[HTML][HTML] Machine learning and remote sensing integration for leveraging urban sustainability: A review and framework

F Li, T Yigitcanlar, M Nepal, K Nguyen, F Dur - Sustainable Cities and …, 2023 - Elsevier
Climate change and rapid urbanisation exacerbated multiple urban issues threatening
urban sustainability. Numerous studies integrated machine learning and remote sensing to …

[HTML][HTML] Hyperlocal map** of urban air temperature using remote sensing and crowdsourced weather data

ZS Venter, O Brousse, I Esau, F Meier - Remote Sensing of Environment, 2020 - Elsevier
The impacts of climate change such as extreme heat waves are exacerbated in cities where
most of the world's population live. Quantifying urbanization impacts on ambient air …

Comparative assessment of various machine learning‐based bias correction methods for numerical weather prediction model forecasts of extreme air temperatures in …

D Cho, C Yoo, J Im, DH Cha - Earth and Space Science, 2020 - Wiley Online Library
Forecasts of maximum and minimum air temperatures are essential to mitigate the damage
of extreme weather events such as heat waves and tropical nights. The Numerical Weather …

Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images

C Yoo, D Han, J Im, B Bechtel - ISPRS Journal of Photogrammetry and …, 2019 - Elsevier
Abstract The Local Climate Zone (LCZ) scheme is a classification system providing a
standardization framework to present the characteristics of urban forms and functions …

Application of MODIS land surface temperature data: a systematic literature review and analysis

TN Phan, M Kappas - Journal of Applied Remote Sensing, 2018 - spiedigitallibrary.org
The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua
satellites, which provides a very high temporal (four times per day) and spatial (1 km) …

[HTML][HTML] A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations

S Chen, Y Yang, F Deng, Y Zhang, D Liu… - Atmospheric …, 2022 - amt.copernicus.org
Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect
has become a more concerning climatic and environmental issue. A high-spatial-resolution …

A global dataset of daily near-surface air temperature at 1-km resolution (2003–2020)

T Zhang, Y Zhou, K Zhao, Z Zhu, G Chen… - Earth System …, 2022 - essd.copernicus.org
Near-surface air temperature (Ta) is a key variable in global climate studies. A global
gridded dataset of daily maximum and minimum Ta (Tmax and Tmin) is particularly valuable …

Generating a 2-km, all-sky, hourly land surface temperature product from Advanced Baseline Imager data

A Jia, S Liang, D Wang - Remote Sensing of Environment, 2022 - Elsevier
By characterizing high-frequency surface thermal dynamics at a medium spatial scale,
hourly land surface temperatures (LST), retrieved from geostationary satellite thermal …

Long-term trends of surface and canopy layer urban heat island intensity in 272 cities in the mainland of China

R Yao, L Wang, X Huang, Y Liu, Z Niu, S Wang… - Science of the Total …, 2021 - Elsevier
The canopy layer urban heat island (CLUHI) and surface urban heat island (SUHI) refer to
higher canopy layer and land surface temperatures in urban areas than in rural areas …

A dataset of daily near-surface air temperature in China from 1979 to 2018

S Fang, K Mao, X **a, P Wang, J Shi… - Earth System …, 2021 - essd.copernicus.org
T a (Near-surface air temperature) is an important physical parameter that reflects climate
change. Although there are currently many methods to obtain the daily maximum (T max) …