Zobrazeno 1 - 10
of 56
pro vyhledávání: '"XIAOCONG XU"'
Inferring the heterogeneous effect of urban land use on building height with causal machine learning
Publikováno v:
GIScience & Remote Sensing, Vol 61, Iss 1 (2024)
ABSTRACTMachine learning has become an important approach for land use change modeling. However, conventional machine learning algorithms are limited in their ability to capture causal relationships in land use change, which are important knowledge f
Externí odkaz:
https://doaj.org/article/cc5193c164e0466c84cba2e6a5029b50
Publikováno v:
GIScience & Remote Sensing, Vol 59, Iss 1, Pp 609-632 (2022)
Cellular automata (CA) model is a useful tool for simulating spatiotemporal changes of land-use evolution. However, previous CA models have usually ignored the inhomogeneous and mixed land-use situations and simplified the land grid cell as one singl
Externí odkaz:
https://doaj.org/article/18fb59ab803e4dc581274a58581da84f
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 118, Iss , Pp 103226- (2023)
Carbon emissions from forest ecosystems are greatly impacted by the acceleration of fragmentation and edge effects. Understanding these effects requires accurate monitoring of changes in fragmented forest landscapes. However, these changes are often
Externí odkaz:
https://doaj.org/article/b4606560d8604a679d2a9c9a1ca4b3b1
Publikováno v:
Geo-spatial Information Science, Pp 1-18 (2022)
The accessibility provided by the transportation system plays an essential role in driving urban growth and urban functional land use changes. Conventional studies on land use simulation usually simplified the accessibility as proximities and adopted
Externí odkaz:
https://doaj.org/article/2fea8acd578d4f3c94a61149bdbff4ee
Autor:
Guangzhao Chen, Xia Li, Xiaoping Liu, Yimin Chen, Xun Liang, Jiye Leng, Xiaocong Xu, Weilin Liao, Yue’an Qiu, Qianlian Wu, Kangning Huang
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-12 (2020)
Shared socioeconomic pathways (SSPs) is a crucial scenario describing the potential of future socio-economic development. The authors here investigate long-term effects of various government policies suggested by different SSPs on urban land and reve
Externí odkaz:
https://doaj.org/article/0ce8401435f348c9b0e8841de7abadad
Publikováno v:
International Journal of Disaster Risk Science, Vol 10, Iss 4, Pp 557-572 (2019)
Abstract By using the latest China population grid and land-use data, we assess the changing exposure of China’s population and land uses to the hazards of storm surges, droughts, earthquakes, floods, and landslides from 1995 to 2015. We found that
Externí odkaz:
https://doaj.org/article/9292254193464bcda0eb3ac607e57ce0
Publikováno v:
Remote Sensing, Vol 14, Iss 6, p 1503 (2022)
Urban expansion studies have focused on two-dimensional planar dimensions, ignoring the impact of building height growth changes in the vertical direction on the urban three-dimensional (3D) spatial expansion. Past 3D simulation studies have tended t
Externí odkaz:
https://doaj.org/article/d49d2786c47540c383d044192c90ac8c
Publikováno v:
Remote Sensing, Vol 11, Iss 7, p 830 (2019)
The rapid development in deep learning and computer vision has introduced new opportunities and paradigms for building extraction from remote sensing images. In this paper, we propose a novel fully convolutional network (FCN), in which a spatial resi
Externí odkaz:
https://doaj.org/article/fa0e3adb90ff463bbd23ef768dbb3a5b
Publikováno v:
SIAM Journal on Scientific Computing. 44:B996-B1017
Publikováno v:
Earth's Future. 11