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Generation of PM10 Map with Sentinel-2 Satellite Images: The Case of Çankırı Province

Yıl 2024, Cilt: 24 Sayı: 2, 350 - 359, 29.04.2024
https://doi.org/10.35414/akufemubid.1372761

Öz

Air pollution, which is characterized as a global environmental problem, negatively affects life in Turkey as a result of the increase in the amount of energy needed and uncontrolled construction. In order to minimize the health impacts of air pollution, air quality should be monitored regularly and necessary steps should be taken to improve it. With the innovations in satellite technologies, the air quality of large areas can be monitored with the help of satellite images and effective solutions can be produced in many areas such as the detection of air pollutant parameters and the creation of thematic maps. The main objective of the research is to investigate the relationship between in-situ measured PM10 parameters and Sentinel-2 satellite data and to map PM10 based on this relationship. In this context, PM10 parameters measured in the field on two different dates and Sentinel-2 satellite images dated 22.11.2021 and 16.04.2022 were used as data sources. The relationship between the data used was established by multiple regression analysis. The coefficients obtained from the analysis results were applied to the relevant bands and thematic maps were created using satellite images. The correlation coefficients of 0.80 and 0.79 calculated by regression analyses indicate that sufficient accuracy was achieved in the research. The results of the study show that satellite imagery provides accurate data for PM10 estimate and that pollution exceeds World Health Organization limits in the road transportation network and industrial areas.

Kaynakça

  • Anderson, J.O., Thundiyil, J.G., Stolbach, A., 2012. Clearing the air: a review of the effects of particulate matter air pollution on human health. Journal of medical toxicology: official journal of the American College of Medical Toxicology, 8(2), 166–175. https://doi.org/10.1007/s13181-011-0203-1
  • Chen, C.W., Tseng, Y.S., Mukundan, A., Wang, H.C., 2021. Air pollution: Sensitive Detection of PM2.5 and PM10 Concentration Using Hyperspectral Imaging, Applied Sciences, 11. https://doi.org/10.3390/app11104543
  • Cohen, A.J., Anderson, H.R., Ostro, B., Pandey, K.D., Krzyzanowski, M., Künzli N., Gutschmidt, K., Pope, A., Romieu, I., Samet, J.M., Smith, K., 2005. Comparative Quantification of Health Risks, Global and Regional Burden of Disease Attributable to Selected Major Risk Factors, Urban Air pollution, Journal of Toxicology and Environmental Health, 433–1354.
  • De Donno, A., De Giorgi, M., Bagordo, F., Grassi, T., Idolo, A., Serio, F., Ceretti, E., Feretti, D., Villarini, M., Moretti, M., Carducci, A., Verani, M., Bonetta, S., Pignata, C., Bonizzoni, S., Bonetti, A., Gelatti, U., MAPEC_LIFE Study Group., 2018. Health Risk Associated with Exposure to PM10 and Benzene in Three Italian Towns. International journal of environmental research and public health, 15(8), 1672. https://doi.org/10.3390/ijerph15081672
  • Ghasempour, F., Aliihsan Şekertekin, A., Kutoğlu, Ş.H., 2021. 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. https://doi.org/10.1016/j.jclepro.2021.128599.
  • Harbula, J., 2010. Dependence of PM10 Particles Concentration on Aerosol Optical Thickness Value from the MODIS Data.
  • Hime, N., Marks, G., Cowie, C., 2018. A Comparison of the Health Effects of Ambient Particulate Matter Air Pollution from Five Emission Sources. International Journal of Environmental Research and Public Health, 15, 1206. https://doi.org/10.3390/ijerph15061206
  • İnal, C., Turgut, B., Yiğit, C.Ö., 2002. Lokal Alanlarda Jeoit Ondülasyonlarının Belirlenmesinde Kullanılan Enterpolasyon Yöntemlerinin Karşılaştırılması (Comparison of Interpolation Methods Uset to Determine Geoid Corrugations in Local Areas), Selçuk Üniversitesi Jeodezi ve Fotogrametri Mühendisliği Öğretiminde 30. Yıl Sempozyumu, 16–18.
  • Jafarian, H., Behzadi, S., 2020. Evaluation of PM2.5 Emissions in Tehran by Means of Remote Sensing and Regression Models, Pollution. 6, 521–529.
  • Karakoç, O., 2022. Uzaktan Algılama ve Coğrafi Bilgi Sistemleri Entegrasyonu ile Çankırı İli Hava Kalitesi Haritasının Oluşturulması (Mapping of Dispersion of Air Quality of Çankırı Province by the Integration of Remote Sensing and Geographical Information Systems), (Master Thesis), Instute of Science, Konya, 96.
  • Kim K. H., Kabir, E., Kabir, S., 2015. A Review on the Human Health Impact of Airborne Particulate Matter, Environment International, 74, 136–143. https://doi.org/10.1016/j.envint.2014.10.005
  • Krzanowski, W. J., Hand, D. J., 2009. ROC Curve for Continuous Data, Chapman and Hall/CRC. https://doi.org/10.1201/9781439800225
  • Li, Z., Roy, D. P., Zhang, H. K., Vermote, E. F., Huang, H., 2019. Evaluation of Landsat-8 and Sentinel-2A Aerosol Optical Depth Retrievals Across Chinese Cities and Implications for Medium Spatial Resolution Urban Aerosol Monitoring, Remote Sensing, 11. https://doi.org/10.3390/rs11020122
  • Maddala, G. S., 2001. Introduction to Econometrics, John Wiley&Sons, New York.
  • Makineci, H., Arikan, D., Alkan, D., Karasaka, L., 2023. Spatio-temporal Analysis of Sentinel-5P Data of Konya City Between 2019- 2021, 170, 23-40.
  • Mamić, L., Gašparović, M., Kaplan, G., 2023. Developing PM2.5 and PM10 prediction models on a national and regional scale using open-source remote sensing data, Environ Monit Assess 195, 644. https://doi.org/10.1007/s10661-023-11212-x
  • Mather, P. M., Koch, M., 2011. Computer Processing of Remotely-Sensed Images: An Introduction, 4th ed., Wiley-Blackwell, Chichester.
  • Nas, B., Karabork, H., Berktay, A., Ekercin, S., 2007. Assessing Water Quality in the Beysehir Lake (Turkey) by the Application of GIS, Geostatistics and Remote Sensing.
  • Nguyen, N. H. and Tran, V.A., 2014. Estimation of PM10 from Aot of Satellite Landsat 8 Image over Hanoi City, in: International Symposium on Geoinformatics for Spatial Infrastructure Development in Earth and Allied Sciences.
  • Othman, N., Mat Jafri, M. Z., San, L. H., 2010. Estimating Particulate Matter Concentration over Arid Region Using Satellite Remote Sensing: A Case Study in Makkah, Saudi Arabia, Modern Applied Science, 4. https://doi.org/10.5539/mas.v4n11p131
  • Schwarze, P. E., Ovrevik, J., Låg, M., Refsnes, M., Nafstad, P., Hetland, R. B., & Dybing, E, 2006. Particulate matter properties and health effects: consistency of epidemiological and toxicological studies. Human & experimental toxicology, 25(10), 559–579. https://doi.org/10.1177/096032706072520
  • Sifakis, N., 1992. Mapping of Air Pollution Using SPOT Satellite Data, Photogrammetric Engineering and Remote Sensing, 58, 1433-1437.
  • Sola, I., García-Martín, A., Sandonís-Pozo, L., Álvarez-Mozos, J., Pérez-Cabello, F., González-Audícana, M., Llovería, R. M., 2018. Assessment of atmospheric correction methods for Sentinel-2 images in Mediterranean landscapes, International Journal of Applied Earth Observation and Geoinformation, 73, 63-76. https://doi.org/10.1016/j.jag.2018.05.020.
  • Şahinler, S., 2000. En Küçük Kareler Yöntemi ile Doǧrusal Regresyon Modeli Oluşturmanın Temel Prensipleri (Basic Principles of Linear Regression Modeling with Least Squares Method), MKÜ Faculty of Agriculture Journal, 5, 57–73.
  • Tasic, M., Rajsic, S., Novakovic, V., Mijic, Z., 2006. Atmospheric Aerosols and Their Influence on Air Quality in Urban Areas, Facta universitatis-series: Physics, Chemistry and Technology, 4, 83–91. https://doi.org/10.2298/FUPCT0601083T
  • Tomak, L., Bek, Y., 2010. Deneysel Araştırma (Experimental Research), 27, 58-65.
  • Valavanidis, A., Fiotakis, K., Vlachogianni, T., 2008. Airborne particulate matter and human health: toxicological assessment and importance of size and composition of particles for oxidative damage and carcinogenic mechanisms. Journal of Environmental Science and Health, Part C, 26(4), 339-362. https://doi.org/10.1080/10590500802494538
  • Wang, Y., Yuan, Q., Li, T., Tan, S., Zhang, L., 2021. Full-coverage spatiotemporal mapping of ambient PM2.5 and PM10 over China from Sentinel-5P and assimilated datasets: Considering the precursors and chemical compositions, Science of The Total Environment, 793. https://doi.org/10.1016/j.scitotenv.2021.148535.
  • https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/wpp2022_summary_of_results.pdf
  • https://www.who.int/news/item/04-04-2022-billions-of-people-still-breathe-unhealthy-air-new-who-data

Sentinel-2 Uydu Görüntüleri ile PM10 Haritasının Üretilmesi: Çankırı İli Örneği

Yıl 2024, Cilt: 24 Sayı: 2, 350 - 359, 29.04.2024
https://doi.org/10.35414/akufemubid.1372761

Öz

Küresel boyutta çevresel bir problem olarak nitelendirilen hava kirliliği dünya ülkelerine benzer şekilde Türkiye’de de gereksinim duyulan enerji miktarındaki artışın ve kontrolsüz yapılaşmanın bir sonucu olarak yaşamı negatif yönde etkilemektedir. Hava kirliliğine bağlı sağlık etkilerinin minimum düzeye indirilmesi için hava kalitesinin düzenli periyotlarla izlenmesi ve iyileştirilmesi yönünde ihtiyaç duyulan adımların atılması gerekmektedir. Uydu teknolojilerindeki yenilikler ile birlikte büyük alanların hava kalitesi uydu görüntüleri yardımıyla izlenebilmekte ve hava kirletici parametrelerin saptanması, tematik haritaların oluşturulması gibi birçok alanda etkili çözümler üretilebilmektedir. Araştırmanın temel amacı yerinde ölçülen PM10 parametreleri ile Sentinel-2 uydu verileri arasındaki ilişkiyi araştırmak ve bu ilişkiye dayanarak PM10’ u haritalandırmaktır. Bu kapsamda çalışmada farklı iki tarihte arazide ölçülen PM10 parametreleri ile Sentinel-2 uydusuna ait 22.11.2021 ve 16.04.2022 tarihli görüntüler veri kaynakları olarak kullanılmıştır. Kullanılan veriler arasındaki ilişki çoklu regresyon analizi ile kurulmuştur. Analiz sonuçlarından temin edilen katsayılar ilgili bantlara uygulanmış ve uydu görüntüleri kullanılarak tematik haritalar oluşturulmuştur. Regresyon analizleri ile hesaplanan 0,80 ve 0,79 korelasyon katsayıları araştırmada yeterli doğruluğa ulaşıldığını işaret etmektedir. Çalışma sonuçları PM10 tahmininde uydu görüntülerinin doğru veriler sunduğunu ve kirliliğin karayolu ulaşım ağı ile endüstriyel bölgelerde Dünya Sağlık Örgütü limitlerini aştığını göstermektedir.

Kaynakça

  • Anderson, J.O., Thundiyil, J.G., Stolbach, A., 2012. Clearing the air: a review of the effects of particulate matter air pollution on human health. Journal of medical toxicology: official journal of the American College of Medical Toxicology, 8(2), 166–175. https://doi.org/10.1007/s13181-011-0203-1
  • Chen, C.W., Tseng, Y.S., Mukundan, A., Wang, H.C., 2021. Air pollution: Sensitive Detection of PM2.5 and PM10 Concentration Using Hyperspectral Imaging, Applied Sciences, 11. https://doi.org/10.3390/app11104543
  • Cohen, A.J., Anderson, H.R., Ostro, B., Pandey, K.D., Krzyzanowski, M., Künzli N., Gutschmidt, K., Pope, A., Romieu, I., Samet, J.M., Smith, K., 2005. Comparative Quantification of Health Risks, Global and Regional Burden of Disease Attributable to Selected Major Risk Factors, Urban Air pollution, Journal of Toxicology and Environmental Health, 433–1354.
  • De Donno, A., De Giorgi, M., Bagordo, F., Grassi, T., Idolo, A., Serio, F., Ceretti, E., Feretti, D., Villarini, M., Moretti, M., Carducci, A., Verani, M., Bonetta, S., Pignata, C., Bonizzoni, S., Bonetti, A., Gelatti, U., MAPEC_LIFE Study Group., 2018. Health Risk Associated with Exposure to PM10 and Benzene in Three Italian Towns. International journal of environmental research and public health, 15(8), 1672. https://doi.org/10.3390/ijerph15081672
  • Ghasempour, F., Aliihsan Şekertekin, A., Kutoğlu, Ş.H., 2021. 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. https://doi.org/10.1016/j.jclepro.2021.128599.
  • Harbula, J., 2010. Dependence of PM10 Particles Concentration on Aerosol Optical Thickness Value from the MODIS Data.
  • Hime, N., Marks, G., Cowie, C., 2018. A Comparison of the Health Effects of Ambient Particulate Matter Air Pollution from Five Emission Sources. International Journal of Environmental Research and Public Health, 15, 1206. https://doi.org/10.3390/ijerph15061206
  • İnal, C., Turgut, B., Yiğit, C.Ö., 2002. Lokal Alanlarda Jeoit Ondülasyonlarının Belirlenmesinde Kullanılan Enterpolasyon Yöntemlerinin Karşılaştırılması (Comparison of Interpolation Methods Uset to Determine Geoid Corrugations in Local Areas), Selçuk Üniversitesi Jeodezi ve Fotogrametri Mühendisliği Öğretiminde 30. Yıl Sempozyumu, 16–18.
  • Jafarian, H., Behzadi, S., 2020. Evaluation of PM2.5 Emissions in Tehran by Means of Remote Sensing and Regression Models, Pollution. 6, 521–529.
  • Karakoç, O., 2022. Uzaktan Algılama ve Coğrafi Bilgi Sistemleri Entegrasyonu ile Çankırı İli Hava Kalitesi Haritasının Oluşturulması (Mapping of Dispersion of Air Quality of Çankırı Province by the Integration of Remote Sensing and Geographical Information Systems), (Master Thesis), Instute of Science, Konya, 96.
  • Kim K. H., Kabir, E., Kabir, S., 2015. A Review on the Human Health Impact of Airborne Particulate Matter, Environment International, 74, 136–143. https://doi.org/10.1016/j.envint.2014.10.005
  • Krzanowski, W. J., Hand, D. J., 2009. ROC Curve for Continuous Data, Chapman and Hall/CRC. https://doi.org/10.1201/9781439800225
  • Li, Z., Roy, D. P., Zhang, H. K., Vermote, E. F., Huang, H., 2019. Evaluation of Landsat-8 and Sentinel-2A Aerosol Optical Depth Retrievals Across Chinese Cities and Implications for Medium Spatial Resolution Urban Aerosol Monitoring, Remote Sensing, 11. https://doi.org/10.3390/rs11020122
  • Maddala, G. S., 2001. Introduction to Econometrics, John Wiley&Sons, New York.
  • Makineci, H., Arikan, D., Alkan, D., Karasaka, L., 2023. Spatio-temporal Analysis of Sentinel-5P Data of Konya City Between 2019- 2021, 170, 23-40.
  • Mamić, L., Gašparović, M., Kaplan, G., 2023. Developing PM2.5 and PM10 prediction models on a national and regional scale using open-source remote sensing data, Environ Monit Assess 195, 644. https://doi.org/10.1007/s10661-023-11212-x
  • Mather, P. M., Koch, M., 2011. Computer Processing of Remotely-Sensed Images: An Introduction, 4th ed., Wiley-Blackwell, Chichester.
  • Nas, B., Karabork, H., Berktay, A., Ekercin, S., 2007. Assessing Water Quality in the Beysehir Lake (Turkey) by the Application of GIS, Geostatistics and Remote Sensing.
  • Nguyen, N. H. and Tran, V.A., 2014. Estimation of PM10 from Aot of Satellite Landsat 8 Image over Hanoi City, in: International Symposium on Geoinformatics for Spatial Infrastructure Development in Earth and Allied Sciences.
  • Othman, N., Mat Jafri, M. Z., San, L. H., 2010. Estimating Particulate Matter Concentration over Arid Region Using Satellite Remote Sensing: A Case Study in Makkah, Saudi Arabia, Modern Applied Science, 4. https://doi.org/10.5539/mas.v4n11p131
  • Schwarze, P. E., Ovrevik, J., Låg, M., Refsnes, M., Nafstad, P., Hetland, R. B., & Dybing, E, 2006. Particulate matter properties and health effects: consistency of epidemiological and toxicological studies. Human & experimental toxicology, 25(10), 559–579. https://doi.org/10.1177/096032706072520
  • Sifakis, N., 1992. Mapping of Air Pollution Using SPOT Satellite Data, Photogrammetric Engineering and Remote Sensing, 58, 1433-1437.
  • Sola, I., García-Martín, A., Sandonís-Pozo, L., Álvarez-Mozos, J., Pérez-Cabello, F., González-Audícana, M., Llovería, R. M., 2018. Assessment of atmospheric correction methods for Sentinel-2 images in Mediterranean landscapes, International Journal of Applied Earth Observation and Geoinformation, 73, 63-76. https://doi.org/10.1016/j.jag.2018.05.020.
  • Şahinler, S., 2000. En Küçük Kareler Yöntemi ile Doǧrusal Regresyon Modeli Oluşturmanın Temel Prensipleri (Basic Principles of Linear Regression Modeling with Least Squares Method), MKÜ Faculty of Agriculture Journal, 5, 57–73.
  • Tasic, M., Rajsic, S., Novakovic, V., Mijic, Z., 2006. Atmospheric Aerosols and Their Influence on Air Quality in Urban Areas, Facta universitatis-series: Physics, Chemistry and Technology, 4, 83–91. https://doi.org/10.2298/FUPCT0601083T
  • Tomak, L., Bek, Y., 2010. Deneysel Araştırma (Experimental Research), 27, 58-65.
  • Valavanidis, A., Fiotakis, K., Vlachogianni, T., 2008. Airborne particulate matter and human health: toxicological assessment and importance of size and composition of particles for oxidative damage and carcinogenic mechanisms. Journal of Environmental Science and Health, Part C, 26(4), 339-362. https://doi.org/10.1080/10590500802494538
  • Wang, Y., Yuan, Q., Li, T., Tan, S., Zhang, L., 2021. Full-coverage spatiotemporal mapping of ambient PM2.5 and PM10 over China from Sentinel-5P and assimilated datasets: Considering the precursors and chemical compositions, Science of The Total Environment, 793. https://doi.org/10.1016/j.scitotenv.2021.148535.
  • https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/wpp2022_summary_of_results.pdf
  • https://www.who.int/news/item/04-04-2022-billions-of-people-still-breathe-unhealthy-air-new-who-data
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Fotogrametri ve Uzaktan Algılama, Planlamada Coğrafi Bilgi Sistemleri (CBS), Yer Ölçümü (Hidrografik Etüt Dahil)
Bölüm Makaleler
Yazarlar

Osman Karakoç 0000-0003-0351-7075

Semih Ekercin 0000-0002-9458-2261

Erken Görünüm Tarihi 14 Nisan 2024
Yayımlanma Tarihi 29 Nisan 2024
Gönderilme Tarihi 7 Ekim 2023
Yayımlandığı Sayı Yıl 2024 Cilt: 24 Sayı: 2

Kaynak Göster

APA Karakoç, O., & Ekercin, S. (2024). Generation of PM10 Map with Sentinel-2 Satellite Images: The Case of Çankırı Province. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 24(2), 350-359. https://doi.org/10.35414/akufemubid.1372761
AMA Karakoç O, Ekercin S. Generation of PM10 Map with Sentinel-2 Satellite Images: The Case of Çankırı Province. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. Nisan 2024;24(2):350-359. doi:10.35414/akufemubid.1372761
Chicago Karakoç, Osman, ve Semih Ekercin. “Generation of PM10 Map With Sentinel-2 Satellite Images: The Case of Çankırı Province”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 24, sy. 2 (Nisan 2024): 350-59. https://doi.org/10.35414/akufemubid.1372761.
EndNote Karakoç O, Ekercin S (01 Nisan 2024) Generation of PM10 Map with Sentinel-2 Satellite Images: The Case of Çankırı Province. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 24 2 350–359.
IEEE O. Karakoç ve S. Ekercin, “Generation of PM10 Map with Sentinel-2 Satellite Images: The Case of Çankırı Province”, Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, c. 24, sy. 2, ss. 350–359, 2024, doi: 10.35414/akufemubid.1372761.
ISNAD Karakoç, Osman - Ekercin, Semih. “Generation of PM10 Map With Sentinel-2 Satellite Images: The Case of Çankırı Province”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 24/2 (Nisan 2024), 350-359. https://doi.org/10.35414/akufemubid.1372761.
JAMA Karakoç O, Ekercin S. Generation of PM10 Map with Sentinel-2 Satellite Images: The Case of Çankırı Province. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2024;24:350–359.
MLA Karakoç, Osman ve Semih Ekercin. “Generation of PM10 Map With Sentinel-2 Satellite Images: The Case of Çankırı Province”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, c. 24, sy. 2, 2024, ss. 350-9, doi:10.35414/akufemubid.1372761.
Vancouver Karakoç O, Ekercin S. Generation of PM10 Map with Sentinel-2 Satellite Images: The Case of Çankırı Province. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2024;24(2):350-9.