SCAR-B fires in the tropics: Properties and remote sensing from EOS-MODIS

Citation
Yj. Kaufman et al., SCAR-B fires in the tropics: Properties and remote sensing from EOS-MODIS, J GEO RES-A, 103(D24), 1998, pp. 31955-31968
Citations number
15
Categorie Soggetti
Earth Sciences
Volume
103
Issue
D24
Year of publication
1998
Pages
31955 - 31968
Database
ISI
SICI code
Abstract
Two moderate resolution imaging spectroradiometer (MODIS) instruments are p lanned for launch in 1999 and 2000 on the NASA Earth Observing System (EOS) AM-1 and EOS PM-1 satellites. The MODIS instrument will sense fires with d esignated 3.9 and 11 mu m channels that saturate at high temperatures (450 and 400 K, respectively). MODIS data will be used to detect fires, to estim ate the rate of emission of radiative energy from the fire, and to estimate the fraction of biomass burned in the smoldering phase. The rate of emissi on of radiative energy is a measure of the rate of combustion of biomass in the fires. In the Smoke, Clouds, and Radiation-Brazil (SCAR-B) experiment the NASA ER-2 aircraft flew the MODIS airborne simulator (MAS) to measure t he fire thermal and mid-IR signature with a 50 m spatial resolution. These data are used to observe the thermal properties and sizes of fires in the c errado grassland and Amazon forests of Brazil and to simulate the performan ce of the MODIS 1 km resolution fire observations. Although some fires satu rated the MAS 3.9 mu m channel, all the fires were well within the MODIS in strument saturation levels. Analysis of MAS data over different ecosystems, shows that the fire size varied from single MAS pixels (50 x 50 m) to over 1 km(2). The 1 x 1 km resolution MODIS instrument can observe only 30-40% of these fires, but the observed fires are responsible for 80 to nearly 100 % of the emitted radiative energy and therefore for 80 to 100% of the rate of biomass burning in the region. The rate of emission of radiative energy from the fires correlated very well with the formation of fire burn scars ( correlation coefficient = 0.97). This new remotely sensed quantity should b e useful in regional estimates of biomass consumption.