Trend-preserving blending of passive and active microwave soil moisture retrievals

Liu, Y. Y.; Dorigo, Wouter; Parinussa, Robert; Jeu, R. A. M. de; Wagner, Wolfgang; McCabe, Matthew F.; Evans, Jason P.; Dijk, Albert I. J. M. van

doi:10.1016/j.rse.2012.03.014

Cited by 684 publications

(560 citation statements)

References 61 publications

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“…In addition, satellite microwave soil moisture observations (MW-SMO) from a newly developed global dataset [42]) were also used to estimate summer surface soil moisture variability during the period 1982-2010. This soil moisture dataset is based on the statistical blending of daily passive and active satellite microwave observations between November 1978 and December 2010 on a 0.25 • × 0.25 • regular grid.…”

Section: Vegetation Photosynthetic Activitymentioning

confidence: 99%

“…The historical paucity of observational datasets of soil moisture dynamics has been notably improved by the recent release of a multi-satellite product of surface soil moisture with global coverage for the period 1979-2010 [42] and an improved high-resolution global dataset of the self-calibrating Palmer Drought Severity Index (scPDSI) based on historical monthly meteorological observations since 1901 [43]. Progress has also been made in producing improved estimates of seasonal snow mass dynamics by assimilating ground-based measurements with historical satellite observations within a consistent modeling framework [44].…”

Section: Introductionmentioning

confidence: 99%

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Temperature and Snow-Mediated Moisture Controls of Summer Photosynthetic Activity in Northern Terrestrial Ecosystems between 1982 and 2011

et al. 2014

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Recent warming has stimulated the productivity of boreal and Arctic vegetation by reducing temperature limitations. However, several studies have hypothesized that warming may have also increased moisture limitations because of intensified summer drought severity. Establishing the connections between warming and drought stress has been difficult because soil moisture observations are scarce. Here we use recently developed gridded datasets of moisture variability to investigate the links between warming and changes in available soil moisture and summer vegetation photosynthetic activity at northern latitudes (>45 • N) based on the Normalized Difference Vegetation Index (NDVI) since 1982. Moisture and temperature exert a significant influence on the interannual variability of Remote Sens. 2014, 6 1391 summer NDVI over about 29% (mean r 2 = 0.29 ± 0.16) and 43% (mean r 2 = 0.25 ± 0.12) of the northern vegetated land, respectively. Rapid summer warming since the late 1980s (∼0.7 • C) has increased evapotranspiration demand and consequently summer drought severity, but contrary to earlier suggestions it has not changed the dominant climate controls of NDVI over time. Furthermore, changes in snow dynamics (accumulation and melting) appear to be more important than increased evaporative demand in controlling changes in summer soil moisture availability and NDVI in moisture-sensitive regions of the boreal forest. In boreal North America, forest NDVI declines are more consistent with reduced snowpack rather than with temperature-induced increases in evaporative demand as suggested in earlier studies. Moreover, summer NDVI variability over about 28% of the northern vegetated land is not significantly associated with moisture or temperature variability, yet most of this land shows increasing NDVI trends. These results suggest that changes in snow accumulation and melt, together with other possibly non-climatic factors are likely to play a significant role in modulating regional ecosystem responses to the projected warming and increase in evapotranspiration demand during the coming decades.

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Section: Vegetation Photosynthetic Activitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Temperature and Snow-Mediated Moisture Controls of Summer Photosynthetic Activity in Northern Terrestrial Ecosystems between 1982 and 2011

et al. 2014

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“…For example, satellite-based soil moisture may be used for estimation of near-future vegetation health (Qiu et al 2014), improved calculation of crop water requirement (McNelly et al 2015) and operational drought warnings (Enenkel et al 2016). EODC currently leads the second phase of the ESA Climate Change Initiative Soil Moisture project, providing the operational framework for merging more than a dozen of satellite data sets into consistent long-term soil moisture data records (Liu et al 2012(Liu et al , 2011Wagner et al 2012).…”

Section: Pilot Servicesmentioning

confidence: 99%

Development of an Earth Observation Cloud Platform in Support to Water Resources Monitoring

Bucur

Wagner

Elefante

et al. 2018

Earth Observation Open Science and Innovation

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Earth observation (EO) satellites collect verifiable observations that allow tracing natural and anthropogenic changes from local to global scale over several decades. Multi-decadal data sets are already available from various types of EO sensors, but their effective exploitation is hindered by the lack of data centres which offer dedicated EO processing chains and high-performance processing (HPC) capabilities. Recognizing this need, TU Wien founded the EODC Earth Observation Data Centre for Water Resources Monitoring together with other Austrian partners in May 2014 as a public-private partnership. The EODC aims at providing an independent science-driven platform that is transparent for its users and offering a high diversity and flexibility in terms of data sets and algorithms used. In this contribution, we describe the collaborative approach followed by EODC to build up its infrastructure and services and briefly introduce three pilot services.A. Bucur ( ) • S. Elefante • V. Naeimi

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“…Several studies have demonstrated soil moisture estimation from space using passive microwave (e.g., [2][3][4][5]) and active microwave (scatterometer) (e.g., [4,6,7]) at a coarse (25-150 km) spatial resolution. On the other hand, active microwave SAR data have been successfully used to retrieve the soil moisture at a finer (less than 100 m) spatial resolution but with a coarse (approximately 3 weeks) temporal resolution [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Several studies suggested spatial downscaling of passive microwave soil moisture products using physical and statistical approaches (e.g., [12][13][14][15][16][17]) or by assimilating coarse scale soil moisture into a Land Data Assimilation System (LDAS) (e.g., [18]). However, few studies have demonstrated merging the active and passive microwave soil moisture [4,19] to improve the spatial and temporal availability at a moderate spatial resolution. The spatial downscaling using physical approaches are based on the assumption that the evaporative flux is controlled by the amount of water available in the top surface layer [12,15].…”

Section: Introductionmentioning

confidence: 99%

MAPSM: A Spatio-Temporal Algorithm for Merging Soil Moisture from Active and Passive Microwave Remote Sensing

et al. 2016

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Simple Summary: -A novel algorithm delivering high resolution soil moisture maps is developed by merging active (SAR) and passive microwave.-MAPSM is based on the concept of Water Change Capacity. -A case study using MAPSM is presented by using the RADARSAT-2 and SMOS retrieved soil moisture data products over Berambadi watershed, Karnataka, India. -The algorithm parameters show scalability from the spatial resolution of 20 m to 2000 m.Abstract: Availability of soil moisture observations at a high spatial and temporal resolution is a prerequisite for various hydrological, agricultural and meteorological applications. In the current study, a novel algorithm for merging soil moisture from active microwave (SAR) and passive microwave is presented. The MAPSM algorithm-Merge Active and Passive microwave Soil Moisture-uses a spatio-temporal approach based on the concept of the Water Change Capacity (WCC) which represents the amplitude and direction of change in the soil moisture at the fine spatial resolution. The algorithm is applied and validated during a period of 3 years spanning from 2010 to 2013 over the Berambadi watershed which is located in a semi-arid tropical region in the Karnataka state of south India. Passive microwave products are provided from ESA Level 2 soil moisture products derived from Soil Moisture and Ocean Salinity (SMOS) satellite (3 days temporal resolution and 40 km nominal spatial resolution). Active microwave are based on soil moisture retrievals from 30 images of RADARSAT-2 data (24 days temporal resolution and 20 m spatial resolution). The results show that MAPSM is able to provide a good estimate of soil moisture at a spatial resolution of 500 m with an RMSE of 0.025 m 3 /m 3 and 0.069 m 3 /m 3 when comparing it to soil moisture from RADARSAT-2 and in-situ measurements, respectively. The use of Sentinel-1 and RISAT products in MAPSM algorithm is envisioned over other areas where high number of revisits is available. This will need an update of the algorithm to take into account the angle sampling and resolution of Sentinel-1 and RISAT data.

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Trend-preserving blending of passive and active microwave soil moisture retrievals

Cited by 684 publications

References 61 publications

Temperature and Snow-Mediated Moisture Controls of Summer Photosynthetic Activity in Northern Terrestrial Ecosystems between 1982 and 2011

Temperature and Snow-Mediated Moisture Controls of Summer Photosynthetic Activity in Northern Terrestrial Ecosystems between 1982 and 2011

Development of an Earth Observation Cloud Platform in Support to Water Resources Monitoring

MAPSM: A Spatio-Temporal Algorithm for Merging Soil Moisture from Active and Passive Microwave Remote Sensing

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