Potentialité des données satellitaires Sentinel-2 pour la cartographie de l’impact des feux de végétation en Afrique tropicale : application au Togo
DOI :
https://doi.org/10.19182/bft2021.347.a36349Mots-clés
feux de végétation, feux utilitaires, feux incontrôlés, indice NBR, image Sentinel-2, cartographie, télédétection, TogoRésumé
Le réchauffement climatique est un phénomène d’envergure mondiale qui se répercute sur le système climatique. Une des conséquences du réchauffement climatique est l'extension de la période de sécheresse, favorisant ainsi l’augmentation des fréquences du phénomène des feux de végétation. Les feux incontrôlés perturbent l’écologie et la fonctionnalité des écosystèmes, entraînant parfois leur érosion. La présente étude est une contribution pour la gestion des feux de végétation au Togo et porte sur le suivi spatial pour la saison des feux 2018-2019. Elle explore la potentialité des nouvelles données satellitaires Sentinel-2 (S-2) en accès libre dans la gamme de la télédétection optique pour la détection des surfaces brûlées, la cartographie des feux utilitaires et des feux incontrôlés. Elle teste également la performance de la méthode de cartographie des feux de végétation à partir de l’indice NBR (Normalized Burn Ratio) initialement conçue pour les images Landsat et évalue la biomasse végétale brûlée. Les résultats révèlent que les images S-2 présentent du potentiel dans la restitution des surfaces brûlées. La performance de la méthode de l’indice NBR sur les images S-2 est satisfaisante. La cartographie des feux de végétation montre que les feux utilitaires représentent 21,75 % contre 78,25 % pour les feux incontrôlés. L’ensemble des feux de végétation enregistrés a occasionné l’incendie de 5 878 km2 du couvert végétal, soit 10,39 % du territoire national. Le couvert végétal brûlé est composé majoritairement de savanes (33,12 %), de cultures et jachères (24,48 %), de plantations (14,59 %), de forêts claires (14,43 %) et de forêts riveraines (13,02 %). Les résultats obtenus constituent des éléments tangibles pour le suivi, la sensibilisation, l’élaboration des plans d’aménagement, de prévention et de gestion des feux.
Téléchargements
Références
Références
Afelu B., 2016. Contribution à la gestion des feux de végétation au Togo. Thèse de doctorat, Université de Lomé, Togo, 177 p.
Atsri H. K., Konko Y., Cuni-Sanchez A., Abotsi K. E., Kokou K., 2018. Changes in the West African forest-savanna mosaic, insights from central Togo. Plos One, 13v (10): e0203999. https://doi.org/10.1371/journal.pone.0203999
Bartalev S. A., Egorov V. A., Loupian E. A., Uvarov I. A., 2007. Multi-year circumpolar assessment of the area burnt in boreal ecosystems using SPOT-VEGETATION. International Journal of Remote Sensing, 28 (6): 1397-1404. https://doi.org/10.1080/01431160600840978
Bastarrika A., Chuvieco E., Pilar Martín M., 2011. Mapping burned areas from Landsat TM/ETM+ data with a two-phase algorithm: Balancing omission and commission errors. Remote Sensing of Environment, 115 (4): 1003-1012. https://doi.org/10.1016/j.rse.2010.12.005
Boschetti M., Stroppiana D., Brivio P. A., 2010. Mapping burned areas in a Mediterranean environment using soft integration of spectral indices from high resolution satellite images. Earth Interactions, 14 (17): 1-20. https://doi.org/10.1175/2010EI349.1
Bowman D. M. J. S., Balch J. K., Artaxo P., Bond W. J., Carlson J. M., Cochrane M. A., et al., 2009. Fire in the Earth system. Science, 324 (5926): 481-484. https://doi.org/10.1126/science.1163886
Chuvieco E., Martin M. P., Palacios A., 2002. Assessment of different spectral indices in the red-near-infrared spectral domain for burned land discrimination. International Journal of Remote Sensing, 23 (23): 5103-5110. https://doi.org/10.1080/01431160210153129
Chuvieco E., Englefield P., Trischenko A., Lio Y., 2008. Generation of long time series of burn area maps of the boreal forest from NOAA-AVHRR composite data. Remote Sensing of Environment, 112 (5): 2381-2396. https://doi.org/10.1016/j.rse.2007.11.007
Chuvieco E., Aguado I., Yebra M., Nieto H., Salas J., Pilar Martín M., et al., 2010. Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecological Modelling, 221 (1): 46-58. https://doi.org/10.1016/j.ecolmodel.2008.11.017
Chuvieco E., Lizundia-Loiola J., Pettinari M. L., Ramo R., Padilla M., Tansey K., Mouillot F., et al., 2018. Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies. Earth System Science Data, 10 (4): 2015-2031. https://doi.org/10.5194/essd-10-2015-2018
Chuvieco E., Mouillot F., Van der Werf G. R., San Miguel J., Tanase M., Koutsias N., et al., 2019. Historical background and current developments for mapping burned area from satellite Earth observation. Remote Sensing of Environment, 225 (1): 45-64. https://doi.org/10.1016/j.rse.2019.02.013
Congalton R. G., 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37 (1): 35-46. https://doi.org/10.1016/0034-4257(91)90048-B
Doerr S. H., Shakesby R. A., Blake W. H., Chafer C. J., Humphreys G. S., Wallbrink P. J., 2006. Effects of differing wildfire severities on soil wettability and implications for hydrological response. Journal of Hydrology, 319 (1-4): 295-311. https://doi.org/10.1016/j.jhydrol.2005.06.038
Ern H., 1979. Die Vegetation Togos. Gliederung, Gefährdung, Erhaltung. Willdenowia, 9: 295-312. https://www.jstor.org/stable/3995654?seq=1
García-Llamas P., Suárez-Seoane S., Fernández-Guisuraga J. M., Fernández-García V., Fernández-Manso A., Quintano C., et al., 2019. Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems. International Journal of Applied Earth Observation and Geoinformation, 80: 137-144. https://doi.org/10.1016/j.jag.2019.04.006
González F. E., Ruiz J. M., Acosta F. M., 2013. Manuel de télédétection spatiale. TELECAN. Université de Las Palmas, Gran Canaria, 337 p. https://www.grss-ieee.org/wp-content/uploads/2014/07/FR_TUTORIAL_COMPLETO.pdf
Guelly K. A., 1994. Les savanes de la zone forestière subhumide du Togo. Thèse de doctorat. Université Pierre Marie-Curie, Paris VI, France. http://www.theses.fr/1994PA066589
IPCC, 2018. Global warming of 1.5 °C: An IPCC Special Report on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. Cambridge, UK, Cambridge University Press, 562 p. https://www.ipcc.ch/sr15/
Kamau P. N., Medley K. E., 2014. Anthropogenic fires and local livelihoods at Chyulu Hills, Kenya. Landscape and Urban Planning, 124: 76-84. https://doi.org/10.1016/j.landurbplan.2014.01.010
Keeley J. E., 2009. Fire intensity, fire severity and burn severity: a brief review and suggested usage. International Journal of Wildland Fire, 18 (1): 116-126. https://doi.org/10.1071/WF07049
Key C., Benson N., 2006. Landscape assessment: Ground measure of severity, the Composite Burn Index, and remote sensing of severity, the Normalized Burn Index. In: Lutes D., Keane R., Caratti J., Key C., Benson N., Sutherland S., et al., (eds). FIREMON: Fire effects monitoring and inventory system. Fort Collins, CO, USA, USDA Forest Service, Rocky Mountains Research Station, General Technical Report RMRS-GTR-164-CD, LA 1-51. https://www.fs.fed.us/rm/pubs/rmrs_gtr164.pdf
Knorr W., Jiang L., Arneth A., 2016. Climate, CO2 and human population impacts on global wildfire emissions. Biogeosciences, 13 (1): 267-282. https://doi.org/10.5194/bg-13-267-2016
Kokou K., Sokpon N., 2006. Les forêts sacrées du couloir du Dahomey. Bois et Forêts des Tropiques, 288 : 15-23. https://revues.cirad.fr/index.php/BFT/article/view/20312
Konko Y., 2016. Contribution of Remote Sensing and GIS to the Integrated Management of Community Forest Resources in the Bas-Mono Valley (South-East Togo). Master’s Thesis, Post University Regional School of Integrated Management of Tropical Forests and Territories, Kinshasa, Democratic Republic of Congo, 94 p. https://doi.org/10.13140/RG.2.2.20280.70403
Konko Y., Bagaram B., Julien F., Akpamou K. G., Kokou K., 2018a. Multitemporal Analysis of Coastal Erosion Based on Multisource Satellite Images in the South of the Mono Transboundary Biosphere Reserve in Togo (West Africa). Open Access Library Journal, 5 (4): e4526. https://doi.org/10.4236/oalib.1104526
Konko Y., Rudant J. P., Akpamou G. K., Noumonvi K. D., Kokou K., 2018b. Spatio-Temporal Distribution of Southeastern Community Forests in Togo (West Africa). Journal of Geoscience and Environment Protection, 6 (7): 51-65. https://doi.org/10.4236/gep.2018.67004
Konko Y., Okhimambe A., Nimon P., Asaana J., Rudant J. P., Kokou K., 2020. Coastline Change Modelling Induced by Climate Change Using Geospatial Techniques in Togo (West Africa). Advances in Remote Sensing, 9 (2): 85-100. https://doi.org/10.4236/ars.2020.92005
Labib S. M., Harris A., 2018. The potentials of Sentinel-2 and LandSat-8 data in green infrastructure extraction, using object based image analysis (OBIA) method. European Journal of Remote Sensing, 51 (1): 231-240. https://doi.org/10.1080/22797254.2017.1419441
Lasaponara R., 2006. Estimating spectral separability of satellite derived parameters for burned areas mapping in the Calabria region by using SPOT-vegetation data. Ecological Modelling, 196 (1-2): 265-270. https://doi.org/10.1016/j.ecolmodel.2006.02.025
Lewis S. L., Edwards D. P., Galbraith D., 2015. Increasing human dominance of tropical forests. Science, 349 (6250): 827-832. https://doi.org/10.1126/science.aaa9932
Mallinis G., Mitsopoulos I., Chrysafi I., 2018. Evaluating and comparing Sentinel 2A and Landsat-8 Operational Land Imager (OLI) spectral indices for estimating fire severity in a Mediterranean pine ecosystem of Greece. GIScience and Remote Sensing, 55 (1): 1-18. https://doi.org/10.1080/15481603.2017.1354803
McFeeters S. K., 1996. The Use of the Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features. International Journal of Remote Sensing, 17 (7): 1425-1432. https://doi.org/10.1080/01431169608948714
Miller J. D., Knapp E. E., Key C. H., Skinner C. N., Isbell C. J., Creasy R. M., et al., 2009. Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA. Remote Sensing of Environment, 113 (3) : 645-656. https://doi.org/10.1016/j.rse.2008.11.009
Mpakairi K. S., Ndaimani H., Kavhu B., 2020. Exploring the utility of Sentinel-2 MSI derived spectral indices in mapping burned areas in different land-cover types. Scientific African, 10: e00565. https://doi.org/10.1016/j.sciaf.2020.e00565
Nimon P., Issaou L., Konko Y., Kokou K., 2020. Spatio-Temporal Patterns of Rainfall Variability for Wet Season over Togo in West Africa. Open Access Library Journal, 7 (1): e6044. https://doi.org/10.4236/oalib.1106044
Reid C. E., Brauer M., Johnston F. H., Jerrett M., Balmes J. R., Elliott C. T., 2016. Critical review of health impacts of wildfire smoke exposure. Environmental Health Perspectives, 124 (9): 1334-1343. https://doi.org/10.1289/ehp.1409277
Rwanga S. S., Ndambuki J. M., 2017. Accuracy assessment of land use/land cover classification using remote sensing and GIS. International Journal of Geosciences, 8 (4): 611-622. https://doi.org/10.4236/ijg.2017.84033
Smith A. M. S., Drake N. A., Wooster M. J., Hudak A. T., Holden Z. A., Gibbons C. J., 2007. Production of Landsat ETM+ reference imagery of burned areas within Southern African savannahs: Comparison of methods and application to MODIS. International Journal of Remote Sensing, 28 (12): 2753-2775. https://doi.org/10.1080/01431160600954704
Schroeder Th., Behnert I., Schaale M., Fischer J., Doerffer R., 2007. Atmospheric correction algorithm for MERIS above case‐2 waters. International Journal of Remote Sensing, 28 (7):1469-1486. https://doi.org/10.1080/01431160600962574
Schroeder W., Oliva P., Giglio L., Quayle B., Lorenz E., Morelli F., 2016. Active fire detection using Landsat-8/OLI data. Remote Sensing of Environment, 185: 210-220. https://doi.org/10.1016/j.rse.2015.08.032
Sow M., Hély C., Mbow C., Sambou B., 2013. Fuel and fire behaviour analysis for early-season prescribed fire planning in Sudanian and Sahelian savannas. Journal of Arid Environments, 89: 84-93. https://doi.org/10.1016/j.jaridenv.2012.09.007
Smith A. M. S., Drake N. A., Wooster M. J., Hudak A. T., Holden Z. A., Gibbons C. J., 2007. Production of Landsat ETM+ reference imagery of burned areas within Southern African savannahs: Comparison of methods and application to MODIS. International Journal of Remote Sensing, 28 (12): 2753-2775. https://doi.org/10.1080/01431160600954704
Stehman S. V., Foody G. M., 2019. Key issues in rigorous accuracy assessment of land cover products. Remote Sensing of Environment, 231: 111199. https://doi.org/10.1016/j.rse.2019.05.018
Story M., Congalton R. G., 1986. Accuracy assessment: a user’s perspective. Photogrammetric Engineering and Remote Sensing, 52 (3): 397-399. https://www.asprs.org/wp-content/uploads/pers/1986journal/mar/1986_mar_397-399.pdf
Stroppiana D., Boschetti M., Zaffaroni P., Brivio P., 2009. Analysis and interpretation of spectral indices for soft multicriteria burned-area mapping in Mediterranean regions. IEEE Geoscience and Remote Sensing Letters, 6 (3): 499-503. https://doi.org/10.1109/LGRS.2009.2020067
Tucker C. J., 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8: 127-150. https://doi.org/10.1016/0034-4257(79)90013-0
Veraverbeke S., Verstraeten W. W., Lhermitte S., Goossens R., 2010a. Evaluating Landsat Thematic Mapper spectral indices for estimating burn severity of the 2007 Peloponnese wildfires in Greece. International Journal of Wildland Fire, 19 (5): 558-569. https://doi.org/10.1071/WF09069.
Veraverbeke S., Verstraeten W. W., Lhermitte S., Goossens R., 2010b. Illumination effects on the differenced Normalized Burn Ratio's optimality for assessing fire severity. International Journal of Applied Earth Observation and Geoinformation, 12 (1): 60-70. https://doi.org/10.1016/j.jag.2009.10.004
Veraverbeke S., Hook S., Hulley G., 2012. An alternative spectral index for rapid fire severity assessments. Remote Sensing of Environment, 123: 72-80. https://doi.org/10.1016/j.rse.2012.02.025
Verhegghen A., Eva H., Ceccherini G., Achard F., Gond V., Gourlet-Fleury S., et al., 2016. The potential of Sentinel satellites for burnt area mapping and monitoring in the Congo Basin forests. Remote Sensing, 8 (12): 986. https://doi.org/10.3390/rs8120986
Wang X., Liu Y., Ling F., Liu Y., Fang F., 2017. Spatio-Temporal Change Detection of Ningbo Shoreline Using Landsat Time-Series Images during 1976-2015. ISPRS International Journal of Geo-Information, 6 (3): 68. https://doi.org/10.3390/ijgi6030068
Yue C., Ciais P., Cadule P., Thonicke K., van Leeuwen T. T., 2015. Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE. Part 2: Carbon emissions and the role of fires in the global carbon balance. Geoscientific Model Development, 8 (5): 1285-1297. https://doi.org/10.5194/gmd-8-1321-2015
Téléchargements
Numéro
Rubrique
-
Résumé988
-
PDF755
Publié
Comment citer
Licence
Les articles sont publiés en Accès libre. Ils sont régis par le Droit d'auteur et par les licenses créative commons. La license utilisée est Attribution (CC BY 4.0).
