A New Soil Moisture Downscaling Approach for SMAP, SMOS, and ASCAT by Predicting Sub-Grid Variability

Montzka, Carsten; Rötzer, Kathrina; Bogena, Heye; Sánchez, Nilda; Vereecken, Harry

doi:10.3390/rs10030427

Cited by 51 publications

(40 citation statements)

References 129 publications

(176 reference statements)

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“…The combination extracts the relative advantages of the two sensing techniques, as there is a tradeoff between resolution and soil moisture sensing sensitivity between active and passive microwave measurements [285]. Fusion methods include temporal change detection methods [286], Bayesian merging approaches [287], statistical disaggregation [285,288,289], and physics-based covariation algorithms [290][291][292]. Other methods retrieve vegetation variables from active microwave measurements for the utilization of passive microwave soil moisture inversion [293,294].…”

Section: Combining Active and Passive Microwave Sensorsmentioning

confidence: 99%

Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

Lausch

Baade

Bannehr³

et al. 2019

Remote Sensing

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In the face of rapid global change it is imperative to preserve geodiversity for the overall conservation of biodiversity. Geodiversity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystem organization. Despite the great importance of geodiversity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geodiversity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques. Initially, the definitions for geodiversity along with its five essential characteristics are provided, with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral trait variations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geodiversity characteristics can be recorded. The paper provides an overview of those geotraits.

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Section: Combining Active and Passive Microwave Sensorsmentioning

confidence: 99%

Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

Lausch

Baade

Bannehr³

et al. 2019

Remote Sensing

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“…To estimate soil moisture at higher resolution, active microwave synthetic aperture radars (SARs) have been employed (such as Sentinel-1), which are capable of providing 1-km daily soil moisture products [42,43]. Other methods exploit optical and thermal images to downscale low-resolution products to 1 km (e.g., [44]) often in combination with modelling approaches [45].…”

Section: Introductionmentioning

confidence: 99%

An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources

Zeng

Romano

et al. 2020

Water

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The past decades have seen rapid advancements in space-based monitoring of essential water cycle variables, providing products related to precipitation, evapotranspiration, and soil moisture, often at tens of kilometer scales. Whilst these data effectively characterize water cycle variability at regional to global scales, they are less suitable for sustainable management of local water resources, which needs detailed information to represent the spatial heterogeneity of soil and vegetation. The following questions are critical to effectively exploit information from remotely sensed and in situ Earth observations (EOs): How to downscale the global water cycle products to the local scale using multiple sources and scales of EO data? How to explore and apply the downscaled information at the management level for a better understanding of soil-water-vegetation-energy processes? How can such fine-scale information be used to improve the management of soil and water resources? An integrative information flow (i.e., iAqueduct theoretical framework) is developed to close the gaps between satellite water cycle products and local information necessary for sustainable management of water resources. The integrated iAqueduct framework aims to address the abovementioned scientific questions by combining medium-resolution (10 m–1 km) Copernicus satellite data with high-resolution (cm) unmanned aerial system (UAS) data, in situ observations, analytical- and physical-based models, as well as big-data analytics with machine learning algorithms. This paper provides a general overview of the iAqueduct theoretical framework and introduces some preliminary results.

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“…Piles et al (2011) suggested a downscaling scheme to cope with this shortcoming of remotely sensed soil moisture. Several further methods have been developed to enhance the spatial resolution of coarse global soil moisture products (Verhoest et al, 2015;Im et al, 2016;Colliander, Fisher, et al, 2017;Jin et al, 2017;Montzka et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Validation of satellite soil moisture in the absence of <i>in situ</i> soil moisture: the case of the Tropical Yankin Basin

Badou¹,

Diekkrüger²,

Montzka³

2019

SA J of Geomatics

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Soil moisture is known to be important in hydrology, agronomy, flood and drought forecasting. Acquisition of in situ soil moisture data is time consuming, costly, and does not cover the scale required for basin analysis. The consideration of remotely-sensed soil moisture is therefore promising. However, considering the limitations of satellite data, there is a need to check their validity prior to their utilization for impact studies. This, in turn, poses a problem in the absence of in situ soil moisture. The present study suggests a methodology for testing the validity of remotelysensed soil moisture without in situ soil moisture. Hydrological models with a detailed soil moisture routine are calibrated and validated with measured stream flows. The most behavioural solutions of modelled soil moistures are averaged, and used as proxy measurements. This methodology was applied to the Yankin Basin (8,171 km 2), a tributary of the Niger River Basin. The soil moistures of three hydrological models (UHP-HRU, SWAT and WaSiM) used as proxy were compared with the daily ESA-CCI soil moisture for a four year period (2005-2008). The coefficient of determination (R 2), bias and visual inspection were used as quality criteria. A rather small bias ranging from-0.01cm 3 /cm 3 (SWAT & UHP-HRU) to-0.04cm 3 /cm 3 (WaSiM &UHP-HRU) was determined as well as good R 2 varying between 0.71 (SWAT & UHP-HRU) and 0.81 (WaSiM & SWAT & UHP-HRU). The ESA-CCI soil moisture was therefore judged as reliable for the study area. More important, this research shows that averaging soil moistures from different hydrological models provides valuable proxy measurements for testing the reliability of satellite soil moistures.

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A New Soil Moisture Downscaling Approach for SMAP, SMOS, and ASCAT by Predicting Sub-Grid Variability

Cited by 51 publications

References 129 publications

Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources

Validation of satellite soil moisture in the absence of <i>in situ</i> soil moisture: the case of the Tropical Yankin Basin

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