Cited by Explainable artificial intelligence models for proposing mitigation strategies to combat urbanization impact on land surface temperature dynamics in Saudi Arabia

Impact of seasonal global land surface temperature (LST) change on gross primary production (GPP) in the early 21st century DOI

Ao Wang, Maomao Zhang, Enqing Chen

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 110, P. 105572 - 105572

Published: June 3, 2024

Language: Английский

Citations

Multi-Scenario Simulation of Land Use Change and Ecosystem Service Value Based on the Markov–FLUS Model in Ezhou City, China DOI

Maomao Zhang, Enqing Chen, Cheng Zhang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(14), P. 6237 - 6237

Published: July 22, 2024

Changes in land use patterns, types, and intensities significantly impact ecosystem services. This study follows the time series logic from history to expected future investigate spatial temporal characteristics of changes Ezhou their potential impacts on services value (ESV). The results show that Markov–FLUS model has strong applicability predicting pattern use, with a Kappa coefficient 0.9433 FoM 0.1080. Between 2000 2020, construction expanded continuously, while water area remained relatively stable, other types experienced varying degrees contraction. Notably, compared 2000, it by 70.99% 2020. Moreover, watershed 9.30% 2010, but there was very little change following 10 years. Under three scenarios, significant differences were observed City, driven human activities, particularly expansion land. In inertial development scenario, 313.39 km2 2030, representing 38.30% increase Conversely, under farmland protection increased 237.66 km2, 4.89% rise However, ecological priority 253.59 10.13% Compared ESV losses inertia scenarios USD 4497.71 1072.23, respectively, 2030. scenario 2749.09, emphasizing importance prioritizing City’s development. may provide new clues for formulation regional strategies sustainable restoration.

Language: Английский

Citations

Tracking the Impact of the Land Cover Change on the Spatial-Temporal Distribution of the Thermal Comfort: Insights from the Qinhuai River Basin, China DOI

Chunguang Hu, Maomao Zhang, Gaoliu Huang

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: unknown, P. 105916 - 105916

Published: Oct. 1, 2024

Language: Английский

Citations

Impact of Urban Surfaces on Microclimatic Conditions and Thermal Comfort in Burdur, Türkiye DOI

Maomao Zhang, İlker Yiğit, Fatih Adıgüzel

et al.

Atmosphere, Journal Year: 2024, Volume and Issue: 15(11), P. 1375 - 1375

Published: Nov. 14, 2024

Rapid urbanization worldwide offers numerous benefits but also introduces challenges, particularly concerning urban climate comfort, which affects the physical and social well-being in cities. This study examined microclimatic characteristics of Burç neighborhood historical core Burdur city, using ENVI-Met models with temperature, relative humidity, wind PET data collected over a 33,665 m2 area at 06:00, 09:00, 12:00, 15:00, 18:00 21:00 on 15 August 2023. The analysis revealed that thermal comfort decreases significantly from 09:00 onwards, especially hard surfaces like asphalt, concrete parquet, lack vegetation intensify heat retention. By contrast, green areas were found to enhance bioclimatic by reducing perceived temperatures up 20% shaded vegetated zones. Based these findings, it is recommended reduce heat-absorbing materials, such as asphalt prioritize spaces landscape planning improve create more sustainable environments.

Language: Английский

Citations

Spatiotemporal Dynamics and Response of Land Surface Temperature and Kernel Normalized Difference Vegetation Index in Yangtze River Economic Belt, China: Multi-Method Analysis DOI

Hongjia Zhu,

Ao Wang, Pengtao Wang

et al.

Land, Journal Year: 2025, Volume and Issue: 14(3), P. 598 - 598

Published: March 12, 2025

As global climate change intensifies, its impact on the ecological environment is becoming increasingly pronounced. Among these, land surface temperature (LST) and vegetation cover status, as key indicators, have garnered widespread attention. This study analyzes spatiotemporal dynamics of LST Kernel Normalized Difference Vegetation Index (KNDVI) in 11 provinces along Yangtze River their response to based MODIS Terra satellite data from 2000 2020. The linear regression showed a significant KNDVI increase 0.003/year (p < 0.05) rise 0.065 °C/year 0.01). Principal Component Analysis (PCA) explained 74.5% variance, highlighting dominant influence urbanization. K-means clustering identified three regional patterns, with Shanghai forming distinct group due low variability. Generalized Additive Model (GAM) analysis revealed nonlinear LST–KNDVI relationship, most evident Hunan, where cooling effects weakened beyond threshold 0.25. Despite 0.07 increase, high-temperature areas Chongqing Jiangsu expanded by over 2500 km2, indicating limited mitigation. reveals complex interaction between KNDVI, which may provide scientific basis for development management adaptation strategies.

Language: Английский

Citations

Long-term tracking of urban structure and analysis of its impact on urban heat stress: a case study of Xi’an, China DOI

Kaipeng Huo,

Rui Qin, Jingyuan Zhao

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 174, P. 113418 - 113418

Published: April 9, 2025

Language: Английский

Citations

Improving Landslide Susceptibility Prediction in Uttarakhand through Hyper-Tuned Artificial Intelligence and Global Sensitivity Analysis DOI

Mohd Rihan, Swapan Talukdar, Mohd Waseem Naikoo

et al.

Earth Systems and Environment, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 23, 2024

Language: Английский

Citations

Impact of Sea Surface Temperature on City Temperature near Warm and Cold Ocean Currents in Summer Season for Northern Hemisphere DOI

Muhammad Farhan Ul Moazzam,

Byung Gul Lee,

Sanghyun Kim

et al.

Atmosphere, Journal Year: 2025, Volume and Issue: 16(1), P. 54 - 54

Published: Jan. 7, 2025

This study examined the impact of sea surface temperature (SST) on urban across four cities located in three different countries (United States America, Japan, and Morocco), all at nearly same latitude, focusing summer season over period from 2003 to 2020, because previously no one attempted analyze SST land (LST). Data were acquired Moderate Resolution Imaging Spectroradiometer (MODIS) for LST evaluate correlation between SST, trends time, relationship areas LST. The novelty this lies its being first investigate based a city’s proximity warm cold ocean currents. findings revealed positive analyzed (San Francisco, Tangier, Tokyo, Atlantic City), some instances significant was observed 95% confidence level, but still significance is range weak moderate. Specifically, found that during both daytime nighttime, Tangier exhibited decreasing trend (99% level) SST. On contrary, San Francisco displayed an increasing daytime, while continued rise, showed trend. Further analysis differentiated influenced by currents (Tokyo City) those affected Tangier). In current, there despite increased Conversely, City, also currents, daytime. At Tokyo City Additionally, explored LST, finding contrast, Tangier) negative Overall, research highlights complex interplay temperatures, demonstrating how urbanization can influence differently similar latitudes.

Language: Английский

Citations

Impact of urban land use and anthropogenic heat on winter and summer outdoor thermal comfort in Beijing DOI

Jiangkang Qian, Linlin Zhang, Uwe Schlink

et al.

Urban Climate, Journal Year: 2025, Volume and Issue: 59, P. 102306 - 102306

Published: Jan. 24, 2025

Language: Английский

Citations

High-resolution maximum air temperature estimation over India from MODIS data using machine learning DOI

Amal Joy,

K. Satheesan,

Avinash Paul

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 101463 - 101463

Published: Jan. 1, 2025

Language: Английский

Citations