Prediction of urban heat island intensity based on multiple linear regression and deep learning.

ABSTRACT: The rapid urbanization process has led to many prominent environmental issues in urban areas, resulting from a drastic change in land use. The Urban Heat Island (UHI) effect is of particular concern because it has a significant impact on the livability of cities. Therefore, exploring and studying the intensity of UHI and its future distribution have significant practical implications. In this study, the CNN-LSTM-Attention model was constructed to predict four remote sensing spectral indices, and combined with the CA-Markov model to predict land use change. The relationship between four different spectral indices and the intensity of UHI was analyzed by a multiple linear regression model (R2 = 0.7468, RMSE = 0.0546), and the UHI intensity and distribution in 2025 were predicted and analyzed

SUBMITTER: Liu X 

PROVIDER: S-EPMC12747439 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature