| Assessing street-level urban greenery using Google Street View and a modified green view index X Li, C Zhang, W Li, R Ricard, Q Meng, W Zhang Urban Forestry & Urban Greening 14 (3), 675-685, 2015 | 796 | 2015 |
| Mapping sky, tree, and building view factors of street canyons in a high-density urban environment FY Gong, ZC Zeng, F Zhang, X Li, E Ng, LK Norford Building and Environment 134, 155-167, 2018 | 258 | 2018 |
| Quantifying the shade provision of street trees in urban landscape: A case study in Boston, USA, using Google Street View X Li, C Ratti, I Seiferling Landscape and Urban Planning 169, 81-91, 2018 | 234 | 2018 |
| Who lives in greener neighborhoods? The distribution of street greenery and its association with residents’ socioeconomic conditions in Hartford, Connecticut, USA X Li, C Zhang, W Li, YA Kuzovkina, D Weiner Urban Forestry & Urban Greening 14 (4), 751-759, 2015 | 213 | 2015 |
| Does the visibility of greenery increase perceived safety in urban areas? Evidence from the place pulse 1.0 dataset X Li, C Zhang, W Li ISPRS International Journal of Geo-Information 4 (3), 1166-1183, 2015 | 134 | 2015 |
| Comparing the normalized difference vegetation index with the google street view measure of vegetation to assess associations between greenness, walkability, recreational … PJ Villeneuve, RL Ysseldyk, A Root, S Ambrose, J DiMuzio, N Kumar, ... International journal of environmental research and public health 15 (8), 1719, 2018 | 119 | 2018 |
| Mapping the spatial distribution of shade provision of street trees in Boston using Google Street View panoramas X Li, C Ratti Urban Forestry & Urban Greening 31, 109-119, 2018 | 117 | 2018 |
| Investigating the association between streetscapes and human walking activities using Google Street View and human trajectory data X Li, P Santi, TK Courtney, SK Verma, C Ratti Transactions in GIS 22 (4), 1029-1044, 2018 | 95 | 2018 |
| Environmental inequities in terms of different types of urban greenery in Hartford, Connecticut X Li, C Zhang, W Li, YA Kuzovkina Urban Forestry & Urban Greening 18, 163-172, 2016 | 93 | 2016 |
| Parcel-based urban land use classification in megacity using airborne LiDAR, high resolution orthoimagery, and Google Street View W Zhang, W Li, C Zhang, DM Hanink, X Li, W Wang Computers, Environment and Urban Systems 64, 215-228, 2017 | 90 | 2017 |
| Building block level urban land-use information retrieval based on Google Street View images X Li, C Zhang, W Li GIScience & Remote Sensing 54 (6), 819-835, 2017 | 89 | 2017 |
| Mapping urban landscapes along streets using google street view X Li, C Ratti, I Seiferling Advances in Cartography and GIScience: Selections from the International …, 2017 | 86 | 2017 |
| Using deep learning to identify utility poles with crossarms and estimate their locations from google street view images W Zhang, C Witharana, W Li, C Zhang, X Li, J Parent Sensors 18 (8), 2484, 2018 | 81 | 2018 |
| Mapping the spatio-temporal distribution of solar radiation within street canyons of Boston using Google Street View panoramas and building height model X Li, C Ratti Landscape and urban planning 191, 103387, 2019 | 80 | 2019 |
| Subjective or objective measures of street environment, which are more effective in explaining housing prices? W Qiu, Z Zhang, X Liu, W Li, X Li, X Xu, X Huang Landscape and Urban Planning 221, 104358, 2022 | 78 | 2022 |
| A big data approach to understanding pedestrian route choice preferences: Evidence from San Francisco A Sevtsuk, R Basu, X Li, R Kalvo Travel behaviour and society 25, 41-51, 2021 | 73 | 2021 |
| The distribution of greenspace quantity and quality and their association with neighbourhood socioeconomic conditions in Guangzhou, China: A new approach using deep learning … R Wang, Z Feng, J Pearce, Y Yao, X Li, Y Liu Sustainable Cities and Society 66, 102664, 2021 | 70 | 2021 |
| Treepedia 2.0: applying deep learning for large-scale quantification of urban tree cover BY Cai, X Li, I Seiferling, C Ratti 2018 IEEE International Congress on Big Data (BigData Congress), 49-56, 2018 | 62 | 2018 |
| Associations between body mass index and urban “green” streetscape in Cleveland, Ohio, USA X Li, D Ghosh International journal of environmental research and public health 15 (10), 2186, 2018 | 60 | 2018 |
| Examining the spatial distribution and temporal change of the green view index in New York City using Google Street View images and deep learning X Li Environment and Planning B: Urban Analytics and City Science 48 (7), 2039-2054, 2021 | 59 | 2021 |
Carlo RattiProfessor, Senseable City Lab, Department of Urban Studies and Planning, MIT在 mit.edu 的电子邮件经过验证
