**1. Introduction**

176 Remote Sensing of Biomass – Principles and Applications

van Wagtendonk, J., Root, R., Key, C. and Running, S., 2004. Comparison of AVIRIS and

Veraverbeke, S., Verstraeten, W. W., Lhermitte, S. and Goossens, R., 2010a. Illumination effects

Veraverbeke, S., Lhermitte, S., Verstraeten, W. W. and Goossens, R., 2011a. A time-

Veraverbeke, S., Somers, B., Gitas, I., Katagis, T., Polychronaki, A. and Goossens, R., 2012a.

Veraverbeke, S., Gitas, I., Katagis, T., Polychronaki, A., Somers, B. and Goossens, R., 2012b.

Veraverbeke, S., Verstraeten, W. W., Lhermitte, S., Van De Kerchove, R. and Goossens, R.,

series of Landsat images. Remote Sensing of Environment 112: 3916-3934. Viedma, O., Melia, J., Segarra, D. and Garcia-Haro, J., 1997. Modeling rates of ecosystem recovery after fires by using Landsat TM data. Remote Sensing of Environment 61: 383-398. Vila, G. and Barbosa, P., 2010. Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM+ data. Ecological Modelling 221: 75-84. Wahren, C., Papst, W. and Williams, R., 2001. Early post-fire regeneration in subalpine

White, J., Ryan, K., Key, C. and Running, S., 1996. Remote sensing of forest fire severity and vegetation recovery. International Journal of Wildland Fire 6: 125-136. Wicks, T., Smith, G. and Curran, P., 2002. Polygon-based aggragation of remotely sensed

Wittenberg, L., Malkinson, D., Beeri, O., Halotzy, A. and Tesler, N., 2007. Spatial and

Wulder, M. A., White, J. C., Alvarez, F., Han, T., Rogan, J. and Hawkes, B., 2009.

Mediterranan landscape, Mt. Carmel Israel. Catena 71: 76-83.

Journal of Applied Earth Observation and Geoinformation 14: 1-11.

Wildland Fire 19: 75-93.

Wildland Fire 92: 397-408.

of Environment 114: 2548-2563.

Observation and Geoinformation 13: 52-58.

Photogrammetry and Remote Sensing in press.

Australia. Austral Ecology 26: 670-679.

Observation and Geoinformation 4: 161-173.

Remote Sensing of Environment 113: 1540–1555.

remotely sensed time series data in Spain, USA and Israel. International Journal of

Landsat ETM+ detection capabilities for burn severity. International Journal of

on the differenced Normalized Burn Ratio's optimality for assessing fire severity. International Journal of Applied Earth Observation and Geoinformation 12: 60-70. Veraverbeke, S., Lhermitte, S., Verstraeten, W. W. and Goossens, R., 2010b. The temporal

dimension of differenced Normalized Burn Ratio (dNBR) fire/burn severity studies: the case of the large 2007 Peloponnese wildfires in Greece. Remote Sensing

integrated MODIS burn severity assessment using the multi-temporal differenced Normalized Burn Ratio (dNBRMT). International Journal of Applied Earth

Spectral mixture analysis to assess post-fire vegetation regeneration using Landsat Thematic mapper imagery: accounting for soil brightness variation. International

Assessing post-fire vegetation recovery using red-near infrared vegetation indices: accounting for background and vegetation variability. ISPRS Journal of

2012c. Spaceborne assessment of post-fire changes in vegetation, land surface temperature and surface albedo. International Journal of Wildland Fire in press. Vicente-Serrano, S., Perez-Cabello, F. and Lasanta, T., 2008. Assessment of radiometric

correction techniques in analyzing vegetation variability and change using time

heathland and grassland in the Victorian Alpine National Park, south-eastern

data for regional ecological analysis. International Journal of Applied Earth

temporal patterns of vegetation recovery following sequences of forest fires in a

Characterizing boreal forest wildfire with multi-temporal Landsat and LIDAR data.

Biomass burning has been a topic of research interest for many years due to the implications for climatic change as a result of landscape alteration and atmospheric loading of aerosols and trace gases from pyrogenic emissions (Crutzen & Andreae, 1990). Crutzen et al. (1979) first highlighted the variety of trace gas emissions from tropical forest fires and the potential these constituents could have in altering atmospheric chemistry and biogeochemical cycles. Subsequent research has demonstrated additional impacts on the biosphere, atmosphere, and directly upon humans. For example, ozone (O3) is produced photochemically in the troposphere from hydrocarbon and nitrogen oxides released during vegetation burning and results in regional health hazards such as damage to human respiratory systems (Andreae, 2004; Levine, 2003). Cicerone (1994) emphasized that some byproducts of biomass burning, such as methyl chloride (CH3Cl) and methyl bromide (MeBr), can escape to the stratosphere where they are responsible for ozone destruction; resulting in health risks at a much larger scale.

Fire is an integral part of many ecosystems (Kuhry, 1994; Cary and Banks, 2000), but the nature of this relationship may change according to some climate models which show fire frequency and intensity increasing with global warming trends (Intergovernmental Panel on Climate Change [IPCC], 2007). For example, boreal forests, one of Earth's larger biomes, are a key component in global carbon cycling. In particular, peatland in boreal and sub-arctic regions of Earth are estimated to contain 455Gt of carbon, translating to roughly a third of the world's soil carbon pool (Brady & Weil, 1999; Gorham, 1991; Moore, 2002; Pastor et al., 2003), and act as a sink for atmospheric carbon; accounting for an uptake of roughly 12% of the global anthropogenic emissions (Moore, 2002). Carbon sequestered through the process of photosynthesis by living vegetation does not exit the boreal system at the same rate since respiration via decomposition is retarded. However combustion of organic matter contributes to atmospheric loading of "greenhouse" gases (Kaufman et al., 1990; Page et al., 2002) and can affect carbon sequestration regimes (Kasischke et al., 1995). In addition, the influence of anthropogenic ignited fires, which accounts for 90% of all biomass burning (Levine, 2000), may increase with population growth and the added pressure for land and resources. A result of these driving forces will be greater biomass burning emissions, decreased sequestration of carbon, and the potential creation of feedback loops (Kasischke et al., 1995a; Chapman and Thurlow, 1998; Moore, 2002).

The Science and Application of Satellite Based Fire Radiative Energy 179

area estimates using SPOT (Satellite Pour Observation de la Terra) imagery, during the 1997 Indonesian fire season. Legg & Laumonier (1999) also employed the United States Defense Meteorological Satellite Program (US DMSP) to help eliminate spurious daytime hotspots by detecting highly reflective pixels at night, presumably from fire, while excluding known human related bright spots. Kaufman et al. (1990) used AVHRR fire counts to assess trace gas and aerosol emissions in the tropics. Although some of the assumptions about burned area and fire detections would later be shown to be erroneous, their research set in motion the development of new approaches for using remotely sensed fire information for emission estimates (Kaufman, 1998). Aragão et al. (2007) examined drought and fire spatial distribution in Amazonia using NOAA-12's AVHRR and MODIS hot spot detections and later Aragão et al. (2008) examined specific interactions between precipitation, deforestation, and fires related to the 2005 Brazilian Amazon drought. More recently, Aragão & Shimabukuro (2010), again using MODIS and NOAA-12 hot spots, showed the co-varying nature of deforestation and fire activity trends over the past several years in the Brazilian Amazon. Their research has implications for fire and emission policies such as the United Nation's REDD+ (Reducing Emissions from Deforestation and Degradation). Giglio et al. (2010) used active fire detections to expand their burned area product to pre-MODIS data using the ATSR and Visible and Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM). The active fire burned area was developed using relationships based on regression between MODIS-Terra 500 meter burned area reference maps and Terra active fire counts. Morton et al. (2008) showed a clear correlation between fire hot spot frequency and land use patterns in Amazonia. Their research concluded that trends in land use intensity and fire frequency were linked. Such work offers promise for developing

monitoring schemes to characterize land use transitions to inform policy makers.

managers around the world.

discussed in more detail below.

**3.1 Burned area** 

**3. Combustion, fire energy, and emissions** 

In addition to the above research, a variety near-real time applications of active fire detections exist. The U.S. Forest Service Active Fire Mapping Program (http://activefiremaps.fs.fed.us/) is an operational system providing invaluable, near-real time information about location and timing of fire activity in the United States and Canada allowing fire managers to efficiently monitor fires and allocate resources. The Fire Information for Resource Management System (FIRMS, http://maps.geog.umd.edu/firms/) delivers timely fire detections, made by MODIS and processed through the Rapid Response System (http://rapidfire.sci.gsfc.nasa.gov/), to fire

Development of "new tools" such as fire radiative energy (FRE) can aid in estimating the biomass combusted and rates of atmospheric loading trace gases and aerosols. Calculated by determining the amount of energy emitted during fire, FRE may offer an accurate measurement of the fire intensity and vegetation consumed per unit time, as will be

In theory, remotely sensed data should offer the capability to directly quantify atmospheric emissions from fire events, but in practice this requires determining the source of emissions which involves complex, computationally demanding inversion and geochemical transport modeling. Therefore most current approaches, referred to as the "bottom up" method in this paper, involve multiplying the fuel consumed by an emission factor for the atmospheric

In order to understand the spatial and temporal global distribution of biomass burning, and ultimately the potential impacts to the biosphere and atmosphere, regular, broad scale monitoring is necessary. Satellite sensors provide daily, synoptic observations to detect and analyze fires (Justice et al., 2002) and therefore a great deal of research to characterize fires from remote sensing systems has been performed over the past several decades (e.g. Dozier, 1981; Kaufman et al., 1998; Giglio et al., 2003; Wooster et al., 2005; Ichoku & Kaufman, 2005).
