Urbanization is persistent globally and has increasingly significant spatial and
environmental consequences. It is especially challenging in developing countries due to the …

Accurate land use and land cover (LULC) is crucial for sustainable urban planning and for
many scientific researches. However, the demand for accurate LULC maps is increasing; it …

The challenges for sustainable cities to protect the environment, ensure economic growth,
and maintain social justice have been widely recognized. Along with the digitization …

Modern cities dynamically face several challenges including digitalization, sustainability,
resilience and economic development. Urban planners and designers must develop urban …

Because deep learning has various downsides, such as complexity, expense, and the need
to wait longer for results, this creates a significant incentive and impetus to invent and adopt …

With the recent advances in earth observation technologies, the increasing availability of
data from more and more different satellite sensors as well as progress in semi-automated …

Land value plays a vital role in the real estate market. It is a critical reference for urban
planners to reallocate land resources and introduce valid policies. Studying the influential …

This paper compares six land use change (LUC) models, including artificial neural networks
(ANNs), support vector regression (SVR), random forest (RF), classification and regression …

With the rapid expansion of cities, monitoring urban sprawl is recognized as a vital tool by
many researchers who use this information in several applications like urban planning …

Land use/land cover (LULC) changes can occur naturally or due to human activities. In this
study, the maximum likelihood algorithm (MLH) and machine learning (random forest …