[HTML][HTML] Deep learning in remote sensing applications: A meta-analysis and review
Deep learning (DL) algorithms have seen a massive rise in popularity for remote-sensing
image analysis over the past few years. In this study, the major DL concepts pertinent to …
image analysis over the past few years. In this study, the major DL concepts pertinent to …
On the opportunities and challenges of foundation models for geospatial artificial intelligence
Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method
Urban growth boundaries (UGBs) have been commonly regarded as a useful tool for
controlling urban sprawl. There is a need to create models that can establish plausible …
controlling urban sprawl. There is a need to create models that can establish plausible …
[HTML][HTML] Machine learning for spatial analyses in urban areas: a sco** review
The challenges for sustainable cities to protect the environment, ensure economic growth,
and maintain social justice have been widely recognized. Along with the digitization …
and maintain social justice have been widely recognized. Along with the digitization …
Extracting urban functional regions from points of interest and human activities on location‐based social networks
Data about points of interest (POI) have been widely used in studying urban land use types
and for sensing human behavior. However, it is difficult to quantify the correct mix or the …
and for sensing human behavior. However, it is difficult to quantify the correct mix or the …
A human-machine adversarial scoring framework for urban perception assessment using street-view images
Though global-coverage urban perception datasets have been recently created using
machine learning, their efficacy in accurately assessing local urban perceptions for other …
machine learning, their efficacy in accurately assessing local urban perceptions for other …
Urban growth simulation by incorporating planning policies into a CA-based future land-use simulation model
Urban land-use change is affected by urban planning and government decision-making.
Previous urban simulation methods focused only on planning constraints that prevent urban …
Previous urban simulation methods focused only on planning constraints that prevent urban …
Urban function classification at road segment level using taxi trajectory data: A graph convolutional neural network approach
Extracting hidden information from human mobility patterns is one of the long-standing
challenges of urban studies. In addition, exploring the relationship between urban functional …
challenges of urban studies. In addition, exploring the relationship between urban functional …