Network analysis: a novel approach to identify PM2.5 hotspots and their spatio-temporal impact on air quality in Santiago de Chile

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

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Detecting Tourism Typologies of Regional Destinations Based on Their Spatio-Temporal and Socioeconomic Performance: A Correlation-Based Complex Network Approach for the Case of Greece

Tourism and Hospitality ◽

10.3390/tourhosp2010007 ◽

2021 ◽

Vol 2 (1) ◽

pp. 113-139

Author(s):

Dimitrios Tsiotas ◽

Thomas Krabokoukis ◽

Serafeim Polyzos

Keyword(s):

Network Analysis ◽

Complex Network ◽

Community Detection ◽

Optimization Algorithm ◽

Spatial Dimension ◽

Economic Dimension ◽

Complex Network Analysis ◽

Time Period ◽

Time Patterns ◽

Spatio Temporal

Within the context that tourism-seasonality is a composite phenomenon described by temporal, geographical, and socio-economic aspects, this article develops a multilevel method for studying time patterns of tourism-seasonality in conjunction with its spatial dimension and socio-economic dimension. The study aims to classify the temporal patterns of seasonality into regional groups and to configure distinguishable seasonal profiles facilitating tourism policy and development. The study applies a multilevel pattern recognition approach incorporating time-series assessment, correlation, and complex network analysis based on community detection with the use of the modularity optimization algorithm, on data of overnight-stays recorded for the time-period 1998–2018. The analysis reveals four groups of seasonality, which are described by distinct seasonal, geographical, and socio-economic profiles. Overall, the analysis supports multidisciplinary and synthetic research in the modeling of tourism research and promotes complex network analysis in the study of socio-economic systems, by providing insights into the physical conceptualization that the community detection based on the modularity optimization algorithm can enjoy to the real-world applications.

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VIDEO-SHOT TRANSITION DETECTION: A SPATIO-TEMPORAL SALIENCY APPROACH

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001410008366 ◽

2010 ◽

Vol 24 (08) ◽

pp. 1295-1309 ◽

Cited By ~ 1

Author(s):

XIAN WU ◽

JIANHUANG LAI ◽

PONG C. YUEN

Keyword(s):

Error Probability ◽

Spatial Information ◽

Saliency Map ◽

Detection Error ◽

Novel Approach ◽

Video Shot ◽

Recent Method ◽

Temporal And Spatial ◽

Spatio Temporal ◽

Shot Transitions

This paper proposes a novel approach for video-shot transition detection using spatio-temporal saliency. Both temporal and spatial information are combined to generate a saliency map, and features are available based on the change of saliency. Considering the context of shot changes, a statistical detector is constructed to determine all types of shot transitions by the minimization of the detection-error probability simultaneously under the same framework. The evaluation performed on videos of various content types demonstrates that the proposed approach outperforms a more recent method and two publicly available systems, namely VideoAnnex and VCM.

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A recursive estimation approach to the spatio-temporal analysis and modelling of air quality data

Environmental Modelling & Software ◽

10.1016/j.envsoft.2005.02.004 ◽

2006 ◽

Vol 21 (6) ◽

pp. 759-769 ◽

Cited By ~ 17

Author(s):

R. Romanowicz ◽

P. Young ◽

P. Brown ◽

P. Diggle

Keyword(s):

Air Quality ◽

Temporal Analysis ◽

Recursive Estimation ◽

Quality Data ◽

Spatio Temporal ◽

Air Quality Data

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A Novel Approach for Air Quality Inference and Prediction Based on DBU-LSTM

Web and Big Data - Lecture Notes in Computer Science ◽

10.1007/978-3-030-26072-9_12 ◽

2019 ◽

pp. 171-186

Author(s):

Liang Ge ◽

Aoli Zhou ◽

Junling Liu ◽

Hang Li

Keyword(s):

Air Quality ◽

Novel Approach

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Airborne observation during KORUS-AQ show aerosol optical depth are more spatially self-consistent than aerosol intensive properties

10.5194/acp-2021-1012 ◽

2022 ◽

Author(s):

Samuel E. LeBlanc ◽

Michal Segal-Rozenhaimer ◽

Jens Redemann ◽

Connor J. Flynn ◽

Roy R. Johnson ◽

...

Keyword(s):

Air Quality ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Temporal Variability ◽

Spatial Scales ◽

Aerosol Emission ◽

Fine Mode ◽

Predominant Factor ◽

Spatio Temporal ◽

Microphysical Processes

Abstract. Aerosol particles can be emitted, transported, removed, or transformed, leading to aerosol variability at scales impacting the climate (days to years and over hundreds of kilometers) or the air quality (hours to days and from meters to hundreds of kilometers). We present the temporal and spatial scales of changes in AOD (Aerosol Optical Depth), and aerosol size (using Angstrom Exponent; AE, and Fine-Mode-Fraction; FMF) over Korea during the 2016 KORUS-AQ (KORea-US Air Quality) atmospheric experiment. We use measurements and retrievals of aerosol optical properties from airborne instruments for remote sensing (4STAR; Spectrometers for Sky-Scanning Sun Tracking Atmospheric Research) and in situ (LARGE; NASA Langley Aerosol Research Group Experiment) on board the NASA DC-8, geostationary satellite (GOCI; Geostationary Ocean Color Imager; Yonsei aerosol retrieval (YAER) version 2) and reanalysis (MERRA-2; Modern-Era Retrospective Analysis for Research and Applications, version 2). Measurements from 4STAR when flying below 500 m, show an average AOD at 501 nm of 0.43 and an average AE of 1.15 with large standard deviation (0.32 and 0.26 for AOD and AE respectively) likely due to mixing of different aerosol types (fine and coarse mode). The majority of AODs due to fine mode aerosol is observed at altitudes lower than 2 km. Even though there are large variations, for 18 out of the 20 flight days, the column AOD measurements by 4STAR along the NASA DC-8 flight trajectories matches the south-Korean regional average derived from GOCI. We also observed that, contrary to prevalent understanding, AE and FMF are more spatially variable than AOD during KORUS-AQ, even when accounting for potential sampling biases by using Monte Carlo resampling. Averaging between measurements and model for the entire KORUS-AQ period, a reduction in correlation by 15 % is 65.0 km for AOD and shorter at 22.7 km for AE. While there are observational and model differences, the predominant factor influencing spatial-temporal homogeneity is the meteorological period. High spatio-temporal variability occur during the dynamic period (25–31 May), and low spatio-temporal variability occur during blocking Rex pattern (01–07 June). The changes in spatial variability scales between AOD and FMF/AE, while inter-related, indicate that microphysical processes that impact mostly the dominant aerosol size, like aerosol particle formation, growth, and coagulation, vary at shorter scales than the aerosol concentration processes that mostly impact AOD, like aerosol emission, transport, and removal.

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Spatio-temporal of surface ozone (O3) variations at urban and suburban sites in Sarawak region of Malaysia

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/880/1/012004 ◽

2021 ◽

Vol 880 (1) ◽

pp. 012004

Author(s):

H Mahidin ◽

M T Latif ◽

A Hamdan ◽

J Salleh ◽

D Dominick ◽

...

Keyword(s):

Air Quality ◽

Surface Ozone ◽

Ambient Air ◽

Quality Standard ◽

Transportation Systems ◽

Pollutant Emissions ◽

Daily Maximum ◽

Spatio Temporal ◽

Ambient Air Quality Standard ◽

The Relationship

Abstract Sarawak Region of Malaysia is currently experiencing a high demand for capital needs such as transformation forest to plantations, economic development, and improving transportation systems. Those land cover changes will increase primary pollutant emissions and trigger surface O3 formation. Surface O3 is a secondary pollutant and a significant greenhouse gas contributing to climate change and declining air quality. In this study, variations in surface O3 concentrations at urban and suburban sites in Sarawak were explored using the Malaysian Department of Environment data spanning a two-year cycle (2018-2019). The primary aim of this study is to ascertain the variation of surface O3 concentrations reported at four monitoring stations in Sarawak, namely Kuching (SQ1) (Urban), Sibu (SQ2) (Suburban), Bintulu (SQ3) (Suburban), and Miri (SQ4) (Suburban). The study also analysed the relationship between O3 distribution and nitrogen oxides (NO and NO2). The findings showed that O3 concentrations observed in the region during the study period were lower than the maximum permissible value of 100 ppbv suggested by the Malaysian Ambient Air Quality Standard (2020). SQ4 (Miri) at suburban sites recorded the highest average surface O3 concentrations with an hourly average and daily maximum O3 concentration of 15.7 and 89.5 ppbv, respectively. Temperatures, UV exposure, and wind speed all impact the concentration of surface O3 in Sarawak. In all stations, concentrations of O3 were inversely linked with NO, NO2, and relative humidity (RH). This research will assist the relevant agency in forecast, monitor, and mitigate the level of O3 in the ambient environment, especially in the Sarawak Region.

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Dynamic Network Analysis of Spatio- Temporal Crime Incidents in Bogotá - Colombia

10.1109/besc53957.2021.9635287 ◽

2021 ◽

Author(s):

Juan Moreno ◽

Hernan Garcaa ◽

Sebastian Quintero ◽

Johan Garcia ◽

Alvaro Riascos ◽

...

Keyword(s):

Network Analysis ◽

Dynamic Network ◽

Dynamic Network Analysis ◽

Spatio Temporal

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