Results 51 to 60 of about 241,334 (180)

Googleストリートビューのパノラマ画像を用いた広域・網羅的な地域景観分析 [PDF]

, 2016
地域景観研究では，局所的な箇所や区間が対象となる場合が多いが，地域の全体像を捉えるためには広域的，網羅的な分析が必要となる．本研究では，Googleストリートビューのパノラマ画像を用いた景観可視化手法を開発し，それによる道路景観の空間分布から地域景観分析を行った．富良野・美瑛観光圏を対象に，100m間隔の視点からパノラマ画像を取得し，そのフラクタル次元，空・緑の占有率から対象地域の景観を5つのクラスターに類型化した．さらに ...
亀山 修一, 浅田 拓海
core   +2 more sources

Hyperlocal variation of nitrogen dioxide, black carbon, and ultrafine particles measured with Google Street View cars in Amsterdam and Copenhagen.

Environment International, 2022
Hyperlocal air quality maps are becoming increasingly common, as they provide useful insights into the spatial variation and sources of air pollutants.
J. Kerckhoffs, J. Khan, G. Hoek, Zhendong Yuan, O. Hertel, M. Ketzel, S. Jensen, Fares Al Hasan, K. Meliefste, Roel C. H. Vermeulen   +9 more
semanticscholar   +1 more source

Fine-Grained Car Detection for Visual Census Estimation

, 2017
Targeted socioeconomic policies require an accurate understanding of a country's demographic makeup. To that end, the United States spends more than 1 billion dollars a year gathering census data such as race, gender, education, occupation and ...
Chen, Duyun, Deng, Jia, Fei-Fei, Li, Gebru, Timnit, Krause, Jonathan, Wang, Yilun   +5 more
core   +1 more source

Measuring changes in neighborhood disorder using Google Street View longitudinal imagery: a feasibility study

Cities & Health, 2023
Few studies have used longitudinal imagery of Google Street View (GSV) despite its potential for measuring changes in urban streetscape characteristics relevant to health, such as neighborhood disorder.
P. Gullón, D. Fry, Jesse J. Plascak, S. Mooney, G. Lovasi   +4 more
semanticscholar   +1 more source

A street-view-based method to detect urban growth and decline: A case study of Midtown in Detroit, Michigan, USA

PLoS ONE, 2022
Urban growth and decline occur every year and show changes in urban areas. Although various approaches to detect urban changes have been developed, they mainly use large-scale satellite imagery and socioeconomic factors in urban areas, which provides an ...
Giyoung Byun, Youngchul Kim
doaj  

Fusion of Google Street View, LiDAR, and Orthophoto Classifications Using Ranking Classes Based on F1 Score for Building Land-Use Type Detection

Remote Sensing
Building land-use type classification using earth observation data is essential for urban planning and emergency management. Municipalities usually do not hold a detailed record of building land-use types in their jurisdictions, and there is a ...
Nafiseh Ghasemian Sorboni, Jinfei Wang, M. Najafi   +2 more
semanticscholar   +1 more source

Measuring Perceived Psychological Stress in Urban Built Environments Using Google Street View and Deep Learning

Frontiers in Public Health, 2022
An urban built environment is an important part of the daily lives of urban residents. Correspondingly, a poor design can lead to psychological stress, which can be harmful to their psychological and physical well-being.
Xing Han, Lei Wang, S. Seo, Jie He, Tae-Yong Jung   +4 more
semanticscholar   +1 more source

Tra advergame e mappe online: contaminazioni tra Street View e discorso pubblicitario

G|A|M|E The Italian Journal of Game Studies, 2013
Molti servizi di cartografia online – Google Maps, Bing Maps, Nokia Maps, Yandex Maps e altri ancora – permettono di esplorare alcuni luoghi da un punto di vista quasi in soggettiva, come se l'utente si trovasse effettivamente sul posto.
Gabriele Ferri
doaj  

Predicting Household Income with Sentinel and Street View Imagery: A Comparative Study across Amsterdam, Sydney, and New York

International Journal of Applied Earth Observations and Geoinformation
In the context of urbanisation and growing disparities, timely and detailed spatial data on income inequality in cities is essential. We combined satellite imagery with streetlevel photographs provided by Google Street View to reveal the spatial ...
Oleksandr Karasov, Evelyn Uuemaa, Olle Järv, Monika Kuffer, Tiit Tammaru   +4 more
doaj   +1 more source

​Parcel feature data derived from Google Street View images for urban land use classification in Brooklyn, New York Cityfor urban land use classification in Brooklyn, New York Cityretain-->

Data in Brief, 2017
Google Street View (GSV) was used for urban land use classification, together with airborne light detection and ranging (LiDAR) data and high resolution orthoimagery, by a parcel-based method.
Weixing Zhang, Weidong Li, Chuanrong Zhang, Dean M. Hanink, Xiaojiang Li, Wenjie Wang   +5 more
doaj   +1 more source