Impact of Urbanization on Regional Rainfall-Runoff Processes: Case Study in Jinan City, China

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(9), P. 2383 - 2383

Published: May 1, 2023

Rapid urbanization has altered the regional hydrological processes, posing a great challenge to sustainable development of cities. The TVGM-USWM model, new urban model considering nonlinear rainfall-runoff relationship and flow routing in an drainage system, was developed this study. We employed Huangtaiqiao basin Jinan City, China, examined impact land cover changes due on processes. Two scenarios were set up during design rainfall events with different return periods. Results showed that (1) demonstrated good applicability study area, RNS values flood are all greater than 0.75 both calibration validation periods; (2) proportion impervious areas increased from 44.65% 1990 71.00% 2020, played leading role process change manifested itself as circular extensional expansion; (3) significant amplifying effect particularly for relatively big floods small frequency, time-to-peak gradually decreased frequency decreased. results can provide technical support mitigation construction sponge city City.

Language: Английский

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The Influence of Visual Landscapes on Road Traffic Safety: An Assessment Using Remote Sensing and Deep Learning

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(18), P. 4437 - 4437

Published: Sept. 9, 2023

Rapid global economic development, population growth, and increased motorization have resulted in significant issues urban traffic safety. This study explores the intrinsic connections between road environments driving safety by integrating multiple visual landscape elements. High-resolution remote sensing street-view images were used as primary data sources to obtain features of an expressway. Deep learning semantic segmentation was employed calculate features, a trend surface fitting model driver fatigue established based on experimental from 30 drivers who completed tasks random order. There spatial variations expressway city center periphery. Heart rate values fluctuated within range 0.2% with every 10% change speed complexity. Specifically, complexity changed 5.28 8.30, heart 91 96. suggests that higher degree richness effectively mitigates increases exerts positive impact provides reference for quantitative assessment research combines using sources. It may guide implementation measures during planning construction.

Language: Английский

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Reconstructing MODIS aerosol optical depth and exploring dynamic and influential factors of AOD via random forest at the global scale

Atmospheric Environment, Journal Year: 2023, Volume and Issue: 315, P. 120159 - 120159

Published: Oct. 18, 2023

Language: Английский

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Long-term variations of air pollutants and public exposure in China during 2000–2020

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 930, P. 172606 - 172606

Published: April 18, 2024

Language: Английский

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A study on identifying synergistic prevention and control regions for PM2.5 and O3 and exploring their spatiotemporal dynamic in China

Environmental Pollution, Journal Year: 2023, Volume and Issue: 341, P. 122880 - 122880

Published: Nov. 7, 2023

Language: Английский

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A novel design and application of spatial data management platform for natural resources

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 411, P. 137183 - 137183

Published: April 26, 2023

Language: Английский

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First estimation of hourly full-coverage ground-level ozone from Fengyun-4A satellite using machine learning

Environmental Research Letters, Journal Year: 2024, Volume and Issue: 19(2), P. 024040 - 024040

Published: Jan. 18, 2024

Abstract Ground-level ozone (O 3 ), renowned for its adverse impacts on human health and crop production, has garnered significant attention from governmental public sectors. To address the limitations posed by sparse uneven ground-level O observations, this study proposes an innovative method hourly full-coverage estimation using machine learning. Meteorological data National Centers Environmental Prediction global forecasting system, satellite Fengyun-4 A(FY-4 A) Ozone Monitoring Instrument, emission inventory Multi-resolution Emission Inventory China, other auxiliary are utilized as input variables, while ground-based observations serve response variable. The is applied a monthly basis across China year 2022, resulting in generation of high-resolution (4 km) estimation, termed ML-derived-O . Cross-validation results demonstrate robustness yielding coefficient determination ( R 2 ) 0.96 (0.91) sample-based (site-based) evaluations root-mean-square error (RMSE) 9.22 (13.65) µ g m −3 However, date-based evaluation less satisfactory due to imbalanced training data, pronounced daily variations concentrations. Nevertheless, seasonal exhibits high prediction accuracy, with values surpassing 0.95 RMSE remaining below 7.5 This marks milestone first successful attempt obtain China. diurnal variation demonstrates consistency irrespective clear or cloudy days, effectively capturing pollution exposure events. novel will be employed establish long-term spatial-temporal resolution dataset, which holds valuable applications air monitoring environmental research future endeavors.

Language: Английский

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A novel quantity assessment of landscape ecological risk using human-nature driving mechanism for sustainable society

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 947, P. 173892 - 173892

Published: June 13, 2024

Language: Английский

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Unraveling the Influence of Satellite-Observed Land Surface Temperature on High-Resolution Mapping of Ground-Level Ozone Using Interpretable Machine Learning

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: 58(36), P. 15938 - 15948

Published: Aug. 28, 2024

Accurately mapping ground-level ozone concentrations at high spatiotemporal resolution (daily, 1 km) is essential for evaluating human exposure and conducting public health assessments. This requires identifying understanding a proxy that well-correlated with variation available high-resolution data. study introduces modeling method utilizing the XGBoost algorithm satellite-derived land surface temperature (LST) as primary predictor. Focusing on China in 2019, our model achieved cross-validation

Language: Английский

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The Influence of Meteorological Conditions and Seasons on Surface Ozone in Chonburi, Thailand

Toxics, Journal Year: 2025, Volume and Issue: 13(3), P. 226 - 226

Published: March 19, 2025

This study aims to examine the relationship between meteorological factors, specifically temperature, solar radiation, and ozone concentration levels. Levels of surface were monitored (O3) in Chonburi, Thailand (located at 3.2017° N, 101.2524° E), from January 2010 December 2020. Thailand’s coastal tropical environment provided a unique setting for study. The revealed distinctive seasonal trend levels, with highest concentrations occurring during winter lowest rainy season, on average. increase O3 summer was primarily attributed intense ground-level radiation higher temperatures around 30–35 °C, enhancing ranging 200 1400. During winter, there is an increased elimination by levels NO2. also examined various factors identify which had most significant impact formation. analysis showed that has strong negative correlation relative humidity but positively correlated wind speed.

Language: Английский

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