Impacts and Drivers of Summer Wildfires in the Cape Peninsula: A Remote Sensing Approach
Abstract
:1. Introduction
2. Study Site
3. Data Acquisition and Methods
3.1. Data Acquisition
3.1.1. Sentinel-5P/TROPOMI
3.1.2. MODIS
3.1.3. AIRS
3.1.4. MERRA-2
3.1.5. OMI
3.1.6. HYSPLIT Model
3.2. Methods
Sentinel-2
4. Results and Discussion
4.1. Fire Detection and Burnt Scars
4.2. Emissions and Meteorological Drivers
5. Summary and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
References
- Halofsky, J.E.; Peterson, D.L.; Harvey, B.J. Changing wildfire, changing forests: The effects of climate change on fire regimes and vegetation in the Pacific Northwest, USA. Fire. Ecol. 2020, 16, 4. [Google Scholar] [CrossRef]
- Swati, S. Forest fire emissions: A contribution to global climate change. Front. For. Glob. Chang. 2022, 5, 925480. [Google Scholar] [CrossRef]
- Zhang, Z.; Long, T.; He, G.; Wei, M.; Tang, C.; Wang, W.; Wang, G.; She, W.; Zhang, X. Study on Global Burned Forest Areas Based on Landsat Data. Photogramm. Eng. Remote Sens. 2020, 86, 503–508. [Google Scholar] [CrossRef]
- Gill, A.M.; Stephens, S.L.; Cary, G.J. The worldwide “wildfire” problem. Ecol. Appl. 2013, 23, 438–454. [Google Scholar] [CrossRef] [PubMed]
- Bowman, D.M.J.S.; Kolden, C.A.; Abatzoglou, J.T.; Johnston, F.H.; van der Werf, G.R.; Flannigan, M. Vegetation fires in the Anthropocene. Nat. Rev. Earth. Environ. 2020, 1, 500–515. [Google Scholar] [CrossRef]
- Cardíl, A.; Tapia, V.M.; Monedero, S.; Quiñones, T.; Little, K.; Stoof, C.R.; Ramirez, J.; de-Miguel, S. Characterizing the rate of spread of large wildfires in emerging fire environments of northwestern Europe using Visible Infrared Imaging Radiometer Suite active fire data. Nat. Hazards Earth Syst. Sci. 2023, 23, 361–373. [Google Scholar] [CrossRef]
- Cruz, M.G.; Alexander, M.E.; Kilinc, M. Wildfire Rates of Spread in Grasslands under Critical Burning Conditions. Fire 2022, 5, 55. [Google Scholar] [CrossRef]
- Van Wilgen, B.W.; Le Maitre, D.C.; Kruger, F.J. Fire Behaviour in South African Fynbos (Macchia) Vegetation and Predictions from Rothermel’s Fire Model. J. Appl. Ecol. 1985, 22, 207–216. [Google Scholar] [CrossRef]
- Mucina, L.; Rutherford, M. The vegetation of South Arica, Lesotho and Swaziland. In Strelitzia; South African National Biodiversity Institute: Pretoria, South Africa, 2006; Volume 19. [Google Scholar]
- Dendy, S.P.; Tong, B.; Alexander, H.M.; Fay, P.A.; Murray, L.; Xing, Y.; Garrett, K.A. A long-term study of burning effects on a plant pathogen in tallgrass prairie. Plant Pathol. 2019, 66, 1308–1317. [Google Scholar] [CrossRef]
- Riveiro, S.F.; García-Duro, J.; Cruz, Ó.; Casal, M.; Reyes, O. Fire effects on germination response of the native species Daucus carota and the invasive alien species Helichrysum foetidum and Oenothera glazioviana. Glob. Ecol. Conserv. 2019, 20, e00730. [Google Scholar] [CrossRef]
- Riveiro, S.F.; Cruz, Ó.; Casal, M.; Reyes, O. Fire and seed maturity drive the viability, dormancy, and germination of two invasive species: Acacia longifolia (Andrews) Willd. and Acacia mearnsii De Wild. Ann. For. Sci. 2020, 77, 60. [Google Scholar] [CrossRef]
- He, T.; Lamont, B.B.; Pausas, J.G. Fire as a key driver of Earth’s biodiversity. Biol. Rev. 2019, 94, 1983–2010. [Google Scholar] [CrossRef]
- Yao, W.; Zhao, Y.; Chen, R.; Wang, M.; Song, W.; Yu, D. Emissions of Toxic Substances from Biomass Burning: A Review of Methods and Technical Influencing Factors. Processes 2023, 11, 853. [Google Scholar] [CrossRef]
- Johnston, H.J.; Mueller, W.; Steinle, S.; Steinle, S.; Vardoulakis, S.; Tantrakarnapa, K.; Loh, M.; Cherrie, J.W. How Harmful Is Particulate Matter Emitted from Biomass Burning? A Thailand Perspective. Curr. Pollut. Rep. 2019, 5, 353–377. [Google Scholar] [CrossRef]
- Koppmann, R.; von Czapiewski, K.; Reid, J.S. A review of biomass burning emissions, part I: Gaseous emissions of carbon monoxide, methane, volatile organic compounds, and nitrogen containing compounds. Atmos. Chem. Phys. Discuss. 2005, 5, 10455–10516. [Google Scholar] [CrossRef]
- Andreae, M.O.; Merlet, P. Emission of trace gases and aerosols from biomass burning. Glob. Biogeochem. Cycles 2001, 15, 955–966. [Google Scholar] [CrossRef]
- Keeley, J.E.; Syphard, A.D. Large California wildfires: 2020 fires in historical context. Fire Ecol. 2021, 17, 22. [Google Scholar] [CrossRef]
- Eck, T.F.; Holben, B.N.; Reid, J.S.; Sinyuk, A.; Giles, D.M.; Arola, A.; Slutsker, I.; Schafer, J.S.; Sorokin, M.G.; Smirnov, A.; et al. The extreme forest fires in California/Oregon in 2020: Aerosol optical and physical properties and comparisons of aged versus fresh smoke. Atmos. Environ. 2023, 305, 119798. [Google Scholar] [CrossRef]
- Deb, P.; Moradkhani, H.; Abbaszadeh, P.; Kiem, A.S.; Engström, J.; Keellings, D.; Sharma, A. Causes of the widespread 2019–2020 Australian bushfire season. Earth’s Future 2020, 8, e2020EF001671. [Google Scholar] [CrossRef]
- Shikwambana, L.; Kganyago, M. Observations of Emissions and the Influence of Meteorological Conditions during Wildfires: A Case Study in the USA, Brazil, and Australia during the 2018/19 Period. Atmosphere 2021, 12, 11. [Google Scholar] [CrossRef]
- Clarke, H.; Cirulis, B.; Penman, T. The 2019–2020 Australian forest fires are a harbinger of decreased prescribed burning effectiveness under rising extreme conditions. Sci. Rep. 2022, 12, 11871. [Google Scholar] [CrossRef]
- Jalaludin, B.; Johnston, F.; Vardoulakis, S.; Morgan, G. Reflections on the Catastrophic 2019–2020 Australian Bushfires. Innov. J. 2020, 1, 100010. [Google Scholar] [CrossRef]
- Strydom, S.; Savage, M. A spatio-temporal analysis of fires in South Africa. S. Afr. J. Sci. 2016, 112, 1–8. [Google Scholar] [CrossRef]
- Kraaij, T.; Baard, J.A.; Arndt, J.; Vhengani, L.; van Wilgen, B.W. An assessment of climate, weather, and fuel factors influencing a large, destructive wildfire in the Knysna region, South Africa. Fire Ecol. 2018, 14, 4. [Google Scholar] [CrossRef]
- Quiroz, N.F.; Gibson, L.; Conradie, W.S.; Ryan, P.; Heydenrych, R.; Moran, A.; van Straten, A.; Walls, R. Analysis of the 2017 Knysna fires disaster with emphasis on fire spread, home losses and the influence of vegetation and weather conditions: A South African case study. Int. J. Disaster Risk Reduct. 2023, 88, 103618. [Google Scholar] [CrossRef]
- Fernández-Manso, A.; Fernández-Manso, O.; Quintano, C. SENTINEL-2A red-edge spectral indices suitability for discriminating burn severity. Int. J. Appl. Earth Observ. Geoinform. 2016, 50, 170–175. [Google Scholar] [CrossRef]
- Suwanprasit, C.; Shahnawaz, S. Mapping burned areas in Thailand using Sentinel-2 imagery and OBIA techniques. Sci. Rep. 2024, 14, 9609. [Google Scholar] [CrossRef]
- Giglio, L.; Schroeder, W.; Justice, C.O. The collection 6 MODIS active fire detection algorithm and fire products. Remote Sens. Environ. 2016, 178, 31–41. [Google Scholar] [CrossRef]
- Kim, M.; Jung, M.; Kim, Y. Histogram matching of Sentinel-2 spectral information to enhance Planetscope imagery for effective wildfire damage assessment. Korean J. Remote Sens. 2019, 35, 517–534. [Google Scholar] [CrossRef]
- Cowling, R.M.; MacDonald, I.A.W.; Simmons, M.T. The Cape Peninsula, South Africa: Physiographical, biological, and historical background to an extraordinary hot spot of biodiversity. Biodivers. Conserv. 1996, 5, 527–550. [Google Scholar] [CrossRef]
- Pooley, S. Fire Geography and Urbanisation on the Cape Peninsula. In Burning Table Mountain; Palgrave Studies in World Environmental History; Palgrave Macmillan: London, UK, 2014. [Google Scholar] [CrossRef]
- Theys, N.; Hedelt, P.; De Smedt, I.; Lerot, C.; Yu, H.; Vlietinck, J.; Pedergnana, M.; Arellano, S.; Galle, B.; Fernandez, D.; et al. Global monitoring of volcanic SO2 degassing with unprecedented resolution from TROPOMI onboard Sentinel-5 Precursor. Sci. Rep. 2019, 9, 2643. [Google Scholar] [CrossRef] [PubMed]
- Tilstra, L.G.; de Graaf, M.; Wang, P.; Stammes, P. In-orbit Earth reflectance validation of TROPOMI on board the Sentinel-5 Precursor satellite. Atmos. Meas. Tech. 2020, 13, 4479–4497. [Google Scholar] [CrossRef]
- Verhoelst, T.; Compernolle, S.; Pinardi, G.; Lambert, J.C.; Eskes, H.J.; Eichmann, K.-U.; Fjæraa, A.M.; Granville, J.; Niemeijer, S.; Cede, A.; et al. Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks. Atmos. Meas. Tech. 2021, 14, 481–510. [Google Scholar] [CrossRef]
- National Aeronautics and Space Administration. MODIS Data. Available online: https://terra.nasa.gov/data/modis-data (accessed on 16 November 2022).
- Justice, C.O.; Townshend, J.R.G.; Vermote, E.F.; Masuoka, E.; Wolfe, R.E.; Saleous, N.; Roy, D.P.; Morisette, J.T. An overview of MODIS Land data processing and product status. Remote Sens. Environ. 2002, 83, 3–15. [Google Scholar] [CrossRef]
- Zhao, B.; Mao, K.; Cai, Y.; Shi, J.; Li, Z.; Qin, Z.; Meng, X.; Shen, X.; Guo, Z. A combined Terra and Aqua MODIS land surface temperature and meteorological station data product for China from 2003 to 2017. Earth Syst. Sci. Data 2020, 12, 2555–2577. [Google Scholar] [CrossRef]
- Giglio, L.; Descloitres, J.; Justice, C.O.; Kaufman, Y.J. An Enhanced Contextual Fire Detection Algorithm for MODIS. Remote Sens. Environ. 2003, 87, 273–282. [Google Scholar] [CrossRef]
- Hartmut, H.; Aumann, H.; Miller, C.R. Atmospheric infrared sounder (AIRS) on the earth observing system. In Proceedings of the Advanced and Next-Generation Satellites, Paris, France, 25–28 September 1995; Volume 2583. [Google Scholar]
- Chahine, M.T.; Pagano, T.; Aumann, H.; Atlas, R.; Barnet, C.; Blaisdell, J.; Chen, L.; Divakarla, M.; Fetzer, E.; Goldberg, M.; et al. AIRS: Improving weather forecasting and providing new data on greenhouse gases. Bull. Am. Meteorol. Soc. 2006, 87, 911–926. [Google Scholar]
- Menzel, W.P.; Schmit, T.J.; Zhang, P.; Li, J. Satellite-Based Atmospheric Infrared Sounder Development and Applications. Bull. Am. Meteorol. Soc. 2018, 99, 583–603. [Google Scholar] [CrossRef]
- Rienecker, M.M.; Suarez, M.J.; Gelaro, R.; Todling, R.; Bacmeister, J.; Liu, E.; Bosilovich, M.G.; Schubert, S.D.; Takacs, L.; Kim, G.; et al. MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Clim. 2011, 24, 3624–3648. [Google Scholar] [CrossRef]
- Wargan, K.; Labow, G.; Frith, S.; Pawson, S.; Livesey, N.; Partyka, G. Evaluation of the Ozone Fields in NASA’s MERRA-2 Reanalysis. J. Clim. 2017, 30, 2961–2988. [Google Scholar] [CrossRef]
- Gelaro, R.; McCarty, W.; Suárez, M.J.; Todling, R.; Molod, A.; Takacs, L.; Randles, C.A.; Darmenov, A.; Bosilovich, M.G.; Reichle, R.; et al. The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). J. Clim. 2017, 30, 5419–5454. [Google Scholar] [CrossRef]
- Buchard, V.; Randles, C.A.; da Silva, A.M.; Darmenov, A.; Colarco, P.R.; Govindaraju, R.; Ferrare, R.; Hair, J.; Beyersdorf, A.J.; Ziemba, L.D.; et al. The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part II: Evaluation and Case Studies. J. Clim. 2017, 30, 6851–6872. [Google Scholar] [CrossRef]
- Randles, C.A.; da Silva, A.M.; Buchard, V.; Colarco, P.R.; Darmenov, A.; Govindaraju, R.; Smirnov, A.; Holben, B.; Ferrare, R.; Hair, J.; et al. The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data Assimilation Evaluation. J. Clim. 2017, 30, 6823–6850. [Google Scholar] [CrossRef]
- Kroon, M.; de Haan, J.F.; Veefkind, J.P.; Froidevaux, L.; Wang, R.; Kivi, R.; Hakkarainen, J.J. Validation of operational ozone profiles from the Ozone Monitoring Instrument. J. Geophys. Res. 2011, 116, D18305. [Google Scholar] [CrossRef]
- Levelt, P.F.; van den Oord, G.H.J.; Dobber, M.R.; Mälkki, A.; Visser, H.; de Vries, J.; Stammes, P. The ozone monitoring instrument. IEEE Trans. Geosci. Remote Sens. 2006, 4, 1093–1101. [Google Scholar] [CrossRef]
- Stein, A.F.; Draxler, R.R.; Rolph, G.D.; Stunder, B.J.B.; Cohen, M.D.; Ngan, F. NOAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bull. Am. Meteorol. Soc. 2015, 96, 2059–2077. [Google Scholar] [CrossRef]
- Fleming, Z.L.; Monks, P.S.; Manning, A.J. Review: Untangling the influence of air-mass history in interpreting observed atmospheric composition. Atmos. Res. 2012, 104–105, 1–39. [Google Scholar] [CrossRef]
- Draxler, R. Evaluation of an Ensemble Dispersion Calculation. J. Appl. Meteorol. 2003, 42, 308–317. [Google Scholar] [CrossRef]
- Spoto, F.; Sy, O.; Laberinti, P.; Martimort, P.; Fernandez, V.; Colin, O.; Hoersch, B.; Meygret, A. Overview of Sentinel-2. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany, 22–27 July 2012; pp. 1707–1710. [Google Scholar]
- Sudmanns, M.; Tiede, D.; Augustin, H.; Lang, S. Assessing global Sentinel-2 coverage dynamics and data availability for operational Earth observation (EO) applications using the EO-Compass. Int. J. Digit. Earth. 2019, 13, 768–784. [Google Scholar] [CrossRef]
- Hunt, R.; Barrett, N.; Park, S. Measurement of Leaf Relative Water Content by Infrared Reflectance. Remote Sens. Environ. 1987, 22, 429–435. [Google Scholar] [CrossRef]
- Strydom, T.; Kraaij, T.; Difford, M.; Cowling, R.M. Fire severity effects on resprouting of subtropical dune thicket of the Cape Floristic Region. PeerJ 2020, 8, e9240. [Google Scholar] [CrossRef] [PubMed]
- Cocke, A.E.; Fulé, P.Z.; Crouse, J.E. Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data. Int. J. Wildland Fire 2005, 14, 189–198. [Google Scholar] [CrossRef]
- Kushla, J.D.; Ripple, W.J. Assessing wildfire effects with Landsat thematic mapper data. Int. J. Remote Sens. 1998, 19, 2493–2507. [Google Scholar] [CrossRef]
- Bertolette, D.; Spotskey, D. Remotely sensed burn severity mapping. In Crossing Boundaries in Park Management, Proceedings of the 11th Conference on research and Resource Management in Parks and on Public Lands, MI, USA, 15 April 2021; Harmon, D., Ed.; The George Wright Society: Hancock, MI, USA, 2021; pp. 44–51. [Google Scholar]
- Pierce, S.M.; Cowling, R.M. Disturbance regimes as determinants of seed banks in coastal dune vegetation of the southeastern Cape. J. Veg. Sci. 1991, 2, 403–412. [Google Scholar] [CrossRef]
- Harte, E.W.; Childs, I.R.W.; Hastings, P.A. Imizamo Yethu: A case study of community resilience to fire hazard in an informal settlement Cape Town, South Africa. Geogr. Res. 2009, 47, 142–154. [Google Scholar] [CrossRef]
- Tošić, I.; Mladjan, D.; Gavrilov, M.; Živanović, S.; Radaković, M.; Putniković, S.; Petrović, P.; Mistridželović, I.; Marković, S. Potential influence of meteorological variables on forest fire risk in Serbia during the period 2000–2017. Open Geosci. 2019, 11, 414–425. [Google Scholar] [CrossRef]
- Dong, L.; Leung, L.R.; Qian, Y.; Zou, Y.; Song, F.; Chen, X. Meteorological environments associated with California wildfires and their potential roles in wildfire changes during 1984–2017. J. Geophys. Res. Atmos. 2021, 126, e2020JD033180. [Google Scholar] [CrossRef]
- Kulshrestha, U.; Kumar, B. Airmass Trajectories and Long-Range Transport of Pollutants: Review of Wet Deposition Scenario in South Asia. Adv. Meteorol. 2014, 14, 596041. [Google Scholar] [CrossRef]
- Febo, A.; Guglielmi, F.; Manigrasso, M.; Ciambottini, V.; Avino, P. Local air pollution and long–range mass transport of atmospheric particulate matter: A comparative study of the temporal evolution of the aerosol size fractions. Atmos. Pollut. Res. 2010, 1, 141–146. [Google Scholar] [CrossRef]
- Canny, M.J.; Haung, C.X. Leaf water content and palisade cell size. New Phytol. 2006, 170, 75–85. [Google Scholar] [CrossRef]
- Chen, Y.; Morton, D.C.; Randerson, J.T. Remote sensing for wildfire monitoring: Insights into burned area, emissions, and fire dynamics. One Earth 2024, 7, 1022–1028. [Google Scholar] [CrossRef]
Data Source | Product Name | Spatial Resolution | Spectral Resolution | Date of Acquisition | Output Data |
---|---|---|---|---|---|
TROPOMI | CO | 7.0 km × 3.5 km | 267––2389 nm | 12–25 December 2023 | Spatial distribution map and Timeseries plot |
MODIS | Burnt Area date and LST | 500 m | 36 bands (400–14,400 nm) | 1 January 2023 to 30 April 2024 | Spatial distribution map and Timeseries plot |
AIRS | Relative Humidity | 13.5 km | 2378 channels (3.7–15.4 µm) | 1 January 2023 to 30 April 2024 | Timeseries plot |
MERRA-2 | Wind Speed | 0.625° × 0.5° | N/A | 1 January 2023 to 30 April 2024 | Timeseries plot |
OMI | UVAI | 13 × 24 km2 | 0.42–0.63 nm | 1 January 2023 to 30 April 2024 | Timeseries plot |
Sentinel-2 | ΔNBR | 10 m, 20 m, 60 m | 13 bands (443–2190 nm) | Mean for Jan 2024; October 2023 | Spatial distribution map |
HYSPLIT model | 5-day forward air-mass trajectories | - | - | 25–29 December 2023 | Map showing trajectory of air masses |
Severity Level | dNBR Range (Scaled by 1000) |
---|---|
Enhanced regrowth, high (post-fire) | −500 to −250 |
Enhanced regrowth, low (post-fire) | −250 to −101 |
Unburned | −100 to 99 |
Low Severity | 100 to 269 |
Moderate–low severity | 270 to 439 |
Moderate–high severity | 440 to 659 |
High severity | 660 to 1300 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Xongo, K.; Ngcoliso, N.; Shikwambana, L. Impacts and Drivers of Summer Wildfires in the Cape Peninsula: A Remote Sensing Approach. Fire 2024, 7, 267. https://doi.org/10.3390/fire7080267
Xongo K, Ngcoliso N, Shikwambana L. Impacts and Drivers of Summer Wildfires in the Cape Peninsula: A Remote Sensing Approach. Fire. 2024; 7(8):267. https://doi.org/10.3390/fire7080267
Chicago/Turabian StyleXongo, Kanya, Nasiphi Ngcoliso, and Lerato Shikwambana. 2024. "Impacts and Drivers of Summer Wildfires in the Cape Peninsula: A Remote Sensing Approach" Fire 7, no. 8: 267. https://doi.org/10.3390/fire7080267