Using ENVISAT ASAR Global Mode Data for Surface Soil Moisture Retrieval Over Oklahoma, USA

Pathe, Carsten; Wagner, Wolfgang; Sabel, Daniel; Doubková, Marcela; Basara, Jeffrey B.

doi:10.1109/tgrs.2008.2004711

Cited by 179 publications

(189 citation statements)

References 68 publications

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“…However, the correlations for ASAR against the in-situ measurements were generally weaker than for the ECV SM dataset, despite the scale gap between measurements being less pronounced. Similar findings were observed by Pathe et al (2009) when comparing ASAR-GM derived soil moisture to ERS scatterometer and in-situ soil moisture measurements (Oklahoma MESONET. Zribi et al (2014) also found similar results for ASAR-WS derived soil moisture (resampled to 1km resolution) and ERS/ASCAT products covering a semi-arid region in central Tunisia.…”

Section: Time Series Temporal Analysissupporting

confidence: 80%

“…This technique was originally developed for ERS scatterometer and Advanced Scatterometer (ASCAT) data but has been successfully adapted to both ASAR WS and GM data (e.g. Pathe et al, 2009;Mladenova et al, 2010;Doubková et al, 2012;Peters et al, 2012;Dostálová et al, 2014;Zribi et al, 2014). The TU Wien change detection approach derives relative changes in surface soil moisture and indirectly accounts for surface roughness and vegetation by assuming changes in these parameters will generally occur at longer temporal scales than soil moisture changes.…”

Section: Asar Soil Moisture Observationsmentioning

confidence: 99%

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Intercomparison of Soil Moisture Retrievals From In Situ, ASAR, and ECV SM Data Sets Over Different European Sites

Barrett¹,

Pratola²,

Gruber³

et al. 2016

Satellite Soil Moisture Retrieval

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The availability of satellite-derived global surface soil moisture products during the last decade has opened up great opportunities to incorporate these observations into applications in hydrology, meteorology and climatic modelling. This study evaluates a new global soil moisture product developed under the framework of the European Space Agency (ESA) Climate Change Initiative (CCI), using finer spatial resolution Synthetic Aperture Radar (SAR) and ground-based measurements of soil moisture. The analysis is carried out over selected in-situ networks over Ireland, Spain, and Finland with the aim of assessing the temporal representativeness of the coarse scale CCI Essential Climate Variable (ECV) soil moisture product (ECV SM) in these different areas. A good agreement (correlation coefficient (R) values between 0.53 and 0.92) was observed between the three soil moisture datasets for the Irish and Spanish sites while a reasonable agreement (R values between 0.41 and 0.52) was observed between the SAR and ECV SM soil moisture datasets at the Finnish sites. Overall, the two different satellite derived products captured the soil moisture temporal variations well and were in good agreement with each other, highlighting the confidence of using the coarse scale ECV SM product to track soil moisture variability in time.

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Section: Time Series Temporal Analysissupporting

confidence: 80%

Section: Asar Soil Moisture Observationsmentioning

confidence: 99%

Intercomparison of Soil Moisture Retrievals From In Situ, ASAR, and ECV SM Data Sets Over Different European Sites

Barrett¹,

Pratola²,

Gruber³

et al. 2016

Satellite Soil Moisture Retrieval

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“…This is a collection of routines which manages SAR geocoding and radiometric calibration by calling other non-commercial and commercial software packages. By incorporating orbit information (DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite) orbit files) and digital elevation data (US Geological Survey GTOPO30 digital elevation model, improved by Shuttle Radar Topography Mission data), geocoded images were produced with sub-pixel accuracy (Park et al, 2011;Pathe et al, 2009). The data are resampled into a fixed 15 arcsec grid (datum WGS-84), within 0.5 • by 0.5 • tiles, to allow for efficient spatial and temporal analysis.…”

Section: Sar Data Processingmentioning

confidence: 99%

“…A challenge is the complexity of the interaction of the signal with the Earth surface. Water content of the near-surface soil contributes to the backscatter during unfrozen periods (Wagner et al, 1999;Pathe et al, Figure 1. Location of field sites with high-resolution land-coverbased soil organic carbon maps (Table 1) and area covered by the Circumpolar Arctic Vegetation Map (CAVM; Walker et al, 2002) as well as ENVISAT ASAR GM data (medium grey) 2009) as well as snow grains in the wintertime (Ulaby et al, 1982).…”

Section: Introductionmentioning

confidence: 99%

“…Applications across scale and instruments are common. EN-VISAT ASAR data acquired in Wide Swath (WS, ∼ 120 m) and Global Monitoring (GM, ∼ 1 km) mode were used, for example, to downscale soil-moisture-related patterns (Wagner et al, 2008;Pathe et al, 2009) or bias-correct (Högström and Bartsch, 2016) information from scatterometer. The applicability of similar multitemporal analyses for both GM and WS data has already been demonstrated for forest growing stock volume retrieval (Santoro et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?

et al. 2016

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Abstract.A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ∼ 120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.

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Soil moisture mapping in a semiarid region, based on ASAR/Wide Swath satellite data

et al. 2014

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In this paper, an operational algorithm is proposed for the mapping of surface moisture over the northern and central parts of Tunisia, in North Africa. A change detection approach is applied, using 160 multiincidence Envisat ASAR Wide Swath images acquired in the horizontal polarization over a 7 year period. Parameterization of this algorithm is considered for three classes of vegetation cover density (NDVI < 0.25, 0.25 < NDVI < 0.5, and NDVI > 0.5), retrieved from SPOT-VGT decadal images. A relative soil moisture index, ranging between 0 (for the driest surfaces) and 1 (for saturated soils), is proposed for each date, with a resolution of 1 km. The retrieved soil moistures are validated by means of ground measurements based on continuous thetaprobe measurements, as well as low-resolution (25 km) ERS and ASCAT soil moisture products from the Vienna University of Technology (TU Wien). A qualitative relationship between spatiotemporal variations of moisture and precipitation is also discussed.

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Using ENVISAT ASAR Global Mode Data for Surface Soil Moisture Retrieval Over Oklahoma, USA

Cited by 179 publications

References 68 publications

Intercomparison of Soil Moisture Retrievals From In Situ, ASAR, and ECV SM Data Sets Over Different European Sites

Intercomparison of Soil Moisture Retrievals From In Situ, ASAR, and ECV SM Data Sets Over Different European Sites

Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?

Soil moisture mapping in a semiarid region, based on ASAR/Wide Swath satellite data

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