Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Hanfa Xing"'
Publikováno v:
Geo-spatial Information Science, Pp 1-23 (2024)
Street space is a crucial component of public space, serving as a site for a variety of human activities. However, prior studies have primarily focused on the traffic function of street space, neglecting other functional types, such as residential an
Externí odkaz:
https://doaj.org/article/7bacfa29034d4ff59cc851adda33b196
Publikováno v:
Geo-spatial Information Science, Vol 0, Iss 0, Pp 1-16 (2022)
The classification of urban functional areas plays an important role in urban planning and resource management. Although previous studies have confirmed that different urban functional areas have different morphological structures and Land Surface Te
Externí odkaz:
https://doaj.org/article/92a9732e18754dff8b90e53ce481cd1b
Autor:
Yuan Meng, Man Sing Wong, Hanfa Xing, Rui Zhu, Kai Qin, Mei-Po Kwan, Kwon Ho Lee, Coco Yin Tung Kwok, Hon Li
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
Abstract Urban functional fragmentation plays an important role in assessing Nitrogen Dioxide (NO2) emissions and variations. While the mediated impact of anthropogenic-emission restriction has not been comprehensively discussed, the lockdown respons
Externí odkaz:
https://doaj.org/article/a69ad98b00ec4715ac520a11e10f53dd
Publikováno v:
IEEE Access, Vol 9, Pp 53013-53029 (2021)
Urban functional zones are considered significant components for understanding urban landscape patterns in the socioeconomic environment. Although the spatial configuration of road networks contributes to urban function delineation at the block level
Externí odkaz:
https://doaj.org/article/e4676cb4ce5b4bd5abd086fd6c0489c9
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 103, Iss , Pp 102514- (2021)
Remote Sensing (RS) has been used in urban mapping for a long time; however, the complexity and diversity of urban functional patterns are difficult to be captured by RS only. Emerging Geospatial Big Data (GBD) are considered as the supplement to RS
Externí odkaz:
https://doaj.org/article/9d176cb509d9423095f49e9c018ec0be
Publikováno v:
Applied Sciences, Vol 12, Iss 24, p 12796 (2022)
Network-constrained spatial flows are usually used to describe movements between two spatial places on a road network. The analysis of the spatial associations between different types of network-constrained spatial flows plays a key role in understan
Externí odkaz:
https://doaj.org/article/3bdb9e6e4e134653b57529ec83f02cb5
Publikováno v:
Applied Sciences, Vol 13, Iss 1, p 492 (2022)
Hyperspectral image (HSI) classification is an important but challenging topic in the field of remote sensing and earth observation. By coupling the advantages of convolutional neural network (CNN) and Transformer model, the CNN–Transformer hybrid
Externí odkaz:
https://doaj.org/article/9d186a2ad4894fffac1099d0c3f97555
Publikováno v:
PLoS ONE, Vol 15, Iss 12, p e0244084 (2020)
Regional differences in socioeconomic factors are important for assessing the regional development of an area. While much research has focused on the overall patterns of regional differences within independent cities and areas, the hierarchical spati
Externí odkaz:
https://doaj.org/article/86d32cb4eba04fbe9c60edeb2902c165
Publikováno v:
Remote Sensing, Vol 13, Iss 19, p 3898 (2021)
Automatically extracting buildings from remote sensing images with deep learning is of great significance to urban planning, disaster prevention, change detection, and other applications. Various deep learning models have been proposed to extract bui
Externí odkaz:
https://doaj.org/article/0aad8a29b6b44cf396c1423c15e649f3
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 10, Iss 6, p 401 (2021)
The novel coronavirus disease 2019 (COVID-19) has caused significantly changes in worldwide environmental and socioeconomics, especially in the early stage. Previous research has found that air pollution is potentially affected by these unprecedented
Externí odkaz:
https://doaj.org/article/ae92da84e71f44c1b6fee1bef483880a