Publications

Chew, C; Small, E; Huelsing, H (2023). Flooding and inundation maps using interpolated CYGNSS reflectivity observations. REMOTE SENSING OF ENVIRONMENT, 293, 113598.

Abstract
Despite the myriad of remote sensing techniques currently used to map surface water, a gap remains in our ability to rapidly map inundation from flooding at the required temporal resolution to understand how floods evolve. However, the recent launch of constellations of Global Navigation Satellite System-Reflectometry (GNSSR) satellites can provide data at a more frequent temporal repeat than a single satellite. These L-band instruments could provide moderate spatial resolution inundation maps at a better temporal resolution than other satellite radars. This paper describes a retrieval algorithm for flood inundation mapping using GNSS-R data from the Cyclone GNSS (CYGNSS) constellation. The algorithm employs a simple dielectric model to retrieve fractional inundation from an observation of reflectivity, requiring parameterizations of soil surface and water roughness as well as ancillary soil moisture data. Here, we give a brief overview of the model, describe our parameterization scheme, and present inundation maps using CYGNSS data. We describe four case studies (from the Amazon, Mozambique, Mali, and Australia) and compare the CYGNSS inundation maps to other surface water data (SWAMPS, PALSAR-2, Dartmouth Flood Observatory, MODIS, and the Global Surface Water Explorer). We identify sources of uncertainty in the CYGNSS inundation maps and discuss possible reasons for discrepancies between the inundation retrievals. We introduce the data portal, which houses the CYGNSS inundation maps, for use by the science community.

DOI:
10.1016/j.rse.2023.113598

ISSN:
1879-0704