Using GNSS Reflectometry Measurements Over the Everglades to Identify
Variations in Wetland Inundation Extent Beneath Vegetation
Abstract
Wetlands represent an essential ecosystem, providing flood control,
carbon storage, and supporting biodiversity. In particular, the
Everglades is a Ramsar Wetland of International Importance, supporting
several threatened and endangered species of flora and fauna, and is
especially important for wintering birds. Understanding and monitoring
wetlands like the Everglades requires the ability to accurately identify
and measure wetland extent and change in extent on short time scales.
However, in situ methods are difficult given the nature of the
surrounding environment, and optical methods of remote sensing are
unable to see through dense vegetation. NASA’s Cyclone Global Navigation
Satellite System (CYGNSS) has shown promising results using GNSS
Reflectometry to identify the presence and extent of inland water.
Utilizing GNSS as a signal of opportunity in an L-band passive bistatic
radar, it can penetrate rain, clouds, and vegetation. Its 8-satellite
constellation exhibits daily or sub-daily revisit rates, enabling the
observation of dynamic changes on short time scales. In this work, we
utilize a combination of CYGNSS data, ancillary information, and
simulations to understand the observability of inundation beneath
vegetation. Simulations were used to predict the received power using a
water mask derived from Landsat imagery over the Everglades. By
analyzing the differences between expected and actual received power, we
identified areas of flooded vegetation. These differences were then
combined with ancillary data sets to measure seasonal changes and create
a seasonal map of open water and inundated vegetation throughout the
Everglades network. We also investigated the ability of CYGNSS to
discern and measure different vegetation types. Results were then
compared with optical and radar imagery and verified with truth data
from the Everglades Depth Estimation Network (EDEN) and littoral
vegetation maps from the South Florida Water Management District. By
leveraging CYGNSS’s high temporal frequency of observations and ability
to see under vegetation, measurements of inundated vegetation and its
change can complement other remote sensing and in situ methods of
wetland monitoring.