G. Çiğdem ÇAVDAROĞLU, Ahmet Okan ARIK

31936

Spatial-Temporary Analysis of Istanbul Air Pollution During the Pandemic using Google Earth Engine and Google Community Mobility Reports

The Covid-19 pandemic has brought drastic changes to people's daily life and environmental characteristics. To control the pandemic, all governments have implemented particular policies for their countries and imposed restrictions that affect people's daily life. The traffic index has decreased in many countries and cities depending on the restrictions. Therefore, restrictions in many countries and cities have positively impacted air quality. However, the opposite has also been observed in metropolitan cities. In this study, the change in the air quality of Istanbul, which is accepted as Turkey's largest metropolitan city, has been examined. First, the spatio-temporal distribution of air pollutants (NO2, CO, and SO2) has been analyzed using Sentinel-5P NRTI satellite images. Then six independent variable groups (traffic index of Istanbul, daily deaths in Istanbul, Google community mobility reports of Istanbul, fuel prices, stringency index of Turkey, two logical attributes regarding the Covid-19 restrictions and in-class education) were collected and combined to analyze the correlations between these variable groups and air pollutant concentrations. According to the spatial distribution graphs, there is a tendency to decrease NO2, CO, and SO2 pollutant concentrations in Istanbul when the restrictions are applied in Turkey. There was no significant relationship between the decrease in community mobility in Istanbul and pollutant concentrations, although an increase in air quality has been observed in many cities due to the restrictions of the Covid-19 pandemic.
Anahtar Kelimeler:

Spatial, pandemic, air pollution

PDF

___

  • [1] Ghasempour F, Sekertekin A, Kutoglu S H "Google Earth Engine based spatio-temporal analysis of air pollutants before and during the first wave COVID-19 outbreak over Turkey via remote sensing". Journal of Cleaner Production, 319, 128599, 2021.
  • [2] Chen Y, Qin R, Zhang G, Albanwan H "Spatial temporal analysis of traffic patterns during the COVID-19 epidemic by vehicle detection using planet remote-sensing satellite images". Remote Sensing, 13(2), 208, 2021.
  • [3] Singh M, Singh BB, Singh R, Upendra B, Kaur R, Gill SS, Biswas MS "Quantifying COVID-19 enforced global changes in atmospheric pollutants using cloud computing based remote sensing". Remote Sensing Applications: Society and Environment, 22, 100489, 2021.
  • [4] Elshorbany YF, Kapper HC, Ziemke JR, Parr SA "The status of air quality in the United States during the COVID-19 pandemic: A remote sensing perspective". Remote Sensing, 13(3), 369, 2021.
  • [5] Bustamante-Calabria M, Sánchez de Miguel A, Martín-Ruiz S, Ortiz JL, Vílchez JM, Pelegrina A, Gaston KJ "Effects of the COVID-19 lockdown on urban light emissions: ground and satellite comparison". Remote Sensing, 13(2), 258, 2021.
  • [6] Venter ZS, Aunan K, Chowdhury S, Lelieveld J "COVID-19 lockdowns cause global air pollution declines". Proceedings of the National Academy of Sciences, 117(32), 18984-18990, 2020.
  • [7] Shen L, Zhao T, Wang H, Liu J, Bai Y, Kong S, Shu Z "Importance of meteorology in air pollution events during the city lockdown for COVID-19 in Hubei Province, Central China". Science of the Total Environment, 754, 142227, 2021.
  • [8] Faisal M, Adi Prakoso K, Sanjaya H, Rohmaneo Darminto M "Spatio-Temporal Analysis of Air Pollutants Changes During The COVID-19 Using Sentinel-5P in Google Earth Engine (Case Study: Java Island)". 2021 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS), pp. 102-108, 2021.
  • [9] Iqbal M, Prabaswara IW, Nurlita VA, Hizbaron DR "Spatiotemporal analysis using Google Earth Engine: an evaluation of Covid-19 emergency response mobility policies in Java Island, Indonesia". In Seventh Geoinformation Science Symposium 2021 (Vol. 12082, pp. 382-390). SPIE, 2021.
  • [10] Huang Y, Zhou JL, Yu Y, Mok WC, Lee CF, Yam YS "Uncertainty in the impact of the COVID-19 pandemic on air quality in Hong Kong, China". Atmosphere, 11(9), 914, 2020.
  • [11] https://www.nufusu.com/il/istanbul-nufusu, Last accessed: April 4, 2022.
  • [12] https://www.latlong.net/place/istanbul-turkey-2242.html, Last accessed: April 4, 2022.
  • [13] Annual TomTom Traffic Index: the World at the Pace of the Pandemic, https://www.tomtom.com/press-room/general/147356/annual-tomtom-traffic-index-the-world-at-the-pace-of-the-pandemic/, Last accessed: April 4, 2022.
  • [14] https://havakalitesi.ibb.gov.tr/, Last accessed: April 5, 2022.
  • [15] https://data.ibb.gov.tr/en/dataset?q=traffic+index, Last accessed: April 5, 2022.
  • [16] https://turcovid19.com/acikveri/, Last accessed: April 5, 2022.
  • [17] https://www.google.com/covid19/mobility/, Last accessed: April 5, 2022.
  • [18] https://www.opet.com.tr/akaryakit-fiyatlari-arsivi, Last accessed: April 5, 2022.
  • [19] https://www.bsg.ox.ac.uk/research/research-projects/covid-19-government-response-tracker, Last accessed: 11.04.2022.
  • [20] https://ourworldindata.org/grapher/covid-stringency-index, Last accessed: April 5, 2022.
  • [21] https://earthengine.google.com/, Last accessed: April 6, 2022.
  • [22] https://sentinels.copernicus.eu/documents/247904/1848259/Sentinel-5P_Data_Access_and_Products, Last accessed: April 6, 2022.
  • [23] https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_NO2?hl=en, Last accessed: April 5, 2022.
  • [24] https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CO?hl=en, Last accessed: April 5, 2022.
  • [25] https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_SO2?hl=en, Last accessed: April 5, 2022.
  • [26] https://github.com/cavdarkizi/Spatial-Temporary-Analysis-of-Istanbul-Air-Pollution-During-the-Pandemic-, Last accessed: April 6, 2022.
  • [27] https://www.duvarenglish.com/istanbul-experiences-traffic-jam-on-the-first-day-of-covid-19-full-lockdown-gallery-57303, Last accessed: 13.04.2022.
  • [28] Copernicus Sentinel-5P (processed by ESA), 2021, TROPOMI Level 2 Nitrogen Dioxide total column products. Version 02. European Space Agency. https://doi.org/10.5270/S5P-9bnp8q8, Last accessed: 14.04.2022.
Veri Bilimi-Cover
  • Başlangıç: 2018
  • Yayıncı: Murat GÖK
Arşiv
Sayıdaki Diğer Makaleler

Türkçe Hakaret ve Nefret Söylemi Otomatik Tespit Modeli

Mehmet Salih KURT, Eylem YÜCEL DEMİREL

Spatial-Temporary Analysis of Istanbul Air Pollution During the Pandemic using Google Earth Engine and Google Community Mobility Reports

G. Çiğdem ÇAVDAROĞLU, Ahmet Okan ARIK

Optimal küme sayısının belirlenmesinde kullanılan yöntemlerin karşılaştırılması

Fatih Emre ÖZTÜRK, Neslihan DEMİREL

Covid-19 Pandemi Sürecinde Üniversite Öğrencileri ve Akademisyenlerin Uzaktan Eğitime Yönelik Bakış Açıları Üzerine Bir Araştırma

Semra ERPOLAT TAŞABAT, Ebru OĞUZ, Gülay Ilona TELSİZ KAYAOĞLU, Mert ERSEN

Sis Kaldırma Algoritmalarına Genel Bir Bakış

Bahadır ARABALI, Kemal FİDANBOYLU