The goal of managing smart cities and societies is to maximize the efficient use of finite
resources while enhancing the quality of life. To establish a sustainable urban existence …

In the dynamic landscape of sustainable smart cities, emerging computational technologies
and models are reshaping data-driven planning strategies, practices, and approaches …

In the mass appraisal of properties, Machine Learning (ML) algorithms have produced
effective and promising results. Analysts use various algorithms to train their models with …

Traditional methods of land resource management are no longer adequate to address the
rapidly changing environmental and societal demands. By introducing data-driven …

The urban planning profession is increasingly challenged to analyze extensive text data,
from plans to public feedback. While natural language processing (NLP) has promising …

The spatial layout of the “Production–Living–Ecological”(PLE) function and the spatial
optimization of the “Urban–Agricultural–Ecological”(UAE) pattern are the key points and …

Optimization of the territorial spatial patterns can promote the functional balance and
utilization efficiency of space, which is influenced by economic, social, ecological, and …

Information on historical flood levels can be communicated verbally, in documents, or in the
form of flood marks. The latter are the most useful from the point of view of public awareness …

Due to the complexity of planning processes, as well as the desire to satisfy stakeholders
and entities involved in spatial development and planning procedures, there is a clear need …

The classification of land use information is important for land resource management. With
the purpose of extracting precise spatial information, we present a novel land use …