## 1 Introduction  
Wildfires have occurred frequently throughout the world in the past few decades. This type of natural disaster has a serious impact on the ecological system and human lives. Fire also plays an important role in ecosystem succession [1], global carbon budget [2], climate cycles [3], and land cover change [4]. Since wildfires ruin the terrestrial vegetation layer, accurate burned area mapping is essential for disaster assessment, burned landscape management and vegetation recovery [5; 6; 7]. In recent years, the topic has become a research hotspot because of its important practical significance. The rapid development of satellite remote sensing technology provides an excellent chance to make full use of the advantages of satellites for burned area research. In comparison to manual field measurement of a burned area after wildfires, satellite remote sensing is more convenient, safe and applicable with fast response capability. So far, the satellite sensors applied to burned area research mainly consist of the VEGETATION (VEG) [8; 9; 10], Advanced Very High Resolution Radiometer (AVHRR) [2; 11; 12; 13; 14; 15], Moderate Resolution Imaging Spectroradiometer (MODIS) [1; 16; 17; 18; 19], Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) [20; 21; 22], Visible Infrared Imaging Radiometer Suite (VIIRS) [7], Thematic Mapper (TM) [5; 23; 24], Enhanced Thematic Mapper plus (ETM+) [24; 25; 26; 27], and Operational Land Imager (OLI) [28]. Besides, the availability of Synthetic Aperture Radar (SAR) for burned area mapping has also been investigated [29; 30; 25]. Among the satellite sensors, MODIS sensors onboard Terra and Aqua satellites have 36 spectral bands that cover from the visible region (0.4 \(\upmu\)m) to the thermal infrared region (TIR, 14.4 \(\upmu\)m) [31]. Moreover, the sensor can provide global and daily observations so that the MODIS data contains abundant information for wildfire assessment. In particular, the complex spectral characteristics of the burned area and unburned types of land cover (hereafter simply \"unburned types\") can also be obtained from the data. Therefore, the application of remote sensing technology with MODIS data for burned area mapping has been widely investigated in current research [4; 19; 32]. A variety of methods have been developed for burned area detection based on MODIS data. The traditional threshold-based methods were developed for wide use with a single satellite image. [PERSON] et al. [18] used false-color composition RGB images of MODIS bands 7, 5 and 6 to identify the burned area visually, and then developed an empirical formula to distinguish the burned areas from unburned areas. Methods based on multi-temporal satellite images and time series data were also proposed to evaluate the burned area. [PERSON] et al. [17] developed a regionally adaptable semi-automated algorithm based on the Normalized Burned Ratio differencing (dNBR) images derived from pre- and post-fire data, which adopted the MODIS Surface Reflectance 8-Day Composite product and MODIS Active Fire product to output the yearly maps of the burned area. [PERSON] et al. [16] proposed an algorithm that applied the dynamic thresholds to the images generated from burn-sensitive vegetation index (bsVI) and a measure of temporal texture, and cumulative active fire maps were also used to select the burned and unburned samples. [PERSON] et al. [19] developed a Bayesian-based algorithm to detect the burned area using the MODIS 10-day products of surface reflectance and land surface temperature (LST) data for the Canary Islands' dry woodlands and forests ecoregion. In addition, [PERSON] et al. [4] utilized the Collection 6 MODIS Global Burned Area Product (MCD64A1) of the global monthly record from 2003 to 2016 and the time series data of normalized burn ratio (NBR) to carry out a global analysis of the burned area persistence time. [PERSON] et al.