Satellite Observation of Biomass Burning Implications in Global Change Research

Biomass burning, which involves wildland fires as well as agricultural and grassland burnings, plays a critical role in the environmental equilibrium of our planet, since it is a major driving force in land cover transformations and contributes significantly to greenhouse gas emissions. Several satellite missions provide critical information required to better understand the temporal and spatial distribution of biomass burning. Satellite images provide objective and comprehensive informa- tion on global patterns of fire occurrence, as well as data on factors affecting fire ignition and propagation. Recent improvements in spatial, temporal, and spectral resolution of satellite remote sensing systems reduce past uncertainties - systems can now be used to obtain a more precise evaluation of burned areas and post-fire effects on soils and plants. Greater efforts are required to operationally use Earth Observation data in fire prevention and early warning. Longer time series data are required to acquire a better understanding of fire regimes, and their mutual relation- ships with global warming.

[1]  J. E. Spencer,et al.  Shifting Cultivation in Southeastern Asia , 1968 .

[2]  D. Thompson,et al.  Using Landsat digital data to detect moisture stress , 1979 .

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

[4]  G. R. Minick,et al.  Comparison of Satellite Imagery and Conventional Aerial Photography in Evaluating a Large Forest Fire , 1981 .

[5]  S. Idso,et al.  Canopy temperature as a crop water stress indicator , 1981 .

[6]  J. Dozier A method for satellite identification of surface temperature fields of subpixel resolution , 1981 .

[7]  B. Holben,et al.  Leaf water stress detection utilizing thematic mapper bands 3, 4 and 5 in soybean plants , 1983 .

[8]  R. Burgan,et al.  BEHAVE : Fire Behavior Prediction and Fuel Modeling System -- FUEL Subsystem , 1984 .

[9]  G. Woodwell,et al.  Net flux of carbon dioxide from tropical forests in 1980 , 1985, Nature.

[10]  T. H. Haar,et al.  Forest fire monitoring using NOAA satellite AVHRR , 1986 .

[11]  P. Nixon,et al.  Canopy reflectance of two drought-stressed shrubs , 1986 .

[12]  B. Holben,et al.  Satellite detection of tropical burning in Brazil , 1987 .

[13]  B. Rock,et al.  Measurement of leaf relative water content by infrared reflectance , 1987 .

[14]  M. Matson,et al.  Fire detection using data from the NOAA-N satellites , 1987 .

[15]  J. Brass,et al.  Thermal analysis of wildfires and effects on global ecosystem cycling , 1988 .

[16]  E. Chuvieco,et al.  Mapping and inventory of forest fires from digital processing of tm data , 1988 .

[17]  R. Saunders,et al.  An improved method for detecting clear sky and cloudy radiances from AVHRR data , 1988 .

[18]  J. Barber,et al.  Monitoring grassland dryness and fire potential in australia with NOAA/AVHRR data , 1988 .

[19]  W. Oechel,et al.  A simple method for estimating fire intensity after a burn in california usa chaparral , 1989 .

[20]  P. Mausel,et al.  Assessment of vegetation change in a fire-altered forest landscape. , 1990 .

[21]  Y. Kaufman,et al.  Satellite measurements of large-scale air pollution - Measurements of forest fire smoke , 1990 .

[22]  V. Caselles,et al.  Mapping burns and natural reforestation using thematic Mapper data , 1991 .

[23]  J. Levine Biomass Burning: Its History, Use, and Distribution and Its Impact on Environmental Quality and Global Climate , 1991 .

[24]  E. Prins,et al.  Geostationary satellite detection of bio mass burning in South America , 1992 .

[25]  S. Langaas Temporal and Spatial Distribution of Savanna Fires in Senegal and The Gambia, West Africa, 1989-90, Derived from Multi-temporal AVHRR Night Images , 1992 .

[26]  B. Holben,et al.  Biomass Burning Airborne and Spaceborne Experiment in the Amazonas (BASE-A) , 1992 .

[27]  C. Tucker,et al.  Tropical Deforestation and Habitat Fragmentation in the Amazon: Satellite Data from 1978 to 1988 , 1993, Science.

[28]  R. H. Haas,et al.  Evaluating Landsat Thematic Mapper derived vegetation indices for estimating above-ground biomass on semiarid rangelands , 1993 .

[29]  A. Vidal,et al.  Evaluation of a temporal fire risk index in mediterranean forests from NOAA thermal IR , 1994 .

[30]  P. Kennedy,et al.  An improved approach to fire monitoring in West Africa usingAVHRR data , 1994 .

[31]  M. S. Moran,et al.  Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index , 1994 .

[32]  J. Faundeen,et al.  The 1 km AVHRR global land data set: first stages in implementation , 1994 .

[33]  Zhiliang Zhu,et al.  US forest types and predicted percent forest cover from AVHRR data , 1994 .

[34]  S. Pyne World Fire: The Culture of Fire on Earth , 1995 .

[35]  M. Nunez,et al.  Assessing Grassland Moisture and Biomass in Tasmania - the Application of Remote-Sensing and Empirical-Models for a Cloudy Environment , 1995 .

[36]  P. Siljestrom Ribed,et al.  Monitoring burnt areas by principal components analysis of multi-temporal TM data , 1995 .

[37]  E. Kasischke,et al.  Locating and estimating the areal extent of wildfires in alaskan boreal forests using multiple-season AVHRR NDVI composite data , 1995 .

[38]  C. Skinner,et al.  An Assessment of Factors Associated with Damage to Tree Crowns from the 1987 Wildfires in Northern California , 1995, Forest Science.

[39]  A. Beaudoin,et al.  Monitoring the water status of Mediterranean forests using ERS-1, to support fire risk prevention , 1995, 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications.

[40]  E. Chuvieco,et al.  Estimating temporal dynamics of fuel moisture content of Mediterranean species from NOAA-AVHRR data , 1996 .

[41]  W. Hao,et al.  Emissions of CO2, CO, and hydrocarbons from fires in diverse African savanna ecosystems , 1996 .

[42]  S. Running,et al.  Remote Sensing of Forest Fire Severity and Vegetation Recovery , 1996 .

[43]  Pietro Ceccato,et al.  A contextual algorithm for AVHRR fire detection , 1996 .

[44]  J. Peñuelas,et al.  Estimation of plant water concentration by the reflectance Water Index WI (R900/R970) , 1997 .

[45]  M. Dobson,et al.  The use of Imaging radars for ecological applications : A review , 1997 .

[46]  T. Faurtyot Vegetation water and dry matter contents estimated from top-of-the-atmosphere reflectance data: A simulation study , 1997 .

[47]  M. Petit,et al.  An improved detection and characterization of active fires and smoke plumes in south-eastern Africa and Madagascar , 1998 .

[48]  D. Blake,et al.  Emission factors of hydrocarbons, halocarbons, trace gases and particles from biomass burning in Brazil , 1998 .

[49]  E. Prins,et al.  An overview of GOES‐8 diurnal fire and smoke results for SCAR‐B and 1995 fire season in South America , 1998 .

[50]  R. Burgan,et al.  Evaluation of NDVI for monitoring live moisture in three vegetation types of the Western U.S. , 1999 .

[51]  P. Barbosa,et al.  An Algorithm for Extracting Burned Areas from Time Series of AVHRR GAC Data Applied at a Continental Scale , 1999 .

[52]  M. Karteris,et al.  Burnt land mapping at local scale , 1999 .

[53]  D. Roy Multi-temporal active-fire based burn scar detection algorithm , 1999 .

[54]  Jose M. Cardoso Pereira,et al.  An assessment of vegetation fire in Africa (1981–1991): Burned areas, burned biomass, and atmospheric emissions , 1999 .

[55]  M. Nilsson,et al.  Regional forest biomass and wood volume estimation using satellite data and ancillary data , 1999 .

[56]  João M. N. Silva,et al.  Spectral characterisation and discrimination of burnt areas , 1999 .

[57]  W. Hao,et al.  Seasonality of carbon emissions from biomass burning in a Zambian savanna , 1999 .

[58]  M. D. Rutherford,et al.  Evaluation of ERS SAR data for prediction of fire danger in a Boreal region , 1999 .

[59]  P. Ceccato,et al.  Fire detection and fire growth monitoring using satellite data , 1999 .

[60]  José M. C. Pereira,et al.  A comparative evaluation of NOAA/AVHRR vegetation indexes for burned surface detection and mapping , 1999, IEEE Trans. Geosci. Remote. Sens..

[61]  E. Salinero Remote sensing of large wildfires in the European Mediterranean Basin , 1999 .

[62]  D. Nepstad,et al.  Positive feedbacks in the fire dynamic of closed canopy tropical forests , 1999, Science.

[63]  J. E. Dobson,et al.  LandScan: A Global Population Database for Estimating Populations at Risk , 2000 .

[64]  E. Dwyer,et al.  Characterization of the spatio‐temporal patterns of global fire activity using satellite imagery for the period April 1992 to March 1993 , 2000 .

[65]  J. Grégoire,et al.  The Global Fire Product: Daily fire occurrence from April 1992 to December 1993 derived from NOAA AVHRR data , 2000 .

[66]  M. Verstraete,et al.  Biomass burning and its inter-relationships with the climate system , 2000 .

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

[68]  J. Levine Global Biomass Burning: A Case Study of the Gaseous and Particulate Emissions Released to the Atmosphere During the 1997 Fires in Kalimantan and Sumatra, Indonesia , 2000 .

[69]  X. Pons,et al.  A semi-automatic methodology to detect fire scars in shrubs and evergreen forests with Landsat MSS time series , 2000 .

[70]  M. Fulk,et al.  Comparison of NOAA-AVHRR and DMSP-OLS for operational fire monitoring in Kalimantan, Indonesia , 2000 .

[71]  P. Brivio,et al.  Modelling the Impact of Vegetation Fires, Detected from NOAA-AVHRR Data, on Tropospheric Chemistry in Tropical Africa , 2000 .

[72]  J. Cihlar,et al.  Satellite-based detection of Canadian boreal forest fires: Development and application of the algorithm , 2000 .

[73]  T. Toutin,et al.  Stereo RADARSAT Data for Canopy Height in Brazilian Forests , 2000 .

[74]  J. Hyyppä,et al.  Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes , 2000 .

[75]  J. Franklin,et al.  Mapping Wildfire Burn Severity in Southern California Forests and Shrublands Using Enhanced Thematic Mapper Imagery , 2001 .

[76]  S. Tarantola,et al.  Detecting vegetation leaf water content using reflectance in the optical domain , 2001 .

[77]  R. Pu,et al.  Spectroscopic determination of wheat water status using 1650-1850 nm spectral absorption features , 2001 .

[78]  F. J. García-Haro,et al.  Monitoring fire-affected areas using Thematic Mapper data , 2001 .

[79]  C. Elvidge,et al.  DMSP-OLS estimation of tropical forest area impacted by surface fires in Roraima, Brazil: 1995 versus 1998 , 2001 .

[80]  J. Cuevas,et al.  Comparison of the use of WiFS and LISS images to estimate the area burned in a large forest fire , 2001 .

[81]  C. Justice,et al.  Global and Regional Vegetation Fire Monitoring from Space: Planning a Coordinated International Effort , 2001 .

[82]  K. Ranson,et al.  Characterization of Forests in Western Sayani Mountains, Siberia from SIR-C SAR Data , 2001 .

[83]  R. M. Nelson Water Relations of Forest Fuels , 2001 .

[84]  A. Setzer,et al.  AVHRR analysis of a savanna site through a fire season in Brazil , 2001 .

[85]  Alexandros Dimitrakopoulos,et al.  Flammability Assessment of Mediterranean Forest Fuels , 2001 .

[86]  E. Johnson,et al.  Forest fires : behavior and ecological effects , 2001 .

[87]  P. Fearnside,et al.  Burning of Amazonian rainforests: burning efficiency and charcoal formation in forest cleared for cattle pasture near Manaus, Brazil , 2001 .

[88]  F. Siegert,et al.  ERS SAR backscatter: a potential real-time indicator of the proneness of modified rainforests to fire , 2001 .

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

[90]  E. Kasischke,et al.  Fire Danger Monitoring Using ERS-1 SAR Images in the Case of Northern Boreal Forests , 2002 .

[91]  Consejo Superior de Investigaciones,et al.  Burned land mapping using NOAA-AVHRR and TERRA-MODIS. , 2002 .

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

[93]  M. Maggi,et al.  Advantages and drawbacks of NOAA-AVHRR and SPOT-VGT for burnt area mapping in a tropical savanna ecosystem , 2002 .

[94]  C. Justice,et al.  A framework for the validation of MODIS Land products , 2002 .

[95]  A. Viña,et al.  Drought Monitoring with NDVI-Based Standardized Vegetation Index , 2002 .

[96]  Jay D. Miller,et al.  Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data , 2002 .

[97]  D. Riaño,et al.  Generation of fuel type maps from Landsat TM images and ancillary data in Mediterranean ecosystems , 2002 .

[98]  I. Sandholt,et al.  A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status , 2002 .

[99]  E. Chuvieco,et al.  Assessment of different spectral indices in the red-near-infrared spectral domain for burned land discrimination , 2002 .

[100]  D. Roy,et al.  An overview of MODIS Land data processing and product status , 2002 .

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

[102]  D. Riaño,et al.  Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data: Applications in fire danger assessment , 2002 .

[103]  D. Riaño,et al.  Fuel loads and fuel type mapping , 2003 .

[104]  E. Lorenz,et al.  Fire recognition potential of the bi-spectral Infrared Detection (BIRD) satellite , 2003 .

[105]  E. Chuvieco,et al.  Integration of Physical and Human Factors in Fire Danger Assessment , 2003 .

[106]  S. Ustin,et al.  Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling , 2003 .

[107]  J. Kendall,et al.  A multi-year active fire dataset for the tropics derived from the TRMM VIRS , 2003 .

[108]  J. C. Price Comparing MODIS and ETM+ data for regional and global land classification , 2003 .

[109]  Stephen E. Dunagan,et al.  Demonstrating UAV-acquired real-time thermal data over fires , 2003 .

[110]  D. Riaño,et al.  Design of an empirical index to estimate fuel moisture content from NOAA-AVHRR images in forest fire danger studies. , 2003 .

[111]  Estimation of Live Fuel Moisture Content , 2003 .

[112]  D. Sims,et al.  Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features , 2003 .

[113]  João M. N. Silva,et al.  Evaluating the performance of multitemporal image compositing algorithms for burned area analysis , 2003 .

[114]  Yoram J. Kaufman,et al.  An Enhanced Contextual Fire Detection Algorithm for MODIS , 2003 .

[115]  S. Ustin,et al.  Water content estimation in vegetation with MODIS reflectance data and model inversion methods , 2003 .

[116]  E. Chuvieco Wildland Fire Danger Estimation and Mapping: The Role of Remote Sensing Data , 2003 .

[117]  R. Keane,et al.  MAPPING FUELS AND FIRE REGIMES USING REMOTE SENSING, ECOSYSTEM SIMULATION, AND GRADIENT MODELING , 2004 .

[118]  J. Moreno,et al.  Methods for quantifying fire severity in shrubland-fires , 1998, Plant Ecology.

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

[120]  E. Chuvieco,et al.  Improving burning efficiency estimates through satellite assessment of fuel moisture content , 2004 .

[121]  D. Roy,et al.  Modeling and sensitivity analysis of fire emissions in southern Africa during SAFARI 2000 , 2004 .

[122]  David S. Pilliod,et al.  Tongue-tied: Confused meanings for common fire terminology can lead to fuels mismanagement , 2004 .

[123]  D. Riaño,et al.  Combining NDVI and surface temperature for the estimation of live fuel moisture content in forest fire danger rating , 2004 .

[124]  M. Deshayes,et al.  Estimation of foliage moisture content using near infrared reflectance spectroscopy , 2004 .

[125]  J. Grégoire,et al.  Lessons to be learned from the comparison of three satellite‐derived biomass burning products , 2004 .

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

[127]  J. W. Wagtendonk,et al.  Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity , 2004 .

[128]  J. Randerson,et al.  Continental-Scale Partitioning of Fire Emissions During the 1997 to 2001 El Niño/La Niña Period , 2003, Science.

[129]  E. Chuvieco,et al.  Remote sensing and geographic information systems methods for global spatiotemporal modeling of biomass burning emissions: Assessment in the African continent , 2004 .

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

[131]  F. M. Danson,et al.  Estimating live fuel moisture content from remotely sensed reflectance , 2004 .

[132]  S. Ustin,et al.  Generation of crown bulk density for Pinus sylvestris L. from lidar , 2004 .

[133]  P. Barbosa,et al.  Deriving global quantitative estimates for spatial and temporal distributions of biomass burning emissions , 2004 .

[134]  Yoram J. Kaufman,et al.  A technique for detecting burn scars using MODIS data , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[135]  E. Kasischke,et al.  AVHRR-based mapping of fires in Russia: New products for fire management and carbon cycle studies , 2004 .

[136]  K. Itten,et al.  LIDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management , 2004 .

[137]  Kelly K. Caylor,et al.  A simulation analysis of the detectability of understory burns in miombo woodlands , 2004 .

[138]  W. Cohen,et al.  Estimates of forest canopy height and aboveground biomass using ICESat , 2005 .

[139]  E. Chuvieco,et al.  Applying Local Measures of Spatial Heterogeneity to Landsat-TM Images for Predicting Wildfire Occurrence in Mediterranean Landscapes , 2006, Landscape Ecology.

[140]  D. Stow,et al.  MODIS‐derived visible atmospherically resistant index for monitoring chaparral moisture content , 2005 .

[141]  E. Chuvieco,et al.  Biomass Burning Emissions: A Review of Models Using Remote-Sensing Data , 2005, Environmental monitoring and assessment.

[142]  P. Fulé,et al.  Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data , 2005 .

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

[144]  D. Harding,et al.  ICESat waveform measurements of within‐footprint topographic relief and vegetation vertical structure , 2005 .

[145]  A. Belward,et al.  Characterizing interannual variations in global fire calendar using data from Earth observing satellites , 2005 .

[146]  Forest Fires: A Reference Handbook , 2005 .

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

[148]  D. Verbyla,et al.  Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM , 2005 .

[149]  D. Roberts,et al.  Combining spectral and spatial information to map canopy damage from selective logging and forest fires , 2005 .

[150]  T. Jackson,et al.  Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near- and short-wave infrared bands , 2005 .

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

[152]  C. Justice,et al.  Validation of the MODIS active fire product over Southern Africa with ASTER data , 2005 .

[153]  D. Roy,et al.  The Southern Africa Fire Network (SAFNet) regional burned‐area product‐validation protocol , 2005 .

[154]  Pablo J. Zarco-Tejada,et al.  Estimation of fuel moisture content by inversion of radiative transfer models to simulate equivalent water thickness and dry matter content: analysis at leaf and canopy level , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[155]  Fire emissions from C3 and C4 vegetation and their influence on interannual variability of atmospheric CO2 and δ13CO2 , 2005 .

[156]  C. Justice,et al.  Global fire activity from two years of MODIS data , 2005 .

[157]  D. Roberts,et al.  Use of Normalized Difference Water Index for monitoring live fuel moisture , 2005 .

[158]  Susan I. Stewart,et al.  The wildland-urban interface in the United States based on 125 million building locations. , 2005, Ecological applications : a publication of the Ecological Society of America.

[159]  D. Roy,et al.  Characterizing the surface heterogeneity of fire effects using multi‐temporal reflective wavelength data , 2005 .

[160]  J. Casanova,et al.  Fire detection and monitoring using MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI) data , 2006 .

[161]  C. Justice,et al.  Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors , 2006 .

[162]  O. Boucher,et al.  Emissions from open biomass burning in India: Integrating the inventory approach with high‐resolution Moderate Resolution Imaging Spectroradiometer (MODIS) active‐fire and land cover data , 2006 .

[163]  S. A. Lewis,et al.  Remote sensing techniques to assess active fire characteristics and post-fire effects , 2006 .

[164]  E. Kasischke,et al.  Recent changes in the fire regime across the North American boreal region—Spatial and temporal patterns of burning across Canada and Alaska , 2006 .

[165]  D. Roberts,et al.  Evaluation of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Moderate Resolution Imaging Spectrometer (MODIS) measures of live fuel moisture and fuel condition in a shrubland ecosystem in southern California , 2006 .

[166]  Jeffrey T. Morisette,et al.  Validation of active fire detection from moderate-resolution satellite sensors: the MODIS example in northern eurasia , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[167]  David P. Roy,et al.  Remote sensing of fire severity: assessing the performance of the normalized burn ratio , 2006, IEEE Geoscience and Remote Sensing Letters.

[168]  E. Chuvieco,et al.  Foliage moisture content estimation from one‐dimensional and two‐dimensional spectroradiometry for fire danger assessment , 2006 .

[169]  J. Randerson,et al.  Distinguishing between conversion and maintenance fires in the Amazon , 2006 .

[170]  F. Achard,et al.  Ecology: Human role in Russian wild fires , 2006, Nature.

[171]  J. Randerson,et al.  Interannual variability in global biomass burning emissions from 1997 to 2004 , 2006 .

[172]  J. Randerson,et al.  The Impact of Boreal Forest Fire on Climate Warming , 2006, Science.

[173]  F. M. Danson,et al.  Use of a radiative transfer model to simulate the postfire spectral response to burn severity , 2006 .

[174]  S. Ustin,et al.  Estimating Vegetation Water content with Hyperspectral data for different Canopy scenarios: Relationships between AVIRIS and MODIS Indexes , 2006 .

[175]  E. Chuvieco,et al.  Burn severity estimation from remotely sensed data: Performance of simulation versus empirical models , 2007 .

[176]  S. Ustin,et al.  Global spatial patterns and temporal trends of burned area between 1981 and 2000 using NOAA‐NASA Pathfinder , 2007 .

[177]  S. Ustin,et al.  Estimation of shrub height for fuel-type mapping combining airborne LiDAR and simultaneous color infrared ortho imaging , 2007 .

[178]  K. Halligan,et al.  Simulation Approaches for Burn Severity Estimation Using Remotely Sensed Images , 2007 .

[179]  D. Riaño,et al.  Estimation of live fuel moisture content from MODIS images for fire risk assessment , 2008 .