Developing Forest Fire Danger index using NASA MODIS TERRA Near Real
Time satellite datasets
Abstract
Forest fire is a major ecological disaster, which has economic, social
and environmental impacts on humans and also causes the loss of
biodiversity. Forest officials issue the warnings to the public on the
basis of forest fire danger index classes. There is no operational
forest fire danger index for the country India due to the sparsely
distributed meteorological stations. The Fire Danger Rating System
(FDRS) is a Decision Support System, which takes into consideration of
all the factors affecting the fire danger such as fuel type, weather
parameters and terrain characteristics and indexing into different
classes of fire danger for the purpose of issuing warnings to the
public, implementing the mitigation measures for controlling fires. The
Static Fire Danger Index (SFDI) is a constant over the study area,
computed from the MODIS Land cover type yearly L3 global 500 m SIN grid
(MCD12Q1) and ASTER GDEM datasets. In this study, we used the Near Real
Time datasets and these Near Real time datasets are available within 3
hours of the observation time of satellite overpass, downloaded through
an FTP site. Dynamic Fire Danger Index has been calculated from the Near
Real Time (NRT) Level 2 MODIS Terra Land Surface Temperature datasets
(MOD11_L2) and MODIS TERRA NRT surface reflectance dataset MOD09 by
using three parameters, i.e. Potential surface temperature,
Perpendicular Moisture Index (PMI) and Modified Normalized Difference
Fire Index (MNDFI). Forest Fire Danger Index (FFDI) has been computed by
integrating the static fire danger index and individual dynamic forest
fire danger index on each day during the major fire episode of
Uttarakhand in 2016. The FFDI has been categorized into 5 fire danger
classes such as Very high, High, Moderate, Low and No fire danger and
MODIS active fire product MOD14 has been used for the validation.
Estimated accuracy was ranging from 72% to 91% and the overall
accuracy was around 81.27%. Therefore, the developed Forest Fire Danger
Index will be useful for the disseminating the danger maps daily in near
real time basis using the MODIS TERRA Near Real Time datasets so that
the fire officials to take necessary actions to control the spreading of
forest fires.