
Effects of Aquatic and Emergent Riparian Vegetation on SWOT Mission Capability in Detecting Surface Water Extent
Author(s) -
Nicolas Desrochers,
Melanie Trudel,
Sylvain Biancamaria,
Gabriela Siles,
Damien Desroches,
Denis Carbonne,
Robert Leconte
Publication year - 2021
Publication title -
ieee journal of selected topics in applied earth observations and remote sensing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.246
H-Index - 88
eISSN - 2151-1535
pISSN - 1939-1404
DOI - 10.1109/jstars.2021.3128133
Subject(s) - geoscience , signal processing and analysis , power, energy and industry applications
The future surface water and ocean topography (SWOT) satellite mission will provide images of surface water topography for inland water bodies and oceans. Over land, water surface elevation (WSE) will be retrieved at 10 cm accuracy for water bodies with areas > 250 m × 250 m and rivers with widths > 100 m, when averaging over 1 km2. Studies have shown that the Ka-band used by SWOT's main payload can be affected by aquatic and emergent riparian vegetation, which in turn could influence SWOT capacity to correctly observe water extent. The current study investigates effects of aquatic and emergent riparian vegetation on SWOT water extent and WSE detection capabilities through the use of NASA/JPL's SWOT simulator (HR). Data from the AirSWOT airborne campaign over Mamawi Lake (163 km2) in the Peace-Athabasca Delta (PAD, Alberta, Canada), are used to establish a land cover classification and backscattering values for simulation inputs. Simulation results have shown that aquatic vegetation has a negligible effect on the SWOT signal. Yet, simulations showed that water extent misclassification can occur for water with emergent riparian vegetation in the specific case of wetlands surrounding lakes (i.e., small differences in backscattering values between surrounding land and water with emergent riparian vegetation). Simulations featuring the smallest difference between emergent riparian vegetation and land (1.3 dB) showed a 32–35% lake extent reduction from true extent. As expected, this study reveals that estimating water extent from SWOT in very wet environments with emergent vegetation can be challenging.