Urban Climate, Journal Year: 2024, Volume and Issue: 55, P. 101971 - 101971
Published: May 1, 2024
Language: Английский
Urban Climate, Journal Year: 2024, Volume and Issue: 55, P. 101971 - 101971
Published: May 1, 2024
Language: Английский
Environmental Research, Journal Year: 2020, Volume and Issue: 193, P. 110584 - 110584
Published: Dec. 4, 2020
Language: Английский
Citations
329Sustainable Cities and Society, Journal Year: 2021, Volume and Issue: 69, P. 102818 - 102818
Published: March 1, 2021
Language: Английский
Citations
232Sustainable Cities and Society, Journal Year: 2022, Volume and Issue: 89, P. 104374 - 104374
Published: Dec. 24, 2022
Language: Английский
Citations
144Journal of Cleaner Production, Journal Year: 2022, Volume and Issue: 340, P. 130744 - 130744
Published: Feb. 3, 2022
Language: Английский
Citations
136Journal of Cleaner Production, Journal Year: 2021, Volume and Issue: 310, P. 127467 - 127467
Published: May 19, 2021
Language: Английский
Citations
129Sustainable Cities and Society, Journal Year: 2022, Volume and Issue: 79, P. 103722 - 103722
Published: Jan. 29, 2022
Language: Английский
Citations
99Landscape and Urban Planning, Journal Year: 2023, Volume and Issue: 239, P. 104842 - 104842
Published: July 26, 2023
Language: Английский
Citations
58Urban Climate, Journal Year: 2024, Volume and Issue: 53, P. 101830 - 101830
Published: Jan. 1, 2024
Language: Английский
Citations
24ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2024, Volume and Issue: 210, P. 69 - 79
Published: March 12, 2024
Language: Английский
Citations
19IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Journal Year: 2024, Volume and Issue: 17, P. 4109 - 4124
Published: Jan. 1, 2024
The escalation of greenhouse gas emissions has led to a continuous rise in land surface temperature (LST). Studies have highlighted the substantial influence urban morphology on LST; however, impact different dimensional indicators and their gradient effects remain unexplored. Selecting area Shenyang as case, we chose various representing dimensions. By employing XGBoost for regression analysis, aimed explore 2D 3D seasonal LST its effect. following results were obtained: (1) spatial pattern spring winter was higher suburbs than center. (2) correlation patterns similar, except proportion woodland grass (PWG), digital elevation model (DEM), sky view factor (SVF), which exhibited opposing trends summer autumn. (3) Vegetation construction had highest index, followed by building forms natural landscapes morphology. (4) each indicator varied significantly across gradients. Among all indicators, landscape social development, forms, skyscape impacts areas. built-up areas greater suburban findings this study can assist adjusting provide valuable recommendations targeted improvements thermal environments, thereby contributing sustainable development.
Language: Английский
Citations
17