Wetland monitoring with Global Navigation Satellite System reflectometry

Abstract

Information about wetland dynamics remains a major missing gap in characterizing, understanding, and projecting changes in atmospheric methane and terrestrial water storage. A review of current satellite methods to delineate and monitor wetland change shows some recent advances, but much improved sensing technologies are still needed for wetland mapping, not only to provide more accurate global inventories but also to examine changes spanning multiple decades. Global Navigation Satellite Systems Reflectometry (GNSS‐R) signatures from aircraft over the Ebro River Delta in Spain and satellite measurements over the Mississippi River and adjacent watersheds demonstrate that inundated wetlands can be identified under different vegetation conditions including a dense rice canopy and a thick forest with tall trees, where optical sensors and monostatic radars provide limited capabilities. Advantages as well as constraints of GNSS‐R are presented, and the synergy with various satellite observations are considered to achieve a breakthrough capability for multidecadal wetland dynamics monitoring with frequent global coverage at multiple spatial and temporal scales.

Soil Moisture Sensing Using Spaceborne GNSS Reflections: Comparison of CYGNSS Reflectivity to SMAP Soil Moisture

“…Higher P r ,eff is observed over water bodies, and lower P r ,eff is observed in dry desert areas. This is expected because wet surfaces produce stronger reflections than dry surfaces (Chew et al, ; Nghiem et al, ). Wetter surfaces have higher dielectric constants, which results in higher reflectivity than drier surfaces (Dobson et al, ; Egido, ; Masters, ).…”

Tropical Wetland (TropWet) Mapping Tool: The Automatic Detection of Open and Vegetated Waterbodies in Google Earth Engine for Tropical Wetlands

“…L-band radar imaging systems would provide the best potential for making these assessments [35,36,95]. Although it is encouraging to report accuracies associated with mapping inundated vegetation using TropWet equivalent to those reported by approaches that use L-band imagery [32,35] or GNSS-R [21,23,24], it should be reiterated that TropWet is limited to inundated grassland environments. However, L-band imagery archives are not currently ingested within GEE.…”

“…These examples demonstrate the potential for TropWet to provide policy makers with crucial information to help make national, regional, or continental scale decisions regarding wetland conservation, flood/disease hazard mapping, or mitigation against the impacts of ENSO.Landsat) with microwave systems (e.g., AMSR: Advanced Microwave Scanning Radiometer, SMAP: Soil Moisture Active Passive) [17,20]. Similarly, there is growing evidence that information from global navigation systems (GNSS-R: Global Navigation Satellite System Reflectometry) can provide timely and reliable classifications of wetlands by exploiting signals over both open water and vegetated water surfaces [21][22][23][24]. These approaches provide valuable tools for quantifying wetland dynamics at continental scales with important applications such as characterising greenhouse gas flux [17,18,24,25].…”

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

“…Previous analyses have shown that over land surface, particularly wetlands, there is a dominant coherent component to the reflected signal. Thus, the active scattering area is defined by the first Fresnel zone,~650 m at smaller incidence angles (<40 • ) and reaches up to~1 km at larger angles (>50 • ) [30]. The effective cross-track resolution is assumed as this first Fresnel zone size, but the along-track resolution is elongated since CYGNSS The leading edge slope (LES) is estimated from the peak in the IDW and the two preceding points, while trailing edge slope (TES) is derived from the IDW peak and three following points.…”

“…5-Janurary-2015 18-Januray-2015 16 16-Feberary-2015 1- March-2015 22 11-May-2015 24-May-2015 25 22-June-2015 5-July-2015 27 20-July-2015 2-Aug-2015 30 31-August-2015 13-Septmember-2015 33 12-October-2015 25-October-2015 36 23-November-2015 6-December-2015 39 4-Janurary-2016 17-Januray-2016 42 15-Feberary-2016 28-Feberary-2016 45 28…”