Spatial Autocorrelation Analysis of CO and NO<sub>2</sub> Related to Forest Fire Dynamics
The increasing frequency and severity of forest fires globally highlight the critical need to understand their environmental impacts. This study applies spatial autocorrelation techniques to analyze the dispersion patterns of carbon monoxide (CO) and nitrogen dioxide (NO<sub>2</sub>) emi...
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MDPI AG
2025-02-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/14/2/65 |
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| author | Hatice Atalay Ayse Filiz Sunar Adalet Dervisoglu |
| author_facet | Hatice Atalay Ayse Filiz Sunar Adalet Dervisoglu |
| author_sort | Hatice Atalay |
| collection | DOAJ |
| description | The increasing frequency and severity of forest fires globally highlight the critical need to understand their environmental impacts. This study applies spatial autocorrelation techniques to analyze the dispersion patterns of carbon monoxide (CO) and nitrogen dioxide (NO<sub>2</sub>) emissions during the 2021 Manavgat forest fires in Türkiye, using Sentinel-5P satellite data. Univariate (UV) Global Moran’s I values indicated strong spatial autocorrelation for CO (0.84–0.93) and NO<sub>2</sub> (0.90–0.94), while Bivariate (BV) Global Moran’s I (0.69–0.84) demonstrated significant spatial correlations between the two gases. UV Local Moran’s I analysis identified distinct UV High-High (UV-HH) and UV Low-Low (UV-LL) clusters, with CO concentrations exceeding 0.10000 mol/m<sup>2</sup> and exhibiting wide dispersion, while NO<sub>2</sub> concentrations, above 0.00020 mol/m<sup>2</sup>, remained localized near intense fire zones due to its shorter atmospheric lifetime. BV Local Moran’s I analysis revealed overlapping BV-HH (high CO, high NO<sub>2</sub>) and BV-LL (low CO, low NO<sub>2</sub>) clusters, influenced by topography and meteorological factors. These findings enhance the understanding of gas emission dynamics during forest fires and provide critical insights into the influence of environmental and combustion processes on pollutant dispersion. |
| format | Article |
| id | doaj-art-0fb2d6e5235a4044bc22e5af59b65a6b |
| institution | DOAJ |
| issn | 2220-9964 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj-art-0fb2d6e5235a4044bc22e5af59b65a6b2025-08-20T02:44:35ZengMDPI AGISPRS International Journal of Geo-Information2220-99642025-02-011426510.3390/ijgi14020065Spatial Autocorrelation Analysis of CO and NO<sub>2</sub> Related to Forest Fire DynamicsHatice Atalay0Ayse Filiz Sunar1Adalet Dervisoglu2Geomatics Engineering, Civil Engineering Faculty, Istanbul Technical University, 34469 Istanbul, TürkiyeGeomatics Engineering, Civil Engineering Faculty, Istanbul Technical University, 34469 Istanbul, TürkiyeGeomatics Engineering, Civil Engineering Faculty, Istanbul Technical University, 34469 Istanbul, TürkiyeThe increasing frequency and severity of forest fires globally highlight the critical need to understand their environmental impacts. This study applies spatial autocorrelation techniques to analyze the dispersion patterns of carbon monoxide (CO) and nitrogen dioxide (NO<sub>2</sub>) emissions during the 2021 Manavgat forest fires in Türkiye, using Sentinel-5P satellite data. Univariate (UV) Global Moran’s I values indicated strong spatial autocorrelation for CO (0.84–0.93) and NO<sub>2</sub> (0.90–0.94), while Bivariate (BV) Global Moran’s I (0.69–0.84) demonstrated significant spatial correlations between the two gases. UV Local Moran’s I analysis identified distinct UV High-High (UV-HH) and UV Low-Low (UV-LL) clusters, with CO concentrations exceeding 0.10000 mol/m<sup>2</sup> and exhibiting wide dispersion, while NO<sub>2</sub> concentrations, above 0.00020 mol/m<sup>2</sup>, remained localized near intense fire zones due to its shorter atmospheric lifetime. BV Local Moran’s I analysis revealed overlapping BV-HH (high CO, high NO<sub>2</sub>) and BV-LL (low CO, low NO<sub>2</sub>) clusters, influenced by topography and meteorological factors. These findings enhance the understanding of gas emission dynamics during forest fires and provide critical insights into the influence of environmental and combustion processes on pollutant dispersion.https://www.mdpi.com/2220-9964/14/2/65spatial autocorrelationMoran’s indexforest fireAntalya |
| spellingShingle | Hatice Atalay Ayse Filiz Sunar Adalet Dervisoglu Spatial Autocorrelation Analysis of CO and NO<sub>2</sub> Related to Forest Fire Dynamics ISPRS International Journal of Geo-Information spatial autocorrelation Moran’s index forest fire Antalya |
| title | Spatial Autocorrelation Analysis of CO and NO<sub>2</sub> Related to Forest Fire Dynamics |
| title_full | Spatial Autocorrelation Analysis of CO and NO<sub>2</sub> Related to Forest Fire Dynamics |
| title_fullStr | Spatial Autocorrelation Analysis of CO and NO<sub>2</sub> Related to Forest Fire Dynamics |
| title_full_unstemmed | Spatial Autocorrelation Analysis of CO and NO<sub>2</sub> Related to Forest Fire Dynamics |
| title_short | Spatial Autocorrelation Analysis of CO and NO<sub>2</sub> Related to Forest Fire Dynamics |
| title_sort | spatial autocorrelation analysis of co and no sub 2 sub related to forest fire dynamics |
| topic | spatial autocorrelation Moran’s index forest fire Antalya |
| url | https://www.mdpi.com/2220-9964/14/2/65 |
| work_keys_str_mv | AT haticeatalay spatialautocorrelationanalysisofcoandnosub2subrelatedtoforestfiredynamics AT aysefilizsunar spatialautocorrelationanalysisofcoandnosub2subrelatedtoforestfiredynamics AT adaletdervisoglu spatialautocorrelationanalysisofcoandnosub2subrelatedtoforestfiredynamics |