## 4 Discussion
For instance [17], used the L-band signal from the Cyclone Global Navigation Satellite System (CYGNSS) satellite constellation to provide monthly inundation maps over regions including the Pantanal (Bolivia, Brazil) and Sudd (South Sudan) wetlands. However, at a resolution of 0.01 degree (\(\sim\)1111 m), this approach will not be able to capture fine-scale hydrological features [18]. Conversely, RadWet-L, with the ALOS-2 PALSAR-2 ScanSAR mapping unit of 50 m, offers the ability to map fine-scale features such as headwater rivers, smaller tributary systems and floodplain features such as anabranching channels shown in Figure 9. These features have an important role in the movement of water through basins [66] and, therefore, capturing the inundation dynamics of these features can increase our understanding of the hydrology of a region such as the Amazon Basin. Furthermore, smaller headwaters and tributaries are likely to act as important habitats and refugia for approximately half of the aquatic species in the Amazon, yet they are relatively understudied compared to larger channels [5], and therefore understanding their spatial extent and temporal dynamics can help with efforts to conserve and protect these important habitats [5; 67]. Many widely used global wetland databases and maps (including the Global Lakes and Wetlands Database and the Global Surface Water system) do not adequately capture the extent of inundation vegetation [4]. RadWet-L is designed to detect both open water and inundated forest. The contribution of inundated forest to the total inundation extent of the Amazon Basin is considerable, representing an estimated 9.5% of inundation in the dry season, and 74% of the total observed inundated during the wet season. This proportion of inundated forest detected by RadWet-L for the Amazon Basin is similar to the proportions of inundation vegetation reported in other studies focussing on herbaceous-dominated tropical wetland landscapes using C-band radar, including Western Zambia [24; 25] and the Upper Rupununi, Guyana. If tropical wetland inundation is to be mapped, inundated herbaceous vegetation must also be taken into account. Future work should consider harmonising information from L- and C-band radar to map both inundated forest and inundation herbaceous vegetation, working towards a comprehensive inundation mapping system to provide accurate inventories of the world's tropical wetlands. The ability to map wetland inundation dynamics in large tropical river basins like the Amazon can transform our ability to monitor wetland ecosystems and biodiversity hotspots. Inundated forests in the Amazon are relatively sparsely populated and therefore exist in a near-natural state, largely untouched by human activity and are highly associated with increased biodiversity [5; 68]. However, they are highly vulnerable to a range of pressures, including land cover change and pollution [5]. Through high spatial and temporal scale mapping of inundation dynamics, RadWet-L has the capacity to provide vital information on how these important habitats are changing. Furthermore, anaerobic conditions experienced during periods of inundation have a substantial role in governing the rate of emissions from greenhouse gases such as carbon dioxide and methane. This mechanism is significantly accelerated over inundated vegetation, with tropical regions having a disproportionally large role in global emissions [69]. Indeed, the Amazon floodplain represents the largest natural source of methane in the tropics, largely mediated by forested wetlands [70]. Information generated by RadWet-L could provide unprecedented information on the inundation dynamics of these wetlands and could therefore be used to inform models of greenhouse gas emissions following an approach similar to that used by [17]. They employed improved inundation maps for regions in East Africa and South America for driving methane emission estimates using the WetCHARTS model [71].