Assessing L-Band GNSS-Reflectometry and Imaging Radar for Detecting Sub-Canopy Inundation Dynamics in a Tropical Wetlands Complex

Abstract

Despite the growing number of remote-sensing products from satellite sensors, mapping of the combined spatial distribution and temporal variability of inundation in tropical wetlands remains challenging. An emerging innovative approach is offered by Global Navigation Satellite System reflectometry (GNSS-R), a concept that takes advantage of GNSS-transmitting satellites and independent radar receivers to provide bistatic radar observations of Earth's surface with large-scale coverage. The objective of this paper is to assess the capability of spaceborne GNSS reflections to characterize surface inundation dynamics in a complex wetlands environment in the Peruvian Amazon with respect to current state-of-the-art methods. This study examines contemporaneous ALOS2 PALSAR-2 L-band imaging radar, CYGNSS GNSS reflections, and ground measurements to assess associated advantages and challenges to mapping inundation dynamics, particularly in regions under dense tropical forest canopies. Three derivatives of CYGNSS Delay-Doppler maps (1) peak signal-to-noise ratio (SNR), (2) leading edge slope, and (3) trailing edge slope, demonstrated statistically significant logarithmic relationships with estimated flooded area percentages determined from SAR, with SNR exhibiting the strongest association. Aggregated Delay-Doppler maps SNR time series data examined for inundated regions undetected by imaging radar suggests GNSS-R exhibits a potentially greater sensitivity to inundation state beneath dense forest canopies relative to SAR. Results demonstrate the capability for mapping extent and dynamic wetlands ecosystems in complex tropical landscapes, alone or in combination with other remote-sensing techniques such as those based on imaging radar, contributing to enhanced mapping of these regions. However, several aspects of GNSS-R observations such as noise level, spatial resolution, and signal coherence need to be further examined.biogeochemical processes such as the generation of atmospheric methane and the outgassing of carbon dioxide [2,3]. These flooding regimes can be impacted by future changes in rainfall, evapotranspiration and land use. The ability to accurately monitor the current state and changes in inundation extent would enable further examination of potential climatological and anthropogenic tipping points in these wetlands regions.Satellite remote sensing is the only practical approach that can provide insight into the spatial and temporal dynamics of wetlands on a large scale on a continuous basis. Although they can offer high spatial resolution and sensitivity to photochemical properties of vegetation, optical sensors are severely limited in capturing inundation dynamics in tropical wetlands due to frequent cloud cover and difficulties detecting sub-canopy inundation [4,5]. Microwave sensors, on the other hand, are not significantly affected by clouds or changing solar illumination and are able to observe processes below vegetation canopy. However, tradeoffs exist in the use of microwave remote sensing with respect to...

Flux towers in the sky: global ecology from space

“…ET can be estimated in thermal and runoff from radar altimetry. Some methods exist for measuring inundation, most recently using ‘bistatic’ radar, or analysis of Global Positioning System signals by special receivers (Jensen et al ., ) (Fig. ).…”

“…Tansley review New Phytologist recently using 'bistatic' radar, or analysis of Global Positioning System signals by special receivers (Jensen et al, 2018) (Fig. 4).…”

Mapping of Maximum and Minimum Inundation Extents in the Amazon Basin 2014–2017 with ALOS-2 PALSAR-2 ScanSAR Time-Series Data

“…Existing inundation datasets were used for comparison purposes, developed by Hess et al [9,10], Chapman, et al [12] and Jensen et al [16].…”

“…The product by Jensen et al [16] covers an approximately 15,000 km 2 region of the Pacaya-Samiria National Reserve in Peru. The classification was derived from dual-polarization (HH+HV) ALOS-2 PALSAR-2 ScanSAR data acquired between November 2014 and February 2018, and is thus partially contemporary with the PALSAR-2 ScanSAR data used in this study.…”

“…PALSAR ScanSAR datasets have been employed to develop swath-by-swath time-series mappings of wetlands inundation throughout the Amazon Basin [12] and are an integral part of the NASA Earth System Data Record (ESDR) of inundated wetlands in distribution through NASA's Alaska Satellite Facility DAAC [13]. Research using L-band SAR datasets has also emphasized regional studies, characterizing smaller watersheds within the Amazon Basin, such as the Jaú river basin [14], the Curuaí floodplain [15], Pacaya-Samiria National Park [16] and the Óbidos floodplain [3]. Beyond the Amazon Basin, L-band SAR have also been used for wetland inundation studies in the Pantanal [17], the Congo River basin [18] and Indonesia [19].…”