A Burned Area Mapping Algorithm for Chinese FengYun-3 MERSI Satellite Data

Biomass burning is a worldwide phenomenon, which emits large amounts of carbon into the atmosphere and strongly influences the environment. Burned area is an important parameter in modeling the impacts of biomass burning on the climate and ecosystem. The Medium Resolution Spectral Imager (MERSI) onboard FengYun-3C (FY-3C) has shown great potential for burned area mapping research, but there is still a lack of relevant studies and applications. This paper describes an automated burned area mapping algorithm that was developed using daily MERSI data. The algorithm employs time-series analysis and multi-temporal 1000-m resolution data to obtain seed pixels. To identify the burned pixels automatically, region growing and Support Vector Machine) methods have been used together with 250-m resolution data. The algorithm was tested by applying it in two experimental areas, and the accuracy of the results was evaluated by comparing them to reference burned area maps, which were interpreted manually using Landsat 8 OLI data and the MODIS MCD64A1 burned area product. The results demonstrated that the proposed algorithm was able to improve the burned area mapping accuracy at the two study sites.

[1]  K. P. Overmarsa,et al.  Spatial autocorrelation in multi-scale land use models , 2003 .

[2]  J. Cihlar,et al.  Hotspot and NDVI Differencing Synergy (HANDS): A New Technique for Burned Area Mapping over Boreal Forest , 2000 .

[3]  A. Smith,et al.  Production of Landsat ETM+ reference imagery of burned areas within Southern African savannahs: comparison of methods and application to MODIS , 2007 .

[4]  J. Randerson,et al.  Global estimation of burned area using MODIS active fire observations , 2005 .

[5]  Lorraine Remer,et al.  Detection of forests using mid-IR reflectance: an application for aerosol studies , 1994, IEEE Trans. Geosci. Remote. Sens..

[6]  D. Roy,et al.  An active-fire based burned area mapping algorithm for the MODIS sensor , 2009 .

[7]  E. Chuvieco,et al.  Assessment of multitemporal compositing techniques of MODIS and AVHRR images for burned land mapping , 2005 .

[8]  Ana C. L. Sá,et al.  An estimate of the area burned in southern Africa during the 2000 dry season using SPOT-VEGETATION satellite data , 2003 .

[9]  Piermaria Corona,et al.  Remote sensing support for post fire forest management , 2008 .

[10]  Shan Hai-bin Zhong Ru-xiang Zhao Wen-hua.  The Normalized Difference Thermal Index(NDTI) for the MODIS Fire Detection , 2007 .

[11]  Mariano García,et al.  Assessment of the potential of SAC-C/MMRS imagery for mapping burned areas in Spain , 2004 .

[12]  K. Tansey,et al.  Relationship between MODIS fire hot spot count and burned area in a degraded tropical peat swamp forest in Central Kalimantan, Indonesia , 2008 .

[13]  P. Crutzen,et al.  Estimates of gross and net fluxes of carbon between the biosphere and the atmosphere from biomass burning , 1980 .

[14]  Isabel María del Águila Cano,et al.  Burned Area Mapping in the North American Boreal Forest Using Terra-MODIS LTDR (2001-2011): A Comparison with the MCD45A1, MCD64A1 and BA GEOLAND-2 Products , 2014, Remote. Sens..

[15]  Emilio Chuvieco,et al.  BAMS: A Tool for Supervised Burned Area Mapping Using Landsat Data , 2014, Remote. Sens..

[16]  P. Goovaerts,et al.  Uncertainty in estimating carbon emissions from boreal forest fires , 2004 .

[17]  J. Pereira,et al.  Vegetation burning in the year 2000: Global burned area estimates from SPOT VEGETATION data , 2004 .

[18]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[19]  Nikos Koutsias,et al.  A rule-based semi-automatic method to map burned areas: exploring the USGS historical Landsat archives to reconstruct recent fire history , 2013 .

[20]  Shengli Wu,et al.  A new model for fire forecast , 2010, Remote Sensing.

[21]  José M. C. Pereira,et al.  An algorithm for mapping burnt areas in Australia using SPOT-VEGETATION data , 2003, IEEE Trans. Geosci. Remote. Sens..

[22]  Beniamino Murgante,et al.  Article in Press G Model International Journal of Applied Earth Observation and Geoinformation Multiscale Mapping of Burn Area and Severity Using Multisensor Satellite Data and Spatial Autocorrelation Analysis , 2022 .

[23]  S. Hook,et al.  Evaluating spectral indices for burned area discrimination using MODIS/ASTER (MASTER) airborne simulator data , 2011 .

[24]  E. Chuvieco,et al.  Global burned area mapping from ENVISAT-MERIS and MODIS active fire data , 2015 .

[25]  Hidefumi Imura,et al.  An automatic method for burn scar mapping using support vector machines , 2009 .

[26]  Fabiana Calò,et al.  Integration of Optical and SAR Data for Burned Area Mapping in Mediterranean Regions , 2015, Remote. Sens..

[27]  D. Roy,et al.  The MODIS fire products , 2002 .

[28]  Mathur Manish.  Autocorrelation Simulation Studies for Horizontal Transmission of Ethno- Medicinal-Knowledge Related with Two Corporeal Systems , 2013 .

[29]  P. Gessler,et al.  Evaluation of novel thermally enhanced spectral indices for mapping fire perimeters and comparisons with fire atlas data , 2005 .

[30]  N. Koutsias,et al.  Burned area mapping using logistic regression modeling of a single post-fire Landsat-5 Thematic Mapper image , 2000 .

[31]  C. O. Justicea,et al.  The MODIS fire products , 2002 .

[32]  José M. C. Pereira,et al.  A Rule-Based System for Burned Area Mapping in Temperate and Tropical Regions Using NOAA/AVHRR Imagery , 2000 .

[33]  S. Plummer,et al.  Burnt area detection at global scale using ATSR‐2: The GLOBSCAR products and their qualification , 2004 .

[34]  D. Roy,et al.  Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data , 2005 .

[35]  J. Grégoire,et al.  The GBA2000 initiative: Developing a global burnt area database from SPOT-VEGETATION imagery , 2003 .

[36]  Ioannis B. Theocharis,et al.  Burned Area Mapping Using Support Vector Machines and the FuzCoC Feature Selection Method on VHR IKONOS Imagery , 2014, Remote. Sens..

[37]  Wang Zhao.  Research and evaluation of the algorithm of land surface fire detection based on FY3-VIRR data , 2011 .

[38]  A. Huete.  A soil-adjusted vegetation index (SAVI) , 1988 .

[39]  E. Chuvieco,et al.  Generation of long time series of burn area maps of the boreal forest from NOAA–AVHRR composite data , 2008 .

[40]  Paula D. Blanco,et al.  Semi-automated mapping of burned areas in semi-arid ecosystems using MODIS time-series imagery , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[41]  Gloria Bordogna,et al.  A method for extracting burned areas from Landsat TM/ETM+ images by soft aggregation of multiple Spectral Indices and a region growing algorithm , 2012 .

[42]  Ioannis Z. Gitas,et al.  Burned Area Mapping in Greece Using SPOT-4 HRVIR Images and Object-Based Image Analysis , 2012, Remote. Sens..

[43]  Ioannis Z. Gitas,et al.  Object-based image classification for burned area mapping of Creus Cape, Spain, using NOAA-AVHRR imagery , 2004 .

[44]  D. Roy,et al.  Burned area mapping using multi-temporal moderate spatial resolution data—a bi-directional reflectance model-based expectation approach , 2002 .

[45]  P. Crutzen,et al.  Biomass Burning in the Tropics: Impact on Atmospheric Chemistry and Biogeochemical Cycles , 1990, Science.

[46]  I. Gitas,et al.  An automated two-step NDVI-based method for the production of low-cost historical burned area map records over large areas , 2014 .

[47]  Robert H. Fraser,et al.  SPOT VEGETATION for characterizing boreal forest fires , 2000 .

[48]  Ruth S. DeFries,et al.  The Global Fire Emissions Database (GFED4) Burned Area Data Set , 2012 .

[49]  Steven P. Brumby,et al.  Quantifying tree mortality in a mixed species woodland using multitemporal high spatial resolution satellite imagery , 2013 .

[50]  Joel S. Levine,et al.  Satellite analysis of the severe 1987 forest fires in northern China and southeastern Siberia , 1994 .

[51]  Alan H. Strahler,et al.  Global land cover mapping from MODIS: algorithms and early results , 2002 .

[52]  H. Eva,et al.  Burnt area mapping in Central Africa using ATSR data , 1998 .

[53]  S. K. McFeeters.  The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features , 1996 .

[54]  Dirk H. Hoekman,et al.  PALSAR Wide-Area Mapping of Borneo: Methodology and Map Validation , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.