Launched in 2016, the CYGNSS constellation of 8 satellites measure the reflection from GPS signals reflecting off the surface of the Earth. Calm waterbodies such as rivers, lakes, and wetlands have a specially strong signal in CYGNSS, providing new insight on their spatial and temporal dynamics. Here we combine the new CYGNSS data with a classic computer vision technique to study the monthly evolution of two of the largest tropical wetlands on Earth: the Pantanal in South America and the Sudd in Africa.
Results/Conclusions
We find that CYGNSS captures a maximum wetland extent much larger than other optical products that can be obscured by clouds and vegetation. In addition, the seasonality of the inundation extent is delayed by one to two months compared to the seasonality of the rainfall, with large implication for wetland methane emissions modeling. Finally, we also find that dry season rainfall is also a factor in wetland recharge during the wet season, in particular in the Pantanal. In conclusion, the CYGNSS data offers new information on tropical wetlands and can help improve our understanding of their hydrological and methane emissions dynamics.