# Post-Fire Vegetation Succession and Surface Energy Fluxes Derived from Remote Sensing
## 1 Introduction  
Fires are an integral component of forest ecosystems and the global carbon cycle; through combustion, they release approximately 7% of the net carbon total from vegetation into the atmosphere [1]. High-latitude boreal forests will be more affected by climate warming, as the fire frequency and burn areas will dramatically increase with the extension of the growing season. The fire season will be extended by approximately 20-30% [2; 3; 4]. Historical fire data statistics in China showthat the area of boreal forest fires occupies approximately 35% of the national burn area; thus, the forest-fire frequency in Chinese boreal forests will increase by 100-200% over the next 100 years [5; 6]. Currently, it has been confirmed that fires release significant amounts of carbon into the atmosphere through combustion; however, less is known regarding the effects of vegetation succession following fires on the ecosystem carbon flux (C-flux), which has potential feedback effects that may lengthen adjustments to regional and global ecosystem carbon cycles and further influence climate change. Boreal forests landscape is shaped by fire disturbances and the site's environment to some extent, which affect the forests' composition, structure, spatial distribution and carbon reserves [7; 8]. First, fire disturbances drive landscape changes through causing damage to large areas of vegetation. Second, hydrothermal environments primarily control where and which types of tree species grow in post-fire forest areas. The short growing seasons at high latitudes limits annual tree growth and severe winters control the cycle of forest succession. Thus, fires drive the occurrence of succession. The succession process can, in turn, adjust the essential ecosystem capacity and services that are provided by post-fire boreal forests, which are controlled by diverse patches that vary with age, species composition and productivity. However, few studies have assessed the interaction between seasonality and fire-provoked disturbances [9; 10]. Such effects might be particularly prevalent given the four distinct seasons in Chinese boreal forest areas. For example, extended periods of snow cover heavily influences both vegetation activity and recovery time; ultimately, such changes modify the energy fluxes. Therefore, a detailed record of post-fire boreal forest recovery and hydrothermal environments is crucial to understanding the disturbances in ecosystem services and succession processes. Although post-fire forest recovery has been demonstrated through field surveys in ecological studies [11; 12; 13], the time and space limitations of field-investigation methods have limited their extent, especially under the context of climate change. Remote sensing offers considerable potential for the inversion of the regeneration trajectory of post-fire forests via time-series data or remote sensing indices, such as the normalized difference vegetation index (NDVI) [14; 15], the enhanced vegetation index (EVI) [16], and the normalized difference shortwave infrared index (NDSWIR) [17], alongside the albedo [9], land-surface temperature (LST) [18], net primary productivity (NPP) [19], fractional vegetation coverage (FVC) [20] and fraction of absorbed photosynthetically active radiation (FAPAR) [21]. A common indicator such as the NDVI, whose recovery trajectory equates to vegetation restoration, may not be ideal as a realistic and unbiased representative index. [PERSON] used time-series AVHIR-NDVI data to study forest successions after a fire in Alaska and found that the NDVI increased and reached its maximum after 20-50 years [22]. [PERSON] used the GIMMS-NDVI to investigate the recovery of vegetation after fires in the boreal forests of Canada and found that the recovery time was five years, consistently shorter than results from previous studies [23].