Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Shengyuan Zou"'
Publikováno v:
Remote Sensing, Vol 16, Iss 18, p 3466 (2024)
Building change detection (BCD) from remote sensing images is an essential field for urban studies. In this well-developed field, Convolutional Neural Networks (CNNs) and Transformer have been leveraged to empower BCD models in handling multi-scale i
Externí odkaz:
https://doaj.org/article/cf3696d478b74904aa9df540d6d97ab5
Autor:
Shengyuan Zou, Le Wang
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 113, Iss , Pp 103018- (2022)
Abandoned houses (AH) present an utmost challenge confronting the urban environment in contemporary U.S. shrinking cities. Data accessibility is a major hurdle that prevents the acquisition of large-scale AH information at the individual property lev
Externí odkaz:
https://doaj.org/article/3c77072c95054385bfab6d01f4c2dc0e
Publikováno v:
Sensors, Vol 21, Iss 9, p 3300 (2021)
(1) Background: Public sidewalk GIS data are essential for smart city development. We developed an automated street-level sidewalk detection method with image-processing Google Street View data. (2) Methods: Street view images were processed to produ
Externí odkaz:
https://doaj.org/article/75f0ea3b17d64bfd979d0caee9f4bd89
Publikováno v:
Remote Sensing, Vol 10, Iss 12, p 1920 (2018)
The vacant house is an essential phenomenon of urban decay and population loss. Exploration of the correlations between housing vacancy and some socio-environmental factors is conducive to understanding the mechanism of urban shrinking and revitaliza
Externí odkaz:
https://doaj.org/article/3f821ab425c54895aeb19a97a373dda9
Detecting individual abandoned houses from google street view: A hierarchical deep learning approach
Autor:
Shengyuan Zou, Le Wang
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 175:298-310
Abandoned houses (AH) are focal points in urban communities by threatening local security, destroying housing markets, and burdening government finance in the U.S. legacy cities. In particular, individual-level AH detection provides essential informa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20b9422bf5958ca5fab147b6fa9da93f
https://doi.org/10.1016/j.isprsjprs.2021.03.020
https://doi.org/10.1016/j.isprsjprs.2021.03.020
Publikováno v:
International Journal of Remote Sensing. 41:3147-3161
Night-Time light imagery has become a very popular data source for monitoring the intensity of human activity in urban environments. Subpixel information is required in many applications, however, ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3eb89105724361e4314675baa6495fc1
https://doi.org/10.1080/01431161.2019.1699673
https://doi.org/10.1080/01431161.2019.1699673
Autor:
Le Wang, Shengyuan Zou
Publikováno v:
Annals of the American Association of Geographers. 110:449-461
The formation and demolition of vacant houses are the most visible sign of city shrinking and revitalization. Timely detection of vacant houses has become an inevitable task to aid the “Smart City”...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f7c9dc7424e53be49c3538ab0c7298dc
https://doi.org/10.1080/24694452.2019.1665492
https://doi.org/10.1080/24694452.2019.1665492
Publikováno v:
International Journal of Applied Earth Observation and Geoinformation. 81:13-26
Public Earth Observation (EO) data archives, e.g., MODIS, Landsat, and Sentinels, are valuable sources of information for a broad range of applications. For decision-supporting applications used in urban planning, land management, and sustainable dev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e80446f4ad36519ca0b25874354f0680
https://doi.org/10.1016/j.jag.2019.05.006
https://doi.org/10.1016/j.jag.2019.05.006
Autor:
Shengyuan Zou, Le Wang
Publikováno v:
Smart Spaces and Places ISBN: 9781003145868
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cedc6f26231eb23c95f16e71202f315f
https://doi.org/10.4324/9781003145868-12
https://doi.org/10.4324/9781003145868-12
Publikováno v:
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 9
Sensors, Vol 21, Iss 3300, p 3300 (2021)
Sensors
Volume 21
Issue 9
Sensors, Vol 21, Iss 3300, p 3300 (2021)
(1) Background: Public sidewalk GIS data are essential for smart city development. We developed an automated street-level sidewalk detection method with image-processing Google Street View data. (2) Methods: Street view images were processed to produ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da4300c3d02d8db25ddea4bd157a617d
https://pubmed.ncbi.nlm.nih.gov/34068791
https://pubmed.ncbi.nlm.nih.gov/34068791