Spatial distribution of temporal dynamics in anthropogenic fires in miombo savanna woodlands of Tanzania

Table 3 Spectral indices used in fuzzy classification

Indices	Use
BAIM_L and MIRBI	Detect burned areas at different post-fire conditions
BAIM_L and threshold	Mask bare soil, water^a, topographic and cloud shadows
NBR_L and threshold	Distinguish active fires from other features
BAI	Detect burned areas on MSS imagery

\(BAI = 1/(\rho_{c2} - \rho_{2} )^{2} + (\rho_{c4} - \rho_{4} )^{2} ; \rho_{c2} = 0.1,\rho_{c4} = 0.06 .\)
\(BAIM_{L} = 1/(\rho_{c4} - \rho_{4} )^{2} + (\rho_{c7} - \rho_{7} )^{2} ; \rho_{c4} = 0.05,\rho_{c7} = 0.2 .\)
\(MIRBI = 10\times\rho_{7} - 9.8\times\rho_{5} + 2 .\)
\(NBR = (\rho_{4} - \rho_{7} )/(\rho_{4} + \rho_{7} ) .\)
\(\rho_{ 2} = {\text{Band 2 of MSS on Landsat 4-5 and Band 5 of MSS on Landsat 1-3}} .\)
\(\rho_{4} = {\text{Band 4 of MSS on Landsat 4-5, Band 7 of MSS on Landsat 1-3 and Band 4 of TM/ETM+ }} .\)
\(\rho_{7} = {\text{Band 7 of TM/ETM+ }} .\)
^aPermanent water bodies were manually masked out from fuzzy classification results.

ISSN: 1750-0680