# Post-Fire Vegetation Succession and Surface Energy Fluxes Derived from Remote Sensing
## 1 Introduction
To avoid dependency on a single index, [PERSON] proposed a synergistic approach that used time series of the forest recovery index (FRI) and FVC to determine different stages of post-fire forest successions in a Siberian boreal larch forest [20]. However, the observations of these indices yielded inconsistent results, even within the same region [10]. Consequently, current data are specific to sites and substantially vary depending on the remote sensing indices that are adopted. Therefore, the selection of remote sensing indices to study forest-vegetation succession processes must be relevant and have a clear ecological significance. To date, however, very few studies have attempted to tie post-fire ground variables to a remotely sensed data index with different metrics and spatial and temporal scales in boreal forests [24]. Several works have summarized the effects of fire disturbances on land-surface energy fluxes [25; 26; 27]. [PERSON] observed that latent heat flux decreased over several years following fire disturbances in boreal forests [28]. However, not all results have shown a decreasing trend, depending on the burn severity, vegetation type and succession process. Important changes in the energy, temperature and water balance after burning were observed via eddy covariance measurements [29]. In addition, land cover changes affect the energy exchange and evapotranspiration [30]. As shown above, the majority of the literature that discussed the effects of fires on surface energy fluxes was based on ground measurements, while in situ measurements of surface energy fluxes were highly localized. The effect of fires on surface energy fluxes requires regional-scale monitoring. Multi-temporal remote sensing techniques offer considerable potential to quantify the patterns of variations in space and time. Many current models for the estimation of carbon fluxes use some variant of the light-use efficiency (LUE) model by [PERSON] [21]. This approach can produce considerable errors, however, because of the coarse resolution of the data inputs [31]. The enhanced vegetation index (EVI) has been proven to be strongly correlated with the gross primary production (GPP) within several biomes [31; 32]. Results suggested that the EVI provides a simple approach to estimate the spatial patterns of GPP. Nevertheless, the relationship in post-fire vegetation succession processes has not been confirmed. Consequently, this study primarily examined the vegetation succession process with different metrics to provide a detailed understanding of forests and their hydrothermal environment changes, which were then used to investigate the influence of such disturbances on energy flow. We examined severe fires that occurred almost simultaneously on Great Xing'an Mountain in June 2000, which burned more than eighteen thousand hectares of forest to different degrees. The goal of this study was to determine the vegetation succession processes with satellite-derived indices, including the VI, land-surface water index (LSWI) and LST, by incorporating seasonal changes and a quantified vegetation restoration process and explain the dynamic characteristics of vegetation and hydrothermal environments. We examined the direct relationships between the EVI, LSWI and LST and the GPP and NPP. We explored the main limiting factors on the energy flow of vegetation in post-fire situations. The data were all acquired from a post-fire boreal forest using the Moderate Resolution Imaging Spectroradiometer (MODIS) product.