## 1 Introduction
### Current Literature Reviews  
This SLR identified six review articles (Table 1). [PERSON] and [PERSON] (2022) assessed remote sensing techniques in research involving peatlands and the external factors affecting their development. The study was a state-of-the-art review and found that there had been a surge in the utilisation of RS approaches in peatland research over the past ten years, likely due to the augmented access to a variety of RS data sets and the quick progress of open-source software [52]. [PERSON] et al. (2021) conducted a scoping review to evaluate UAVs' current and potential wetland applications. The authors found that UAVs could reduce the logistical demands of field surveys and optimise UAV-based workflows for monitoring wetland environments and management strategies. In addition, they identified significant trends in applications, technology, and data, and provided recommendations for future research [53]. [PERSON] et al. (2021) assessed the use of remote sensing (RS) technology in wetland studies in Canada. The study was a bibliographic analysis, and the authors found that most wetland classification studies were conducted within the province of Ontario, with a preference for pixel-based supervised classifiers as the primary classification algorithm [54]. [PERSON] et al. (2019) conducted a state-of-the-art review of the current digital mapping techniques used to measure and monitor carbon stocks in peatlands and the potential opportunities and challenges to accurately assessing the world's peatlands. The authors found that interest in utilising satellite imagery and other digital mapping technologies to map peatlands was increasing. However, they noted that assessing the accuracy or uncertainty of the prediction was rarely performed [3]. [PERSON] et al. (2018) conducted a literature review to assess the current understanding of estimating carbon dioxide fluxes in peatland utilising remote sensing technology and identified areas for future research. The authors found that there was potential for remote sensing to be utilised in models of carbon fluxes over northern peatlands. However, further development was necessary to create more comprehensive carbon cycle models and ensure their longevity, notably on peatlands subject to restoration [34]. [PERSON] et al. (2017) conducted a literature review to provide an overview of wetland remote sensing, including selected approaches, findings, and types of remote sensors. The review concluded that early research into wetland mapping utilised aerial photography as the primary data source, though hyperspectral imaging had become more prevalent in recent years. They also noted that radar data are often used to detect wetland areas, and LiDAR data can generate three-dimensional topographical maps [4]. This SLR distinguishes itself by offering a specialised and detailed exploration of the applications, challenges, and future directions of RS in northern peatland research. Unlike previous overviews that broadly discuss RS adoption, our focus extends to specific applications such as the integration and the sensor fusion of hyperspectral and LiDAR data for precise vegetation mapping. We address challenges rigorously, emphasising the importance of calibration, validation practices, and interdisciplinary approaches, setting our review apart from general recommendations provided in prior works. Additionally, our comprehensive exploration covers various applications, including vegetation mapping, hydrology monitoring, and carbon stock assessment, providing a more holistic perspective compared to reviews that primarily focus on carbon flux estimation. This SLR goes beyond emphasising the significance of interdisciplinary approaches, stressing the need for data integration and advanced modelling techniques to enhance our understanding of peatland ecosystems, making it a forward-looking contribution to the field. \begin{table}
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**References** & **Scope** & **Protocol** &