دسته بندی:
بینایی ماشین - Machine vision
سال انتشار:
2022
عنوان انگلیسی مقاله:
Using social media photos and computer vision to assess cultural ecosystem services and landscape features in urban parks
ترجمه فارسی عنوان مقاله:
استفاده از عکس های رسانه های اجتماعی و بینایی کامپیوتری برای ارزیابی خدمات اکوسیستم فرهنگی و ویژگی های چشم انداز در پارک های شهری
منبع:
ScienceDirect- Elsevier- Ecosystem Services, 57 (2022) 101475: doi:10:1016/j:ecoser:2022:101475
نویسنده:
Songyao Huai
چکیده انگلیسی:
Urban parks are important public places that provide an opportunity for city dwellers to interact with nature. In
recent years, social media data have become a promising data source for the assessment of cultural ecosystem
services (CES) and landscape features in urban parks. However, it is a challenging task to identify and classify the
CES and landscape features from social media photos by manual content analysis. In addition, relatively few
studies focused on the differences in landscape preferences between tourists and locals in urban parks. In this
study, we used geotagged social media photos from Flickr and computer vision methods (scene recognition,
image clustering and image labeling) based on the convolutional neural networks (CNN) and the Google Cloud
Vision platform to assess the spatial preferences and landscape preferences (cultural ecosystem services and
landscape features) of tourists and locals in the urban parks of Brussels. The spatial analysis results showed that
the tourists’ photos were spatially concentrated on well-known parks located in the city center while the locals’
photos were rather spatially dispersed across all parks of the city. We identified 10 main landscape themes
(corresponding to 4 CES categories and 10 landscape feature categories) from 20 image clusters by automated
image analysis on social media photos. We also noticed that tourists paid more attention to the place identity
featured by symbolic sculptures and buildings, while locals showed more interest in local species of plants,
flowers, insects, birds, and animals. This research contributes to social media-based user preferences analysis and
CES assessment, which could provide insights for urban park planning and tourism management.
keywords: داده های رسانه های اجتماعی | خدمات اکوسیستم فرهنگی | ویژگی های چشم انداز | پارک های شهری | بینایی کامپیوتر | Social media data | Cultural ecosystem services | Landscape features | Urban parks | Computer vision
قیمت: رایگان
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