## 4 Remote Sensing Platforms Used in Peatland Research
### In Situ-Based Remote Sensing  
In situ remote sensing techniques have become increasingly valuable in peatland research, providing insights into various aspects of these ecosystems and mainly being used to validate the other measurements using different platforms. Regarding the commonly used sensors or instruments, the acquisition of canopy spectral reflectance in the field has primarily relied on proximal sensing using field spectrometers. This approach has been employed in approximately 75% of all conducted studies. Among the instruments utilised, the Analytical Spectral Devices (ASD, USA) series has emerged as the most used. These instruments operate within the spectral range of 350 to 2500 nm, as exemplified in various instances [129; 130] (Table 6). The potential of utilising the spectral data to distinguish between different Sphagnum species has been a subject of speculation in previous literature. Noted that they differ dramatically in laboratory and field measurements [131]. However, our understanding of intraspecific variation in the spectra of Sphagnum species remains limited. This knowledge gap is due to the relatively small sample sizes employed in prior studies, which often included only a single sample per species or a limited number of species under investigation. Additionally, it is worth noting that the bulk of recent studies investigating the spectral characteristics of Sphagnum, as conducted by [PERSON] et al. (2020), have primarily focused on temperate peatlands [49]. This differs significantly from boreal peatlands, where growing conditions are markedly distinct due to factors such as the duration of the snow-free season and seasonal fluctuations in temperature and solar irradiance when compared to the temperate zone. Furthermore, many in situ peatland vegetation studies have employed sensors that solely capture data within the visible (VIS) and near-infrared (NIR) spectral regions [131; 132; 133]. Consequently, insights related to species identification and moisture content obtained through shortwave infrared (SWIR) wavelength data have not yet been thoroughly investigated in the context of boreal peatland vegetation. Several studies [134; 129; 130] highlight the usefulness of in situ measurements in capturing plot-scale changes in peatland ecosystems. These techniques enable the detection of vegetation productivity, biodiversity, and degradation caused by human activities [135; 136; 137]. However, it is essential to note that remote sensing data may have limitations in accurately capturing fine-scale details and species-level information, which could be critical for understanding specific ecological dynamics within peatlands. The assessment of peatland hydrology using remote sensing has been investigated by several researchers [130; 133; 135]. These studies demonstrate the potential of remote sensing in detecting changes in water table levels and hydrological patterns. Nevertheless, challenges exist in accurately capturing the complexities of peatland hydrology due to the presence of variable water levels and the influence of vegetation on the water regime. Moreover, it was noted that there was a lack of studies focusing on drought investigations despite the availability of the hyperspectral in situ data. Several studies have focused on the relationship between spectral indices and peatland characteristics [137; 138; 139; 27; 50]. These investigations use spectral indices to estimate carbon content, vegetation cover, or ecosystem productivity. However, caution must be exercised in interpreting spectral indices, as multiple factors can influence them, including vegetation composition, atmospheric conditions, and sensor characteristics. Moreover, the transferability and generalizability of spectral indices across different peatland types and regions require further exploration. Climate change impacts on peatland ecosystems have been examined in several studies [131; 132; 136; 49].