## 1 Introduction
### Current Literature Reviews
\begin{tabular}{c} **Databases** \\ **Searched** \\ \end{tabular}  & \begin{tabular}{c} **Number of** \\ **Articles** \\ \end{tabular}  & **Timespan** & **Key Findings** \\ \hline \multirow{6}{*}{[52]} & This research delivers a comprehensive & \multirow{6}{*}{ \begin{tabular}{c} This research delivers a comprehensive \\ assessment of the use of remote sensing (BS) \\ techniques in wetland research and the \\ external factors that can influence the way \\ they evolve. \\ \end{tabular}  } & State-of-the- & Web of Science and Scopus & 59 & 2010-2021 & \begin{tabular}{c} There has been a conspicuous rise in adopting BS \\ methodologies within wetland research in the past decade. \\ This surge can largely be attributed to enhanced accessibility \\ to a diverse range of BS datasets, including Sentinel 1 and 2, and Landsat 4, and SPOT 6 and 7, alongside the rapid progress \\ of open-source software tools such as ESA SNAP, QGIS, and SAGA GIS. \\ \hline \multirow{6}{*}{[53]} & The aim of this study was to examine the & \multirow{6}{*}{ \begin{tabular}{c} The aim of this study was to examine the \\ present and prospective capabilities of \\ unmanned aerial vehicles (UAVs) in \\ wetlands to enhance ecosystem management \\ practices. It investigates the status of UAV \\ applications in wetlands and identifies \\ several research, technological, and data \\ prerequisites for optimizing their \\ effectiveness. \\ \end{tabular}  } & \multirow{6}{*}{ \begin{tabular}{c} Sooping \\ review [23] \\ Google Scholar \\ \end{tabular}  } & Web of Science & \multirow{6}{*}{ \begin{tabular}{c} 122 \\ Google Scholar \\ \end{tabular}  } & \multirow{6}{*}{ \begin{tabular}{c} Before 6 March \\ 2021 \\ \end{tabular}  } & \multirow{6}{*}{ \begin{tabular}{c} This review examines the potential of UAVs to reduce the \\ logital demands of field surveys and to optimise \\ UAV-based workflows for monitoring \\ environments and management strategies. Additionally, it identifies significant trends in applications, technology, and data, and provides recommendations for future research. \\ \end{tabular}  } \\ \cline{1-1}  & This research article employs meta-data & \multirow{2}{*}{ \begin{tabular}{c} Bibliographic \\ analysis (31) \\ through RS technology. \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} Web of Science \\ analysis (32) \\ analysis (33) \\ \end{tabular}  } & \multirow{2}{*}{\ \begin{tabular}{c} Web of Science \\ and Elsevier \\ Sopus \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} Many wetland classification studies were conducted within \\ the province of Ontario, with a preference for pixel-based \\ supervised classifiers as the primary classification \\ algorithm. \\ \end{tabular}  } \\ \cline{1-1}  & This study shows a growing interest in using satellite \\ \cline{1-1}  & & & & & & \\ \cline{1-1}  & & & & & \\ \cline{1-1}  & This article delivers an overview of the & & & & \\ \cline{1-1}  & & & & & \\  
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**References** & **Scope** & **Protocol** & \ \begin{tabular}{c} **Databases** \\ **Searched** \\ \end{tabular}  & \begin{tabular}{c} **Number of** \\ **Articles** \\ \end{tabular}  & **Timespan** & **Key Findings** \\ \hline
[34] & This review paper assesses the current understanding of estimating carbon dioxide fluxes in pendant utilising remote sensing technology and identifies areas for future research. & Narrative Review ([5]) & Not mentioned & Not mentioned & Not mentioned & The study demonstrated the potential of FS in modelling carbon fluxes across northern peatlands. Nonetheless, further research is imperative to develop more comprehensive carbon cycle models, with particular emphasis on peatlands undergoing restoration, to ensure the sustainability and durability of these models. & \\ \hline
[4] & This review paper provides an in-depth examination of wetland remote sensing, which involves an overview of selected approaches, findings, and remote sensor types. In also offers recommendations for future research.