(156, 94, 21);box-sizing: border-box;"></section><section style="width: 16px;height: 8px;margin-top: -8px;border-top: 1px solid rgb(156, 94, 21);border-right: 1px solid rgb(156, 94, 21);border-left: 1px solid rgb(156, 94, 21);box-sizing: border-box;"></section></section><section style="width: 0px;height: 8px;border-left: 1px solid rgb(156, 94, 21);margin-left: 23px;box-sizing: border-box;"></section></section> <section style="float: right;margin-top: -2px;background-color: rgb(255, 255, 254) !important;box-sizing: border-box;"><section style="width: 8px;height: 16px;margin-bottom: 1px;margin-left: 16px;border-bottom: 1px solid rgb(156, 94, 21);border-right: 1px solid rgb(156, 94, 21);box-sizing: border-box;"></section><section 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