Wetland Fire Scar Monitoring and Its Response to Changes of the Pantanal Wetland

Fire is an important disturbance factor which results in the irreversible change of land surface ecosystems and leads to a new ecological status after the fire is extinguished. Spanning the period from August to September 2019, the Amazon Forest fires were an unprecedented event in terms of the scale and duration of burning, with a duration of 42 days in the Pantanal wetland. Based on the observation data of wildfire and two Sentinel-2A images separated by a 35-day interval, the objectives of this study are to use the Normalized Burn Ratio (NBR) to map the spatiotemporal change features of fire and then quantitatively measure the fire severity and the impact of fire on the Pantanal wetland. The overall accuracy and Kappa coefficient of the extracted results of wetland types reached 80.6% and 0.767, respectively, and the statistically analyzed results showed that wildfires did not radically change the wetland types of the Pantanal wetland, because the hydrological variation of the burned area was still the main change factor, with a dynamic ratio of ≤50%. Furthermore, the savanna wetland in the burned area was the wetland type which was most affected by the fire. Meanwhile, fire scars belonged to the moderate and low-severity burned areas, with a maximum burn area of 599 km2. The case enriches the research into the impact of wildfire as the main disturbance factor on the change of wetland types and provides a scientific reference for the restoration and sustainable development of global wetland ecosystems.

[1]  M. Swaine,et al.  A re-assessment of a fire protection experiment in north-eastern Ghana savanna. , 1980 .

[2]  C. Fausto,et al.  Amazonia 1492: Pristine Forest or Cultural Parkland? , 2003, Science.

[3]  R. C. S. Alvalá,et al.  BALANÇO DE RADIAÇÃO NO PANTANAL SUL MATO-GROSSENSE DURANTE A ESTAÇÃO SECA , 2013 .

[4]  E. Davidson,et al.  The role of deep roots in the hydrological and carbon cycles of Amazonian forests and pastures , 1994, Nature.

[5]  E. Davidson,et al.  Prolonged tropical forest degradation due to compounding disturbances: Implications for CO2 and H2O fluxes , 2019, Global change biology.

[6]  J. Barlow,et al.  Tropical forest fires and biodiversity: dung beetle community and biomass responses in a northern Brazilian Amazon forest , 2014, Journal of Insect Conservation.

[7]  Walter V. Reid,et al.  Millennium Ecosystem Assessment: Ecosystems and human well-being: wetlands and water synthesis , 2005 .

[8]  Aimin Li,et al.  Assessment of the manganese content of the drinking water source in Yancheng, China. , 2010, Journal of hazardous materials.

[9]  V. Lehsten,et al.  Modelling burned area in Africa , 2010 .

[10]  Shuwen Zhang,et al.  A MODIS time series data based algorithm for mapping forest fire burned area , 2013, Chinese Geographical Science.

[11]  P. Brando,et al.  Droughts, Wildfires, and Forest Carbon Cycling: A Pantropical Synthesis , 2019, Annual Review of Earth and Planetary Sciences.

[12]  A. Taylor,et al.  Spatial and temporal variation of fire regimes in a mixed conifer forest landscape, Southern Cascades, California, USA , 2001 .

[13]  Samira Nourbakhshbeidokhti,et al.  Effect of storms during drought on post‐wildfire recovery of channel sediment dynamics and habitat in the southern California chaparral, USA , 2017 .

[14]  Hanqiu Xu Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery , 2006 .

[15]  M. H. Costa,et al.  Predicting land cover changes in the Amazon rainforest: An ocean‐atmosphere‐biosphere problem , 2012 .

[16]  E. Davidson,et al.  Abrupt increases in Amazonian tree mortality due to drought–fire interactions , 2014, Proceedings of the National Academy of Sciences.

[17]  Clement Atzberger,et al.  First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe , 2016, Remote. Sens..

[18]  B. Soares-Filho,et al.  The gathering firestorm in southern Amazonia , 2019, Science Advances.

[19]  J. Anitha,et al.  Change detection techniques for remote sensing applications: a survey , 2019, Earth Science Informatics.

[20]  A. Daniels,et al.  Conversion or conservation? Understanding wetland change in northwest Costa Rica. , 2008, Ecological applications : a publication of the Ecological Society of America.

[21]  Gabriel Navarro,et al.  Evaluation of forest fire on Madeira Island using Sentinel-2A MSI imagery , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[22]  R. Bradstock,et al.  Defining pyromes and global syndromes of fire regimes , 2013, Proceedings of the National Academy of Sciences.

[23]  J. Cihlar,et al.  Relation between the normalized difference vegetation index and ecological variables , 1991 .

[24]  F. Putz,et al.  Fire, fragmentation, and windstorms: A recipe for tropical forest degradation , 2018, Journal of Ecology.

[25]  Diana C. S. Vieira,et al.  Mulching-induced preservation of soil organic matter quality in a burnt eucalypt plantation in central Portugal. , 2019, Journal of environmental management.

[26]  A. Mayor,et al.  Post-fire hydrological and erosional responses of a Mediterranean landscpe: Seven years of catchment-scale dynamics , 2007 .

[27]  N. Coops,et al.  Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada. , 2010 .

[28]  Maycira Costa,et al.  Large-scale habitat mapping of the Brazilian Pantanal wetland: A synthetic aperture radar approach , 2014 .

[29]  J. Keizer,et al.  Hydrologic Implications of Post‐Fire Mulching Across Different Spatial Scales , 2016 .

[30]  J. Barlow,et al.  AVIFAUNAL RESPONSES TO SINGLE AND RECURRENT WILDFIRES IN AMAZONIAN FORESTS , 2004 .

[31]  I. Bergier,et al.  Dynamics of the Pantanal Wetland in South America , 2016 .

[32]  Juan Carlos Castilla-Rubio,et al.  Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm , 2016, Proceedings of the National Academy of Sciences.

[33]  T. Kozlowski Physiological ecology of natural regeneration of harvested and disturbed forest stands: implications for forest management , 2002 .

[34]  S. Stephens,et al.  The Effects of Forest Fuel-Reduction Treatments in the United States , 2012 .

[35]  P. Brando,et al.  Lowland tapirs facilitate seed dispersal in degraded Amazonian forests , 2019, Biotropica.

[36]  Jos Barlow,et al.  Clarifying Amazonia's burning crisis , 2019, Global change biology.

[37]  Weiwei Sun,et al.  A Hierarchical Classification Framework of Satellite Multispectral/Hyperspectral Images for Mapping Coastal Wetlands , 2019, Remote. Sens..

[38]  Yijun Wang,et al.  Remote Sensing Approach to Detect Burn Severity Risk Zones in Palo Verde National Park, Costa Rica , 2018, Remote. Sens..

[39]  C. Woodcock,et al.  Continuous change detection and classification of land cover using all available Landsat data , 2014 .

[40]  K. Wantzen,et al.  Biodiversity in the Pantanal Wetland, Brazil. , 2001 .

[41]  B. Soares-Filho,et al.  Moment of truth for the Cerrado hotspot , 2017, Nature Ecology &Evolution.

[42]  Qiang Zhou,et al.  Monitoring Landscape Dynamics in Central U.S. Grasslands with Harmonized Landsat-8 and Sentinel-2 Time Series Data , 2019, Remote. Sens..

[43]  William Stafford Noble,et al.  Support vector machine , 2013 .

[44]  R. Cerrillo,et al.  Aplicación de escenas Landsat a la asignación de grados de afectación producidos por incendios forestales , 2002 .

[45]  Swanni T. Alvarado,et al.  Drivers of fire occurrence in a mountainous Brazilian cerrado savanna: tracking long-term fire regimes using remote sensing , 2017 .

[46]  A. Jordán,et al.  Effect of a wildfire and of post-fire restoration actions in the organic matter structure in soil fractions. , 2020, The Science of the total environment.

[47]  C. DaCamara,et al.  Near- and Middle-Infrared Monitoring of Burned Areas from Space , 2019, Satellite Information Classification and Interpretation.

[48]  Peter R. Robichaud,et al.  Current research issues related to post-wildfire runoff and erosion processes , 2013 .

[49]  Xiaojian Hu,et al.  The association between prenatal exposure to organochlorine pesticides and thyroid hormone levels in newborns in Yancheng, China. , 2014, Environmental research.

[50]  R. Shakesby,et al.  Wildfire as a hydrological and geomorphological agent , 2006 .

[51]  Feng Zhao,et al.  Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem , 2017 .

[52]  John W. Jones,et al.  Wetland Fire Scar Monitoring and Analysis Using Archival Landsat Data for the Everglades , 2013 .

[53]  Federico Filipponi,et al.  BAIS2: Burned Area Index for Sentinel-2 , 2018 .

[54]  E. Batista,et al.  Good fire, bad fire: It depends on who burns , 2020 .

[55]  G. Certini Effects of fire on properties of forest soils: a review , 2005, Oecologia.