Urban morphology and climate vulnerability assessment in Kuwait: A spatio-temporal predictive analysis utilizing deep neural network-enhanced markov chain models for 2050 and 2100.

ABSTRACT: Rapid urban growth in Kuwait creates challenges for adapting to climate change. This study investigates the spatio-temporal dynamics of urban growth in Kuwait and assesses its climate change vulnerability using a Multi-Layer Perceptron Markov Chain Model (MLPMCM) to forecast land use and land cover (LULC) changes for the years 2050 and 2100. Utilizing historical LULC data from 1985, 2005, and 2022, along with various spatial drivers, the research predicts urban expansion patterns for 2050 and 2100. The model achieved high accuracy in predictions, indicating that proximity to coastlines, road networks, and commercial areas are the primary drivers of urban growth in Kuwait. The study projects significant urban expansion, particularly in North-Northwestern and South-Southwestern regions, with

SUBMITTER: Al-Shaar W 

PROVIDER: S-EPMC12360559 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature