The Ventilation Efficiency of Urban Built Intensity and Ventilation Path Identification: A Case Study of Wuhan.

Urban ventilation is being hampered by rough surfaces in dense urban areas, and the microclimate and air quality of the urban built environment are not ideal. Identifying urban ventilation paths is helpful to save energy, reduce emissions, and improve the urban ecological environment. Wuhan is the capital city of Hubei, and it has a high urban built intensity and hot summers.

A cooled city? Comparing human activity changes on the impact of urban thermal environment before and after city-wide lockdown.

The outbreak of the COVID-19 epidemic in early 2020 reduced human outdoor activities and changed the spatial-temporal distribution of the population. To find its changes on the impact of urban thermal environment, we applied Pearson correlation analysis and OLS linear regression model from the perspective of urban land use and the local climate zone (LCZ) scheme, and selected Wuhan City in China as a case study. The results showed that the population size decreased in most urban land use and LCZ classes due to the Spring Festival and epidemic effects, which caused residents to leave Wuhan City.

The Diversified Impacts of Urban Morphology on Land Surface Temperature among Urban Functional Zones.

Local warming induced by rapid urbanization has been threatening residents' health, raising significant concerns among urban planners. Local climate zone (LCZ), a widely accepted approach to reclassify the urban area, which is helpful to propose planning strategies for mitigating local warming, has been well documented in recent years. Based on the LCZ framework, many scholars have carried out diversified extensions in urban zoning research in recent years, in which urban functional zone (UFZ) is a typical perspective because it directly takes into account the impacts of human activities.

How Did Distribution Patterns of Particulate Matter Air Pollution (PM and PM) Change in China during the COVID-19 Outbreak: A Spatiotemporal Investigation at Chinese City-Level.

Due to the suspension of traffic mobility and industrial activities during the COVID-19, particulate matter (PM) pollution has decreased in China. However, rarely have research studies discussed the spatiotemporal pattern of this change and related influencing factors at city-scale across the nation. In this research, the clustering patterns of the decline rates of PM and PM during the period from 20 January to 8 April in 2020, compared with the same period of 2019, were investigated using spatial autocorrelation analysis.

Coupling mobile phone data with machine learning: How misclassification errors in ambient PM2.5 exposure estimates are produced?

Background: Most studies relying on time-activity diary or traditional air pollution modelling approach are insufficient to suggest the impacts of ignoring individual mobility and air pollution variations on misclassification errors in exposure estimates. Moreover, very few studies have examined whether such impacts differ across socioeconomic groups.

Objectives: We aim to examine how ignoring individual mobility and PM2.

Spatiotemporal Variations of Particulate and Gaseous Pollutants and Their Relations to Meteorological Parameters: The Case of Xiangyang, China.

High air pollution levels have become a nationwide problem in China, but limited attention has been paid to prefecture-level cities. Furthermore, different time resolutions between air pollutant level data and meteorological parameters used in many previous studies can lead to biased results. Supported by synchronous measurements of air pollutants and meteorological parameters, including PM, PM, total suspended particles (TSP), CO, NO, O, SO, temperature, relative humidity, wind speed and direction, at 16 urban sites in Xiangyang, China, from 1 March 2018 to 28 February 2019, this paper: (1) analyzes the overall air quality using an air quality index (AQI); (2) captures spatial dynamics of air pollutants with pollution point source data; (3) characterizes pollution variations at seasonal, day-of-week and diurnal timescales; (4) detects weekend effects and holiday (Chinese New Year and National Day holidays) effects from a statistical point of view; (5) establishes relationships between air pollutants and meteorological parameters.

How Do the Multi-Temporal Centroid Trajectories of Urban Heat Island Correspond to Impervious Surface Changes: A Case Study in Wuhan, China.

Conspicuous expansion and intensification of impervious surfaces accompanied by rapid urbanization are widely recognized to have exerted evident impacts on the urban thermal environment. Investigating the spatially and temporally varying relationships between Land Surface Temperature (LST) and impervious surfaces (IS) at multiple scales is of great significance for steering IS expansion and intensification. This study proposes an analytical framework to investigate the spatiotemporal variations of LST and its responses to IS in Wuhan, China at both city scale and sub-region scale.

How to quantify the relationship between spatial distribution of urban waterbodies and land surface temperature?

Urban waterbodies can effectively mitigate the increasing UHI effects and thus enhance climate resilience of urban areas. To contribute to our limited understanding in cooling effect of waterbodies on surrounding thermal environments, we examine the quantitative relationship between the spatial distribution of urban waterbodies and the land surface temperature (LST) in Wuhan, China. This paper 1) applies two indicators, the fractional water cover and the gravity water index, for measuring the spatial distribution of urban waterbodies; 2) conducts simple linear regression and spatial regression analyses to explore the LST-water relationship at multiple scales; and 3) compares the individual regression results from different land use types.

An IHS-Based Pan-Sharpening Method for Spectral Fidelity Improvement Using Ripplet Transform and Compressed Sensing.

Pan-sharpening aims at integrating spectral information from a multi-spectral (MS) image and spatial information from a panchromatic (PAN) image in a fused image with both high spectral and spatial resolutions. Numerous pan-sharpening methods are based on intensity-hue-saturation (IHS) transform, which may cause evident spectral distortion. To address this problem, an IHS-based pan-sharpening method using ripplet transform and compressed sensing is proposed.

The multi-timescale temporal patterns and dynamics of land surface temperature using Ensemble Empirical Mode Decomposition.

Temporal variation patterns of Land Surface Temperature (LST) under different time scales are crucial in understanding the response of urban thermal environment to different forcings. However, there is no integrated toolset to extract such patterns from satellite remotely sensed time series LST (TSLST) data. This paper presents a workflow to extract the multi-timescale temporal patterns and dynamics from nonlinear and non-stationary TSLST data by taking Wuhan, China as case study.