利用游客受雇拍摄法和云图标注应用程序接口探究均质化景观的识别与分类——以日本东京桥区河流景观为例  

Recognition and Classification of Homogeneous Landscape With Visitor–Employed Photography and Cloud Image Annotation API——An Example of the Riverscape in Nihonbashi,Tokyo,Japan

作　　者：施佳颖 本條毅 矢泽优里子 古谷胜则 SHI Jiaying;Tsuyoshi HONJO;Yuriko YAZAWA;Katsunori FURUYA(Department of Landscape Architecture,School of Architecture,Southeast University;Department of Environmental Science and Landscape Architecture,Graduate School of Horticulture,Chiba University)

机构地区：[1]东南大学建筑学院景观学系 [2]日本千叶大学园艺学研究科环境科学与绿地造园学系

出　　处：《景观设计学（中英文）》2021年第5期12-31,共20页Landscape Architecture Frontiers

基　　金：日本学术振兴会Kakenhi基金项目“作为私人和非正式绿地的绿色基础设施:论参与式维护政策”(编号:JP 17K08179)。

摘　　要：对景观照片进行有效的分类是数据处理和环境分析中至关重要的一步。随着地理信息的收集逐渐采用众包模式,越来越多的研究开始利用带有地理标记的照片,将人们对场所的感知与互动可视化,并探究场所的美学、文化和游憩价值。近年来,图像识别机器学习算法的应用极大提高了关键词匹配的效率,并实现了大批量照片的自动分类。然而,这类方法在景观分类实践中—尤其是针对具有相似特点的均质化景观—应用仍显不足。本研究利用谷歌云视觉API和多层次聚类法,研发了一种半自动化的分类器来识别均质化景观照片,并将其应用于日本东京桥区城市河流均质化景观照片的分类中。分类器将所有河流景观划分为9个特征组,这些特征组的视觉印象与人们的直观感知一致。研究中所应用的混淆矩阵显示,分类器分类结果总体上的准确性达82.61%,表明机器分类与人工分类的结果十分相近。因此,该分类器对均质化河流景观照片的分类切实有效。这种方法可大力推动评估过程中的公众参与及城市旅游管理。Effective classification of landscape photographs is a vital step in data processing and environment analysis.With the popularity of crowdsourcing geo-information,an increasing number of studies have used geotagged photographs to visualize how people perceive and interact with destinations and explore the aesthetic,cultural,and recreational value of the areas.In recent years,machine-learning algorithms for image recognition have dramatically improved the efficiency of the assignment of keywords and provide possibilities for the automatic classification of numerous photographs.However,the applicability of such methods for the practical landscape classification is still not clear,especially for the photographs presenting a homogeneous landscape that has similar characteristics.This study developed a semi-automatic classifier for homogeneous landscape photographs by using Google Cloud Vision API and multi-level hierarchical clustering.The classifier was applied to the classification of urban riverscape photographs,which is a typical example of homogeneous landscapes in Nihonbashi,Tokyo,Japan.The riverscapes can be classified into 9 characteristic groups by the classifier and the visual impression of these groups matches well with our intuitive feeling.A confusion matrix showed that the overall accuracy was 82.61%,indicating a strong agreement between the classifier and manual classification.Therefore,the classifier is practical for classifying homogeneous riverscape photographs.Such methodology also provides the possibility of public participation in the assessing process,which,in turn,contributes to urban tourism management.

关 键 词：均质化景观 景观特征 图像标注 照片分类 城市河流景观 机器学习 聚类 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TU984[自动化与计算机技术—控制科学与工程]