Active fires illuminated on the earth surface are caught by the satellite. These fires are created by various sources such as vegetation fires, gas flares, biomass burning, volcanoes, and industrial sites such as steel mills. Near real time active fire data is collected using remote sensing techniques of satellites. Amount of active fires in an area is a proxy indicator of aerosols, green houses gases and trace gases. Here the behavior of active fires over a period of one year in Nepal, Bhutan and Srilanka are studied using spatial statistics. This study is based on data acquired through remote sensing of data acquisition platform, NASA’s MODIS. Spatial statistics is used here to study the incidence of active fires with respect to geographical location. The behavior of parameters of various autoregressive models like Spatial Durban Model, Spatial Lag Model, Spatial Error Model, Manski Model and Kelegian Prucha Model are minutely analyzed. The best model with highest pseudo R2 is selected. The spatial behavior of the fire radiative power for three countries is also predicted using spatial interpolation and kriging. So the burning potential of vegetations in unsampled areas is envisaged by thus predicting FRP. Such studies give a country wise perspective to the behavior of fire; this is with reference to south Asia. They are of great importance for countries of developing world which lack a strong backbone of good quality official records. Through the statistical analyses of data collected by such platforms, important information can be indirectly assessed.