Ronny Schroeder

Satellite microwave remote sensing of North Eurasian inundation dynamics: development of coarse-resolution products and comparison with high-resolution synthetic aperture radar data

Wetlands are not only primary producers of atmospheric greenhouse gases but also possess unique features that are favourable for application of satellite microwave remote sensing to monitoring their status and trend. In this study we apply combined passive and active microwave remote sensing data sets from the NASA sensors AMSR-E and QuikSCAT to map surface water dynamics over Northern Eurasia. We demonstrate our method on the evolution of large wetland complexes for two consecutive years from January 2006 to December 2007. We apply river discharge measurements from the Ob River along with land surface runoff simulations derived from the Pan-Arctic Water Balance Model during and after snowmelt in 2006 and 2007 to interpret the abundance of widespread flooding along the River Ob in early summer of 2007 observed in the remote sensing products. The coarse-resolution, 25 km, surface water product is compared to a high-resolution, 30 m, inundation map derived from ALOS PALSAR (Advanced Land Observation Satellite phased array L-band synthetic aperture radar) imagery acquired for 11 July 2006, and extending along a transect in the central Western Siberian Plain. We found that the surface water fraction derived from the combined AMSR-E/QuikSCAT data sets closely tracks the inundation mapped using higher-resolution ALOS PALSAR data.

Development and Evaluation of a Multi-Year Fractional Surface Water Data Set Derived from Active/Passive Microwave Remote Sensing Data

The sensitivity of Earth’s wetlands to observed shifts in global precipitation and temperature patterns and their ability to produce large quantities of methane gas are key global change questions. We present a microwave satellite-based approach for mapping fractional surface water (FW) globally at 25-km resolution. The approach employs a land cover-supported, atmospherically-corrected dynamic mixture model applied to 20+ years (1992–2013) of combined, daily, passive/active microwave remote sensing data. The resulting product, known as Surface WAter Microwave Product Series (SWAMPS), shows strong microwave sensitivity to sub-grid scale open water and inundated wetlands comprising open plant canopies. SWAMPS’ FW compares favorably (R2 = 91%–94%) with higher-resolution, global-scale maps of open water from MODIS and SRTM-MOD44W. Correspondence of SWAMPS with open water and wetland products from satellite SAR in Alaska and the Amazon deteriorates when exposed wetlands or inundated forests captured by the SAR products were added to the open water fraction reflecting SWAMPS’ inability to detect water underneath the soil surface or beneath closed forest canopies. Except for a brief period of drying during the first 4 years of observation, the inundation extent for the global domain excluding the coast was largely stable. Regionally, inundation in North America is advancing while inundation is on the retreat in Tropical Africa and North Eurasia. SWAMPS provides a consistent and long-term global record of daily FW dynamics, with documented accuracies suitable for hydrologic assessment and global change-related investigations.

Mapping Regional Inundation with Spaceborne L-Band SAR

Shortly after the launch of ALOS PALSAR L-band SAR by the Japan Space Exploration Agency (JAXA), a program to develop an Earth Science Data Record (ESDR) for inundated wetlands was funded by NASA. Using established methodologies, extensive multi-temporal L-band ALOS ScanSAR data acquired bi-monthly by the PALSAR instrument onboard ALOS were used to classify the inundation state for South America for delivery as a component of this Inundated Wetlands ESDR (IW-ESDR) and in collaboration with JAXA’s ALOS Kyoto and Carbon Initiative science programme. We describe these methodologies and the final classification of the inundation state, then compared this with results derived from dual-season data acquired by the JERS-1 L-band SAR mission in 1995 and 1996, as well as with estimates of surface water extent measured globally every 10 days by coarser resolution sensors. Good correspondence was found when comparing open water extent classified from multi-temporal ALOS ScanSAR data with surface water fraction identified from coarse resolution sensors, except in those regions where there may be differences in sensitivity to widespread and shallow seasonal flooding event, or in areas that could be excluded through use of a continental-scale inundatable mask. It was found that the ALOS ScanSAR classification of inundated vegetation was relatively insensitive to inundated herbaceous vegetation. Inundation dynamics were examined using the multi-temporal ALOS ScanSAR acquisitions over the Pacaya-Samiria and surrounding areas in the Peruvian Amazon.

Diagnosis of the record discharge of Arctic-draining Eurasian rivers in 2007

Aggregate annual discharge from the six largest Arctic-draining Eurasian rivers achieved an all-time record high in 2007, accentuating a long-term upward trend that argues for intensification of the Arctic hydrologic cycle. This record discharge was due in part to strong positive anomalies in late winter snow water equivalent across much of northern Eurasia. These anomalies arose in response to an unusual pattern of atmospheric circulation in late 2006 and early 2007, characterized by an extreme northeastward extension of the Icelandic Low and a contraction of the Siberian High. Positive net precipitation anomalies then continued into summer, further contributing to discharge.

Application of QuikSCAT Backscatter to SMAP Validation Planning: Freeze/Thaw State Over ALECTRA Sites in Alaska From 2000 to 2007

The mapping of the predominant freeze/thaw state of the landscape is one of the main objectives of the National Aeronautics and Space Administrations proposed Soil Moisture Active Passive (SMAP) mission. This study applies Alaska Ecological Transect (ALECTRA) biophysical network temperature measurements and satellite radar scatterometer data from the Quick Scatterometer (QuikSCAT) to evaluate some of the validation issues regarding the planned SMAP freeze/thaw measurements. Although the QuikSCAT data are acquired at Ku-band frequency, rather than at the L-band frequency of the proposed SMAP instrument, QuikSCAT data do provide a high temporal fidelity over the ALECTRA sites, similar to SMAP. The results of this study show that multiple temperature measurements representative of individual landscape components (soil, snow cover, vegetation, and atmosphere) covering different types of terrain within the satellite field of view are important for understanding the freeze/thaw process and the aggregate radar backscatter response to that process. The backscatter temporal dynamics and relative contribution of the freeze/thaw state of these landscape elements to radar signal vary with land cover, seasonal weather, and climate conditions.

Bioclimatic variables derived from remote sensing: assessment and application for species distribution modelling

Summary Remote sensing techniques offer an opportunity to improve biodiversity modelling and prediction world-wide. Yet, to date, the weather station-based WorldClim data set has been the primary source of temperature and precipitation information used in correlative species distribution models. WorldClim consists of grids interpolated from in situ station data recorded primarily from 1960 to 1990. Those data sets suffer from uneven geographic coverage, with many areas of Earth poorly represented. Here, we compare two remote sensing data sources for the purposes of biodiversity prediction: MERRA climate reanalysis data and AMSR-E, a pure remote sensing data source. We use these data to generate novel temperature-based bioclimatic information and to model the distributions of 20 species of vertebrates endemic to four regions of South America: Amazonia, the Atlantic Forest, the Cerrado and Patagonia. We compare the bioclimatic data sets derived from MERRA and AMSR-E information with in situ station data and contrast species distribution models based on these two products to models built with WorldClim. Surface temperature estimates provided by MERRA and AMSR-E showed warm temperature biases relative to the in situ data fields, but the reliability of these data sets varied in geographic space. Species distribution models derived from the MERRA data performed equally well (in Cerrado, Amazonia and Patagonia) or better (Atlantic Forest) than models built with the WorldClim data. In contrast, the performance of models constructed with the AMSR-E data was similar to (Amazonia, Atlantic Forest, Cerrado) or worse than (Patagonia) that of models built with WorldClim data. Whereas this initial comparison assessed only temperature fields, efforts to estimate precipitation from remote sensing information hold great promise; furthermore, other environmental data sets with higher spatial and temporal fidelity may improve upon these results.

Quikscat backscatter sensitivity to landscape freeze/thaw state over ALECTRA sites in Alaska from 2000 to 2007: Application to SMAP validation planning

The mapping of freeze/thaw state of the landscape is one of the main objectives of NASAs upcoming SMAP (Soil Moisture Active and Passive) mission. This study applies ALECTRA (Alaska Ecological Transect) biophysical network and QuikSCAT scatterometer data to evaluate some of the validation issues regarding the SMAP freeze/thaw measurements. Although the QuikSCAT data is at Ku-band frequency, rather than the L-band of the SMAP instrument, the data is utilized due to its uniquely high temporal resolution over the ALECTRA sites. The results show that multiple temperature measurements representative of individual landscape (soil, snow cover, vegetation and atmosphere) elements and spatial heterogeneity within the satellite field-of-view are important for understanding the radar backscatter process and aggregate freeze/thaw signal. The backscatter temporal dynamics and relative contribution of these landscape elements to the freeze-thaw signal varies with land cover type, seasonal weather and climate conditions.

Active and Passive multi-scale microwave remote sensing of the Alaska Ecological Transect: Application to SMAP freeze/thaw state validation planning

The calibration and validation of the freeze/thaw product of NASAs proposed L-band SMAP (Soil Moisture Active and Passive) radar and radiometer mission requires execution of a strategy for characterization of thermal regime of the relevant landscape elements in terms of freeze/thaw state and the associated relationship to the microwave remote sensing signature. The goal of this study is to improve the understanding of the L-band radar backscatter processes over boreal landscapes by comparing ALOS PALSAR high resolution L-band backscatter images with Ku-band backscatter from the SeaWinds QuikSCAT scatterometer and C-, X- and Ka-band brightness temperatures from the Aqua AMSR-E radiometer. The results show that landscape elements driving the L-band backscatter are different from those at higher (Ku-band) frequencies and establishment of an optimal validation strategy for SMAP requires investigation of L-band measurements at spatial scales and temporal fidelity commensurate with landscape freeze/thaw variability.