Detection of open water dynamics with ENVISAT ASAR in support of land surface modelling at high latitudes

Abstract

Abstract. Wetlands are generally accepted as being the largest but least well quantified single source of methane (CH 4 ). The extent of wetland or inundation is a key factor controlling methane emissions, both in nature and in the parameterisations used in large-scale land surface and climate models. Satellite-derived datasets of wetland extent are available on the global scale, but the resolution is rather coarse (>25 km). The purpose of the present study is to assess the capability of active microwave sensors to derive inundation dynamics for use in land surface and climate models of the boreal and tundra environments. The focus is on synthetic aperture radar (SAR) operating in C-band since, among microwave systems, it has comparably high spatial resolution and data availability, and long-term continuity is expected.C-band data from ENVISAT ASAR (Advanced SAR) operating in wide swath mode (150 m resolution) were investigated and an automated detection procedure for deriving open water fraction has been developed. More than 4000 samples (single acquisitions tiled onto 0.5 • grid cells) have been analysed for July and August in 2007 and 2008 for a study region in Western Siberia. Simple classification algorithms were applied and found to be robust when the water surface was smooth. Modification of input parameters results in differences below 1 % open water fraction. The major issue to address was the frequent occurrence of waves due to wind and precipitation, which reduces the separability of the water class from other land cover classes. Statistical measures of the backscatter distribution were applied in order to retrieve suitable classification data. The Pearson correlation between each sample dataset and a location specific representation of the bimodal distribution was used. On average only 40 % of acquisitions allow a separation of the open water class. Although satellite data are available every 2-3 days over the Western Siberian study region, the irregular acquisition intervals and periods of unsuitable weather suggest that an update interval of 10 days is more realistic for this domain. SAR data availability is currently limited. Future satellite missions, however, which aim for operational services (such as Sentinel-1 with its C-band SAR instrument), may provide the basis for inundation monitoring for land surface and climate modelling applications.

Assessing Seasonal Backscatter Variations with Respect to Uncertainties in Soil Moisture Retrieval in Siberian Tundra Regions

“…Higher backscatter than the typical C-band backscatter for smooth water surfaces may be caused by (1) ice covers on water surfaces and (2) wind and rain action. Wave ripples on the water body surface due to wind and rain increase the surface roughness and hence lead to diffuse scattering and high backscatter values [47,53]. The persistence of lake ice on large lakes well into the summer and the associated water body classification issues have already been pointed out by [47].…”

“…Data availability is considerably constraint compared to scatterometer data. Suitable time series can be obtained for a range of locations across Siberia for selected years [47]. For this study, an ASAR WS dataset which was pre-processed over Northern Eurasia for the time period 2007-2008 within the framework of the European Space Agency (ESA) Support To Science Element (STSE) project ALANIS Methane [47][48][49] was used.…”

“…Suitable time series can be obtained for a range of locations across Siberia for selected years [47]. For this study, an ASAR WS dataset which was pre-processed over Northern Eurasia for the time period 2007-2008 within the framework of the European Space Agency (ESA) Support To Science Element (STSE) project ALANIS Methane [47][48][49] was used. Since the backscatter signal decreases with increasing incidence angle of the radar beam relative to the surface, the backscatter measurements are normalized to a common reference angle (30 • ) using the SAR Geophysical…”

“…The scripting chain calls the commercial SARscape or the free NEST software, allowing for the automatization of the entire preprocessing procedure [47,50]. Single images are split up into predefined subsets and stored as time series stacks.…”

Surface State across Scales; Temporal and Spatial Patterns in Land Surface Freeze/Thaw Dynamics

“…Floating ice produces relatively high backscatter (higher compared to summer values) [49]; therefore, the presence of lakes reduces backscatter in summer, under calm conditions, increases short term under windy conditions [65], and floating ice remains after snow melt [66] and increases backscatter in winter (depending on ice growth patterns). This all introduces noise that may lead to a lower performance of the threshold and edge detection algorithms.…”